WorldWideScience

Sample records for model based controller

  1. Predictor-Based Model Reference Adaptive Control

    Science.gov (United States)

    Lavretsky, Eugene; Gadient, Ross; Gregory, Irene M.

    2010-01-01

    This paper is devoted to the design and analysis of a predictor-based model reference adaptive control. Stable adaptive laws are derived using Lyapunov framework. The proposed architecture is compared with the now classical model reference adaptive control. A simulation example is presented in which numerical evidence indicates that the proposed controller yields improved transient characteristics.

  2. Model based development of engine control algorithms

    NARCIS (Netherlands)

    Dekker, H.J.; Sturm, W.L.

    1996-01-01

    Model based development of engine control systems has several advantages. The development time and costs are strongly reduced because much of the development and optimization work is carried out by simulating both engine and control system. After optimizing the control algorithm it can be executed

  3. Model-Based Power Plant Master Control

    Energy Technology Data Exchange (ETDEWEB)

    Boman, Katarina; Thomas, Jean; Funkquist, Jonas

    2010-08-15

    The main goal of the project has been to evaluate the potential of a coordinated master control for a solid fuel power plant in terms of tracking capability, stability and robustness. The control strategy has been model-based predictive control (MPC) and the plant used in the case study has been the Vattenfall power plant Idbaecken in Nykoeping. A dynamic plant model based on nonlinear physical models was used to imitate the true plant in MATLAB/SIMULINK simulations. The basis for this model was already developed in previous Vattenfall internal projects, along with a simulation model of the existing control implementation with traditional PID controllers. The existing PID control is used as a reference performance, and it has been thoroughly studied and tuned in these previous Vattenfall internal projects. A turbine model was developed with characteristics based on the results of steady-state simulations of the plant using the software EBSILON. Using the derived model as a representative for the actual process, an MPC control strategy was developed using linearization and gain-scheduling. The control signal constraints (rate of change) and constraints on outputs were implemented to comply with plant constraints. After tuning the MPC control parameters, a number of simulation scenarios were performed to compare the MPC strategy with the existing PID control structure. The simulation scenarios also included cases highlighting the robustness properties of the MPC strategy. From the study, the main conclusions are: - The proposed Master MPC controller shows excellent set-point tracking performance even though the plant has strong interactions and non-linearity, and the controls and their rate of change are bounded. - The proposed Master MPC controller is robust, stable in the presence of disturbances and parameter variations. Even though the current study only considered a very small number of the possible disturbances and modelling errors, the considered cases are

  4. Model Based Control of Reefer Container Systems

    DEFF Research Database (Denmark)

    Sørensen, Kresten Kjær

    This thesis is concerned with the development of model based control for the Star Cool refrigerated container (reefer) with the objective of reducing energy consumption. This project has been carried out under the Danish Industrial PhD programme and has been financed by Lodam together with the Da......This thesis is concerned with the development of model based control for the Star Cool refrigerated container (reefer) with the objective of reducing energy consumption. This project has been carried out under the Danish Industrial PhD programme and has been financed by Lodam together...

  5. Model Based Control of Refrigeration Systems

    DEFF Research Database (Denmark)

    Larsen, Lars Finn Sloth

    for automation of these procedures, that is to incorporate some "intelligence" in the control system, this project was started up. The main emphasis of this work has been on model based methods for system optimizing control in supermarket refrigeration systems. The idea of implementing a system optimizing...... control is to let an optimization procedure take over the task of operating the refrigeration system and thereby replace the role of the operator in the traditional control structure. In the context of refrigeration systems, the idea is to divide the optimizing control structure into two parts: A part...... optimizing the steady state operation "set-point optimizing control" and a part optimizing dynamic behaviour of the system "dynamical optimizing control". A novel approach for set-point optimization will be presented. The general idea is to use a prediction of the steady state, for computation of the cost...

  6. Model based design introduction: modeling game controllers to microprocessor architectures

    Science.gov (United States)

    Jungwirth, Patrick; Badawy, Abdel-Hameed

    2017-04-01

    We present an introduction to model based design. Model based design is a visual representation, generally a block diagram, to model and incrementally develop a complex system. Model based design is a commonly used design methodology for digital signal processing, control systems, and embedded systems. Model based design's philosophy is: to solve a problem - a step at a time. The approach can be compared to a series of steps to converge to a solution. A block diagram simulation tool allows a design to be simulated with real world measurement data. For example, if an analog control system is being upgraded to a digital control system, the analog sensor input signals can be recorded. The digital control algorithm can be simulated with the real world sensor data. The output from the simulated digital control system can then be compared to the old analog based control system. Model based design can compared to Agile software develop. The Agile software development goal is to develop working software in incremental steps. Progress is measured in completed and tested code units. Progress is measured in model based design by completed and tested blocks. We present a concept for a video game controller and then use model based design to iterate the design towards a working system. We will also describe a model based design effort to develop an OS Friendly Microprocessor Architecture based on the RISC-V.

  7. Model based control of refrigeration systems

    Energy Technology Data Exchange (ETDEWEB)

    Sloth Larsen, L.F.

    2005-11-15

    The subject for this Ph.D. thesis is model based control of refrigeration systems. Model based control covers a variety of different types of controls, that incorporates mathematical models. In this thesis the main subject therefore has been restricted to deal with system optimizing control. The optimizing control is divided into two layers, where the system oriented top layers deals with set-point optimizing control and the lower layer deals with dynamical optimizing control in the subsystems. The thesis has two main contributions, i.e. a novel approach for set-point optimization and a novel approach for desynchronization based on dynamical optimization. The focus in the development of the proposed set-point optimizing control has been on deriving a simple and general method, that with ease can be applied on various compositions of the same class of systems, such as refrigeration systems. The method is based on a set of parameter depended static equations describing the considered process. By adapting the parameters to the given process, predict the steady state and computing a steady state gradient of the cost function, the process can be driven continuously towards zero gradient, i.e. the optimum (if the cost function is convex). The method furthermore deals with system constrains by introducing barrier functions, hereby the best possible performance taking the given constrains in to account can be obtained, e.g. under extreme operational conditions. The proposed method has been applied on a test refrigeration system, placed at Aalborg University, for minimization of the energy consumption. Here it was proved that by using general static parameter depended system equations it was possible drive the set-points close to the optimum and thus reduce the power consumption with up to 20%. In the dynamical optimizing layer the idea is to optimize the operation of the subsystem or the groupings of subsystems, that limits the obtainable system performance. In systems

  8. Model based design of electronic throttle control

    Science.gov (United States)

    Cherian, Fenin; Ranjan, Ashish; Bhowmick, Pathikrit; Rammohan, A.

    2017-11-01

    With the advent of torque based Engine Management Systems, the precise control and robust performance of the throttle body becomes a key factor in the overall performance of the vehicle. Electronic Throttle Control provides benefits such as improved air-fuel ratio for improving the vehicle performance and lower exhausts emissions to meet the stringent emission norms. Modern vehicles facilitate various features such as Cruise Control, Traction Control, Electronic Stability Program and Pre-crash systems. These systems require control over engine power without driver intervention, which is not possible with conventional mechanical throttle system. Thus these systems are integrated to function with the electronic throttle control. However, due to inherent non-linearities in the throttle body, the control becomes a difficult task. In order to eliminate the influence of this hysteresis at the initial operation of the butterfly valve, a control to compensate the shortage must be added to the duty required for starting throttle operation when the initial operation is detected. Therefore, a lot of work is being done in this field to incorporate the various nonlinearities to achieve robust control. In our present work, the ETB was tested to verify the working of the system. Calibration of the TPS sensors was carried out in order to acquire accurate throttle opening angle. The response of the calibrated system was then plotted against a step input signal. A linear model of the ETB was prepared using Simulink and its response was compared with the experimental data to find out the initial deviation of the model from the actual system. To reduce this deviation, non-linearities from existing literature were introduced to the system and a response analysis was performed to check the deviation from the actual system. Based on this investigation, an introduction of a new nonlinearity parameter can be used in future to reduce the deviation further making the control of the ETB more

  9. A model-based control system concept

    International Nuclear Information System (INIS)

    Aarzen, K.E.

    1992-12-01

    This paper presents an overview of a new concept for DCSs developed within the KBRTCS (Knowledge-Based Real-Time Control Systems) project performed between 1988 and 1991 as a part of the Swedish IT4 programme. The partners of the project have been the Department of Automatic Control at Lund University, Asea Brown Boveri, and during parts of the project, SattControl, and TeleLogic. The aim of the project has been to develop a concept for future generations of DCSs based on a plant database containing a description of the plant together with the control system. The database is object-based and supports multiple views of an objects. A demonstrator is presented where a DCS system of this type is emulated. The demonstrator contains a number of control, monitoring, and diagnosis applications that execute in real time against a simulations of Steritherm sterilization process. (25 refs.)

  10. Model-based accelerator controls: What, why and how

    International Nuclear Information System (INIS)

    Sidhu, S.S.

    1987-01-01

    Model-based control is defined as a gamut of techniques whose aim is to improve the reliability of an accelerator and enhance the capabilities of the operator, and therefore of the whole control system. The aim of model-based control is seen as gradually moving the function of model-reference from the operator to the computer. The role of the operator in accelerator control and the need for and application of model-based control are briefly summarized

  11. Model Predictive Control based on Finite Impulse Response Models

    DEFF Research Database (Denmark)

    Prasath, Guru; Jørgensen, John Bagterp

    2008-01-01

    We develop a regularized l2 finite impulse response (FIR) predictive controller with input and input-rate constraints. Feedback is based on a simple constant output disturbance filter. The performance of the predictive controller in the face of plant-model mismatch is investigated by simulations...... and related to the uncertainty of the impulse response coefficients. The simulations can be used to benchmark l2 MPC against FIR based robust MPC as well as to estimate the maximum performance improvements by robust MPC....

  12. Towards automatic model based controller design for reconfigurable plants

    DEFF Research Database (Denmark)

    Michelsen, Axel Gottlieb; Stoustrup, Jakob; Izadi-Zamanabadi, Roozbeh

    2008-01-01

    This paper introduces model-based Plug and Play Process Control, a novel concept for process control, which allows a model-based control system to be reconfigured when a sensor or an actuator is plugged into a controlled process. The work reported in this paper focuses on composing a monolithic m...

  13. On Model Based Synthesis of Embedded Control Software

    OpenAIRE

    Alimguzhin, Vadim; Mari, Federico; Melatti, Igor; Salvo, Ivano; Tronci, Enrico

    2012-01-01

    Many Embedded Systems are indeed Software Based Control Systems (SBCSs), that is control systems whose controller consists of control software running on a microcontroller device. This motivates investigation on Formal Model Based Design approaches for control software. Given the formal model of a plant as a Discrete Time Linear Hybrid System and the implementation specifications (that is, number of bits in the Analog-to-Digital (AD) conversion) correct-by-construction control software can be...

  14. PI controller based model reference adaptive control for nonlinear

    African Journals Online (AJOL)

    user

    Keywords: Model Reference Adaptive Controller (MRAC), Artificial Neural ... attention, and many new approaches have been applied to practical process .... effectiveness of proposed method, it is compared with the simulation results of the ...

  15. Abstracting event-based control models for high autonomy systems

    Science.gov (United States)

    Luh, Cheng-Jye; Zeigler, Bernard P.

    1993-01-01

    A high autonomy system needs many models on which to base control, management, design, and other interventions. These models differ in level of abstraction and in formalism. Concepts and tools are needed to organize the models into a coherent whole. The paper deals with the abstraction processes for systematic derivation of related models for use in event-based control. The multifaceted modeling methodology is briefly reviewed. The morphism concepts needed for application to model abstraction are described. A theory for supporting the construction of DEVS models needed for event-based control is then presented. An implemented morphism on the basis of this theory is also described.

  16. An Industrial Model Based Disturbance Feedback Control Scheme

    DEFF Research Database (Denmark)

    Kawai, Fukiko; Nakazawa, Chikashi; Vinther, Kasper

    2014-01-01

    This paper presents a model based disturbance feedback control scheme. Industrial process systems have been traditionally controlled by using relay and PID controller. However these controllers are affected by disturbances and model errors and these effects degrade control performance. The authors...... propose a new control method that can decrease the negative impact of disturbance and model errors. The control method is motivated by industrial practice by Fuji Electric. Simulation tests are examined with a conventional PID controller and the disturbance feedback control. The simulation results...

  17. Perti Net-Based Workflow Access Control Model

    Institute of Scientific and Technical Information of China (English)

    陈卓; 骆婷; 石磊; 洪帆

    2004-01-01

    Access control is an important protection mechanism for information systems. This paper shows how to make access control in workflow system. We give a workflow access control model (WACM) based on several current access control models. The model supports roles assignment and dynamic authorization. The paper defines the workflow using Petri net. It firstly gives the definition and description of the workflow, and then analyzes the architecture of the workflow access control model (WACM). Finally, an example of an e-commerce workflow access control model is discussed in detail.

  18. Mechanics and model-based control of advanced engineering systems

    CERN Document Server

    Irschik, Hans; Krommer, Michael

    2014-01-01

    Mechanics and Model-Based Control of Advanced Engineering Systems collects 32 contributions presented at the International Workshop on Advanced Dynamics and Model Based Control of Structures and Machines, which took place in St. Petersburg, Russia in July 2012. The workshop continued a series of international workshops, which started with a Japan-Austria Joint Workshop on Mechanics and Model Based Control of Smart Materials and Structures and a Russia-Austria Joint Workshop on Advanced Dynamics and Model Based Control of Structures and Machines. In the present volume, 10 full-length papers based on presentations from Russia, 9 from Austria, 8 from Japan, 3 from Italy, one from Germany and one from Taiwan are included, which represent the state of the art in the field of mechanics and model based control, with particular emphasis on the application of advanced structures and machines.

  19. Fuzzy model-based control of a nuclear reactor

    International Nuclear Information System (INIS)

    Van Den Durpel, L.; Ruan, D.

    1994-01-01

    The fuzzy model-based control of a nuclear power reactor is an emerging research topic world-wide. SCK-CEN is dealing with this research in a preliminary stage, including two aspects, namely fuzzy control and fuzzy modelling. The aim is to combine both methodologies in contrast to conventional model-based PID control techniques, and to state advantages of including fuzzy parameters as safety and operator feedback. This paper summarizes the general scheme of this new research project

  20. Model-based control for automotive applications

    NARCIS (Netherlands)

    Naus, G.J.L.

    2010-01-01

    The number of distributed control systems in modern vehicles has increased exponentially over the past decades. Today’s performance improvements and innovations in the automotive industry are often resolved using embedded control systems. As a result, a modern vehicle can be regarded as a complex

  1. Predictive Control Based upon State Space Models

    Directory of Open Access Journals (Sweden)

    Jens G. Balchen

    1989-04-01

    Full Text Available Repetitive online computation of the control vector by solving the optimal control problem of a non-linear multivariable process with arbitrary performance indices is investigated. Two different methods are considered in the search for an optimal, parameterized control vector: Pontryagin's Maximum Principle and optimization by using the performance index and its gradient directly. Unfortunately, solving this optimization problem has turned out to be a rather time-consuming task which has resulted in a time delay that cannot be accepted when the actual process is exposed to rapidly-varying disturbances. However, an instantaneous feedback strategy operating in parallel with the original control aogorithm was found to be able to cope with this problem.

  2. Model-Based Development of Control Systems for Forestry Cranes

    Directory of Open Access Journals (Sweden)

    Pedro La Hera

    2015-01-01

    Full Text Available Model-based methods are used in industry for prototyping concepts based on mathematical models. With our forest industry partners, we have established a model-based workflow for rapid development of motion control systems for forestry cranes. Applying this working method, we can verify control algorithms, both theoretically and practically. This paper is an example of this workflow and presents four topics related to the application of nonlinear control theory. The first topic presents the system of differential equations describing the motion dynamics. The second topic presents nonlinear control laws formulated according to sliding mode control theory. The third topic presents a procedure for model calibration and control tuning that are a prerequisite to realize experimental tests. The fourth topic presents the results of tests performed on an experimental crane specifically equipped for these tasks. Results of these studies show the advantages and disadvantages of these control algorithms, and they highlight their performance in terms of robustness and smoothness.

  3. Model-based Control of a Bottom Fired Marine Boiler

    DEFF Research Database (Denmark)

    Solberg, Brian; Karstensen, Claus M. S.; Andersen, Palle

    2005-01-01

    This paper focuses on applying model based MIMO control to minimize variations in water level for a specific boiler type. A first principles model is put up. The model is linearized and an LQG controller is designed. Furthermore the benefit of using a steam °ow measurement is compared to a strategy...... relying on estimates of the disturbance. Preliminary tests at the boiler system show that the designed controller is able to control the boiler process. Furthermore it can be concluded that relying on estimates of the steam flow in the control strategy does not decrease the controller performance...

  4. Model-based Control of a Bottom Fired Marine Boiler

    DEFF Research Database (Denmark)

    Solberg, Brian; Karstensen, Claus M. S.; Andersen, Palle

    This paper focuses on applying model based MIMO control to minimize variations in water level for a specific boiler type. A first principles model is put up. The model is linearized and an LQG controller is designed. Furthermore the benefit of using a steam °ow measurement is compared to a strategy...... relying on estimates of the disturbance. Preliminary tests at the boiler system show that the designed controller is able to control the boiler process. Furthermore it can be concluded that relying on estimates of the steam flow in the control strategy does not decrease the controller performance...

  5. Model-based control of hopper dredgers

    NARCIS (Netherlands)

    Braaksma, J.

    2008-01-01

    The modern trailing suction hopper dredgers are advanced ships that are equipped with many automation systems that can be controlled with integrated computer systems from the bridge. From the operators it is expected that they generate the right set-points for all these systems. The latest ships are

  6. Wind Turbine Control: Robust Model Based Approach

    DEFF Research Database (Denmark)

    Mirzaei, Mahmood

    . Wind turbines are the most common wind energy conversion systems and are hoped to be able to compete economically with fossil fuel power plants in near future. However this demands better technology to reduce the price of electricity production. Control can play an essential part in this context....... This is because, on the one hand, control methods can decrease the cost of energy by keeping the turbine close to its maximum efficiency. On the other hand, they can reduce structural fatigue and therefore increase the lifetime of the wind turbine. The power produced by a wind turbine is proportional...... to the square of its rotor radius, therefore it seems reasonable to increase the size of the wind turbine in order to capture more power. However as the size increases, the mass of the blades increases by cube of the rotor size. This means in order to keep structural feasibility and mass of the whole structure...

  7. Stabilization of model-based networked control systems

    Energy Technology Data Exchange (ETDEWEB)

    Miranda, Francisco [CIDMA, Universidade de Aveiro, Aveiro (Portugal); Instituto Politécnico de Viana do Castelo, Viana do Castelo (Portugal); Abreu, Carlos [Instituto Politécnico de Viana do Castelo, Viana do Castelo (Portugal); CMEMS-UMINHO, Universidade do Minho, Braga (Portugal); Mendes, Paulo M. [CMEMS-UMINHO, Universidade do Minho, Braga (Portugal)

    2016-06-08

    A class of networked control systems called Model-Based Networked Control Systems (MB-NCSs) is considered. Stabilization of MB-NCSs is studied using feedback controls and simulation of stabilization for different feedbacks is made with the purpose to reduce the network trafic. The feedback control input is applied in a compensated model of the plant that approximates the plant dynamics and stabilizes the plant even under slow network conditions. Conditions for global exponential stabilizability and for the choosing of a feedback control input for a given constant time between the information moments of the network are derived. An optimal control problem to obtain an optimal feedback control is also presented.

  8. Model-Based Engineering of Supervisory Controllers using CIF

    NARCIS (Netherlands)

    Schiffelers, R.R.H.; Theunissen, R.J.M.; Beek, van D.A.; Rooda, J.E.; Levendovsky, T.; Lengyel, L.

    2009-01-01

    In the Model-Based Engineering (MBE) paradigm, models are the core elements in the design process of a system from its requirements to the actual implementation of the system. By means of Supervisory Control Theory (SCT), supervisory controllers (supervisors) can be synthesized instead of

  9. Task Delegation Based Access Control Models for Workflow Systems

    Science.gov (United States)

    Gaaloul, Khaled; Charoy, François

    e-Government organisations are facilitated and conducted using workflow management systems. Role-based access control (RBAC) is recognised as an efficient access control model for large organisations. The application of RBAC in workflow systems cannot, however, grant permissions to users dynamically while business processes are being executed. We currently observe a move away from predefined strict workflow modelling towards approaches supporting flexibility on the organisational level. One specific approach is that of task delegation. Task delegation is a mechanism that supports organisational flexibility, and ensures delegation of authority in access control systems. In this paper, we propose a Task-oriented Access Control (TAC) model based on RBAC to address these requirements. We aim to reason about task from organisational perspectives and resources perspectives to analyse and specify authorisation constraints. Moreover, we present a fine grained access control protocol to support delegation based on the TAC model.

  10. Development of a robust model-based reactivity control system

    International Nuclear Information System (INIS)

    Rovere, L.A.; Otaduy, P.J.; Brittain, C.R.

    1990-01-01

    This paper describes the development and implementation of a digital model-based reactivity control system that incorporates a knowledge of the plant physics into the control algorithm to improve system performance. This controller is composed of a model-based module and modified proportional-integral-derivative (PID) module. The model-based module has an estimation component to synthesize unmeasurable process variables that are necessary for the control action computation. These estimated variables, besides being used within the control algorithm, will be used for diagnostic purposes by a supervisory control system under development. The PID module compensates for inaccuracies in model coefficients by supplementing the model-based output with a correction term that eliminates any demand tracking or steady state errors. This control algorithm has been applied to develop controllers for a simulation of liquid metal reactors in a multimodular plant. It has shown its capability to track demands in neutron power much more accurately than conventional controllers, reducing overshoots to almost negligible value while providing a good degree of robustness to unmodeled dynamics. 10 refs., 4 figs

  11. Rate-Based Model Predictive Control of Turbofan Engine Clearance

    Science.gov (United States)

    DeCastro, Jonathan A.

    2006-01-01

    An innovative model predictive control strategy is developed for control of nonlinear aircraft propulsion systems and sub-systems. At the heart of the controller is a rate-based linear parameter-varying model that propagates the state derivatives across the prediction horizon, extending prediction fidelity to transient regimes where conventional models begin to lose validity. The new control law is applied to a demanding active clearance control application, where the objectives are to tightly regulate blade tip clearances and also anticipate and avoid detrimental blade-shroud rub occurrences by optimally maintaining a predefined minimum clearance. Simulation results verify that the rate-based controller is capable of satisfying the objectives during realistic flight scenarios where both a conventional Jacobian-based model predictive control law and an unconstrained linear-quadratic optimal controller are incapable of doing so. The controller is evaluated using a variety of different actuators, illustrating the efficacy and versatility of the control approach. It is concluded that the new strategy has promise for this and other nonlinear aerospace applications that place high importance on the attainment of control objectives during transient regimes.

  12. Economic MPC based on LPV model for thermostatically controlled loads

    DEFF Research Database (Denmark)

    Zemtsov, Nikita; Hlava, Jaroslav; Frantsuzova, Galina

    2017-01-01

    Rapid increase of the renewable energy share in electricity production requires optimization and flexibility of the power consumption side. Thermostatically controlled loads (TCLs) have a large potential for regulation service provision. Economic model predictive control (MPC) is an advanced...... control method which can be used to syncronize the power consumption with undispatchable renewable electricity production. Thermal behavior of TCLs can be described by linear models based on energy balance of the system. In some cases, parameters of the model may be time-varying. In this work, we present...... a modified economic MPC based on linear parameter-varying model. In particular, we provide an exact transformation from a standard economic MPC formulation to a linear program. We assume that the variables influencing the model parameters are known (predictable) for the prediction horizon of the controller...

  13. Fuzzy Logic Based Set-Point Weighting Controller Tuning for an Internal Model Control Based PID Controller

    Directory of Open Access Journals (Sweden)

    Maruthai Suresh

    2009-10-01

    Full Text Available Controller tuning is the process of adjusting the parameters of the selected controller to achieve optimum response for the controlled process. For many of the control problems, a satisfactory performance is obtained by using PID controllers. One of the main problems with mathematical models of physical systems is that the parameters used in the models cannot be determined with absolute accuracy. The values of the parameters may change with time or various effects. In these cases, conventional controller tuning methods suffer when trying a lot to produce optimum response. In order to overcome these difficulties a fuzzy logic based Set- Point weighting controller tuning method is proposed. The effectiveness of the proposed scheme is analyzed through computer simulation using SIMULINK software and the results are presented. The fuzzy logic based simulation results are compared with Cohen-Coon (CC, Ziegler- Nichols (ZN, Ziegler – Nichols with Set- Point weighting (ZN-SPW, Internal Model Control (IMC and Internal model based PID controller responses (IMC-PID. The effects of process modeling errors and the importance of controller tuning have been brought out using the proposed control scheme.

  14. Model-based dynamic control and optimization of gas networks

    Energy Technology Data Exchange (ETDEWEB)

    Hofsten, Kai

    2001-07-01

    by a structured sequential quadratic programming algorithm of Newton type. Each open loop problem is specified using a nonlinear prediction model. For each iteration of the quadratic programming procedure, a linear time variant prediction model is formulated. The suggested controller also handles time varying source capacity. Potential problems such as infeasibility and the security of the supply when facing a change in the status of the infrastructure of the transmission system under a transient customer load are treated. Comments on the infeasibility due to errors such as load forecast error, model error and state estimation error are also discussed. A simplified nonlinear model called the creep flow model is used to describe the fluid dynamics inside a natural gas transmission line. Different assumptions and reformulations of this model yield the different control, simulation and optimization models used in this thesis. The control of a single gas transmission line is investigated using linear model predictive control based on instant linearization of the nonlinear model. Model predictive control using a bi quadratic optimization model formulated from the creep flow model is also investigated. A distributed parameter control model of the gas dynamics for a transmission line is formulated. An analytic solution of this model is given with both Neuman boundary conditions and distributed supplies and loads. A transfer function model is developed expressing the dynamics between the defined output and the control and disturbance inputs of the transmission line. Based on the qualitative behaviour observed from the step responses of the solutions of the distributed parameter model formulated in this thesis, simplified transfer function models were developed. These control models expresses the dynamics of a natural gas transmission line with Neuman boundary control and load. Further, these models were used to design a control law, which is a combination of a Smith

  15. Model-based expert systems for linac computer controls

    International Nuclear Information System (INIS)

    Lee, M.J.

    1988-09-01

    The use of machine modeling and beam simulation programs for the control of accelerator operation has become standard practice. The success of a model-based control operation depends on how the parameter to be controlled is measured, how the measured data is analyzed, how the result of the analysis is interpreted, and how a solution is implemented. There is considerable interest in applying expert systems technology that can automate all of these processes. The design of an expert system to control the beam trajectory in linear accelerators will be discussed as an illustration of this approach. 4 figs., 1 tab

  16. Modeling and Control of CSTR using Model based Neural Network Predictive Control

    OpenAIRE

    Shrivastava, Piyush

    2012-01-01

    This paper presents a predictive control strategy based on neural network model of the plant is applied to Continuous Stirred Tank Reactor (CSTR). This system is a highly nonlinear process; therefore, a nonlinear predictive method, e.g., neural network predictive control, can be a better match to govern the system dynamics. In the paper, the NN model and the way in which it can be used to predict the behavior of the CSTR process over a certain prediction horizon are described, and some commen...

  17. An intelligent trust-based access control model for affective ...

    African Journals Online (AJOL)

    In this study, a fuzzy expert system Trust-Based Access Control (TBAC) model for improving the Quality of crowdsourcing using emotional affective computing is presented. This model takes into consideration a pre-processing module consisting of three inputs such as crowd-workers category, trust metric and emotional ...

  18. Model based controls and the AGS booster controls system architecture

    International Nuclear Information System (INIS)

    Casella, R.A.

    1987-01-01

    For the past three years the Accelerator Controls Section has been responsible for the development of the Heavy Ion Transfer Line (HITL) used to inject heavy ions created at the Tandem Van de Graaff into the Alternating Gradient Synchrotron (AGS). This was recognized as an opportunity to test new ideas for control of a beam line, which if successful, could be implemented in an upgrade of the existing control system for the AGS. The in place control system for the AGS consisted of DEC PDP10 computer as the primary computer interface to the accelerator via three control room consoles, and keeper of the device database. For the HITL project it was decided to make the control system a true distributed network putting more computing power down at the device level via intelligent subsystems. A network of Apollo workstations was added at the host level. Apollos run a distributed operating system and are connected to each other by the Domain Token Ring Network. The Apollos were seen as the new primary computers for consoles with each console containing at least one Apollo. These hosts and all other subsystems are connected to each other via an in house developed LAN (RELWAY). The design of the control system developed for HITL was mostly successful. The proposed AGS Booster is designed to be a synchrotron injector for the AGS. With the forthcoming development of the Booster for the AGS an opportunity has again developed to implement new ideas for accelerator control. One weakness of the HITL control system is the limited cpu power and poor debugging facilities of the stations

  19. GENI: A graphical environment for model-based control

    International Nuclear Information System (INIS)

    Kleban, S.; Lee, M.; Zambre, Y.

    1989-10-01

    A new method to operate machine and beam simulation programs for accelerator control has been developed. Existing methods, although cumbersome, have been used in control systems for commissioning and operation of many machines. We developed GENI, a generalized graphical interface to these programs for model-based control. This ''object-oriented''-like environment is described and some typical applications are presented. 4 refs., 5 figs

  20. Model based controls and the AGS booster controls system architecture

    International Nuclear Information System (INIS)

    Casella, R.A.

    1987-01-01

    The Heavy Ion Transfer Line used to inject heavy ions created at the Tandem Van de Graaff into the Alternating Gradient Synchrotron (AGS) is briefly discussed, particularly as regards its control system

  1. Pressure Control in Distillation Columns: A Model-Based Analysis

    DEFF Research Database (Denmark)

    Mauricio Iglesias, Miguel; Bisgaard, Thomas; Kristensen, Henrik

    2014-01-01

    A comprehensive assessment of pressure control in distillation columns is presented, including the consequences for composition control and energy consumption. Two types of representative control structures are modeled, analyzed, and benchmarked. A detailed simulation test, based on a real...... industrial distillation column, is used to assess the differences between the two control structures and to demonstrate the benefits of pressure control in the operation. In the second part of the article, a thermodynamic analysis is carried out to establish the influence of pressure on relative volatility...

  2. Sensor-Based Model Driven Control Strategy for Precision Irrigation

    Directory of Open Access Journals (Sweden)

    Camilo Lozoya

    2016-01-01

    Full Text Available Improving the efficiency of the agricultural irrigation systems substantially contributes to sustainable water management. This improvement can be achieved through an automated irrigation system that includes a real-time control strategy based on the water, soil, and crop relationship. This paper presents a model driven control strategy applied to an irrigation system, in order to make an efficient use of water for large crop fields, that is, applying the correct amount of water in the correct place at the right moment. The proposed model uses a predictive algorithm that senses soil moisture and weather variables, to determine optimal amount of water required by the crop. This proposed approach is evaluated against a traditional irrigation system based on the empirical definition of time periods and against a basic soil moisture control system. Results indicate that the use of a model predictive control in an irrigation system achieves a higher efficiency and significantly reduce the water consumption.

  3. Mechatronic Model Based Computed Torque Control of a Parallel Manipulator

    Directory of Open Access Journals (Sweden)

    Zhiyong Yang

    2008-11-01

    Full Text Available With high speed and accuracy the parallel manipulators have wide application in the industry, but there still exist many difficulties in the actual control process because of the time-varying and coupling. Unfortunately, the present-day commercial controlles cannot provide satisfying performance for its single axis linear control only. Therefore, aimed at a novel 2-DOF (Degree of Freedom parallel manipulator called Diamond 600, a motor-mechanism coupling dynamic model based control scheme employing the computed torque control algorithm are presented in this paper. First, the integrated dynamic coupling model is deduced, according to equivalent torques between the mechanical structure and the PM (Permanent Magnetism servomotor. Second, computed torque controller is described in detail for the above proposed model. At last, a series of numerical simulations and experiments are carried out to test the effectiveness of the system, and the results verify the favourable tracking ability and robustness.

  4. Mechatronic Model Based Computed Torque Control of a Parallel Manipulator

    Directory of Open Access Journals (Sweden)

    Zhiyong Yang

    2008-03-01

    Full Text Available With high speed and accuracy the parallel manipulators have wide application in the industry, but there still exist many difficulties in the actual control process because of the time-varying and coupling. Unfortunately, the present-day commercial controlles cannot provide satisfying performance for its single axis linear control only. Therefore, aimed at a novel 2-DOF (Degree of Freedom parallel manipulator called Diamond 600, a motor-mechanism coupling dynamic model based control scheme employing the computed torque control algorithm are presented in this paper. First, the integrated dynamic coupling model is deduced, according to equivalent torques between the mechanical structure and the PM (Permanent Magnetism servomotor. Second, computed torque controller is described in detail for the above proposed model. At last, a series of numerical simulations and experiments are carried out to test the effectiveness of the system, and the results verify the favourable tracking ability and robustness.

  5. The Abstract Machine Model for Transaction-based System Control

    Energy Technology Data Exchange (ETDEWEB)

    Chassin, David P.

    2003-01-31

    Recent work applying statistical mechanics to economic modeling has demonstrated the effectiveness of using thermodynamic theory to address the complexities of large scale economic systems. Transaction-based control systems depend on the conjecture that when control of thermodynamic systems is based on price-mediated strategies (e.g., auctions, markets), the optimal allocation of resources in a market-based control system results in an emergent optimal control of the thermodynamic system. This paper proposes an abstract machine model as the necessary precursor for demonstrating this conjecture and establishes the dynamic laws as the basis for a special theory of emergence applied to the global behavior and control of complex adaptive systems. The abstract machine in a large system amounts to the analog of a particle in thermodynamic theory. The permit the establishment of a theory dynamic control of complex system behavior based on statistical mechanics. Thus we may be better able to engineer a few simple control laws for a very small number of devices types, which when deployed in very large numbers and operated as a system of many interacting markets yields the stable and optimal control of the thermodynamic system.

  6. Optimal Model-Based Control in HVAC Systems

    DEFF Research Database (Denmark)

    Komareji, Mohammad; Stoustrup, Jakob; Rasmussen, Henrik

    2008-01-01

    is developed. Then the optimal control structure is designed and implemented. The HVAC system is splitted into two subsystems. By selecting the right set-points and appropriate cost functions for each subsystem controller the optimal control strategy is respected to gaurantee the minimum thermal and electrical......This paper presents optimal model-based control of a heating, ventilating, and air-conditioning (HVAC) system. This HVAC system is made of two heat exchangers: an air-to-air heat exchanger (a rotary wheel heat recovery) and a water-to- air heat exchanger. First dynamic model of the HVAC system...... energy consumption. Finally, the controller is applied to control the mentioned HVAC system and the results show that the expected goals are fulfilled....

  7. Individual-based modelling and control of bovine brucellosis

    Science.gov (United States)

    Nepomuceno, Erivelton G.; Barbosa, Alípio M.; Silva, Marcos X.; Perc, Matjaž

    2018-05-01

    We present a theoretical approach to control bovine brucellosis. We have used individual-based modelling, which is a network-type alternative to compartmental models. Our model thus considers heterogeneous populations, and spatial aspects such as migration among herds and control actions described as pulse interventions are also easily implemented. We show that individual-based modelling reproduces the mean field behaviour of an equivalent compartmental model. Details of this process, as well as flowcharts, are provided to facilitate the reproduction of the presented results. We further investigate three numerical examples using real parameters of herds in the São Paulo state of Brazil, in scenarios which explore eradication, continuous and pulsed vaccination and meta-population effects. The obtained results are in good agreement with the expected behaviour of this disease, which ultimately showcases the effectiveness of our theory.

  8. Distributed model based control of multi unit evaporation systems

    International Nuclear Information System (INIS)

    Yudi Samyudia

    2006-01-01

    In this paper, we present a new approach to the analysis and design of distributed control systems for multi-unit plants. The approach is established after treating the effect of recycled dynamics as a gap metric uncertainty from which a distributed controller can be designed sequentially for each unit to tackle the uncertainty. We then use a single effect multi-unit evaporation system to illustrate how the proposed method is used to analyze different control strategies and to systematically achieve a better closed-loop performance using a distributed model-based controller

  9. Application of model based control to robotic manipulators

    Science.gov (United States)

    Petrosky, Lyman J.; Oppenheim, Irving J.

    1988-01-01

    A robot that can duplicate humam motion capabilities in such activities as balancing, reaching, lifting, and moving has been built and tested. These capabilities are achieved through the use of real time Model-Based Control (MBC) techniques which have recently been demonstrated. MBC accounts for all manipulator inertial forces and provides stable manipulator motion control even at high speeds. To effectively demonstrate the unique capabilities of MBC, an experimental robotic manipulator was constructed, which stands upright, balancing on a two wheel base. The mathematical modeling of dynamics inherent in MBC permit the control system to perform functions that are impossible with conventional non-model based methods. These capabilities include: (1) Stable control at all speeds of operation; (2) Operations requiring dynamic stability such as balancing; (3) Detection and monitoring of applied forces without the use of load sensors; (4) Manipulator safing via detection of abnormal loads. The full potential of MBC has yet to be realized. The experiments performed for this research are only an indication of the potential applications. MBC has no inherent stability limitations and its range of applicability is limited only by the attainable sampling rate, modeling accuracy, and sensor resolution. Manipulators could be designed to operate at the highest speed mechanically attainable without being limited by control inadequacies. Manipulators capable of operating many times faster than current machines would certainly increase productivity for many tasks.

  10. Evaluation-Function-based Model-free Adaptive Fuzzy Control

    Directory of Open Access Journals (Sweden)

    Agus Naba

    2016-12-01

    Full Text Available Designs of adaptive fuzzy controllers (AFC are commonly based on the Lyapunov approach, which requires a known model of the controlled plant. They need to consider a Lyapunov function candidate as an evaluation function to be minimized. In this study these drawbacks were handled by designing a model-free adaptive fuzzy controller (MFAFC using an approximate evaluation function defined in terms of the current state, the next state, and the control action. MFAFC considers the approximate evaluation function as an evaluative control performance measure similar to the state-action value function in reinforcement learning. The simulation results of applying MFAFC to the inverted pendulum benchmark verified the proposed scheme’s efficacy.

  11. Moment based model predictive control for systems with additive uncertainty

    NARCIS (Netherlands)

    Saltik, M.B.; Ozkan, L.; Weiland, S.; Ludlage, J.H.A.

    2017-01-01

    In this paper, we present a model predictive control (MPC) strategy based on the moments of the state variables and the cost functional. The statistical properties of the state predictions are calculated through the open loop iteration of dynamics and used in the formulation of MPC cost function. We

  12. A generic model for camera based intelligent road crowd control ...

    African Journals Online (AJOL)

    This research proposes a model for intelligent traffic flow control by implementing camera based surveillance and feedback system. A series of cameras are set minimum three signals ahead from the target junction. The complete software system is developed to help integrating the multiple camera on road as feedback to ...

  13. Port-based Modeling and Control of Underactuated Aerial Vehicles

    NARCIS (Netherlands)

    Mersha, A.Y.; Carloni, Raffaella; Stramigioli, Stefano

    2011-01-01

    In this paper, we propose a generic model and a controller design for a class of underactuated aerial vehicles, namely for unmanned aerial vehicles whose primary support against gravity is thrust. The approach followed is based on energetic consideration and uses the formalisms of port-Hamiltonian

  14. Model based active power control of a wind turbine

    DEFF Research Database (Denmark)

    Mirzaei, Mahmood; Soltani, Mohsen; Poulsen, Niels Kjølstad

    2014-01-01

    in the electricity market that selling the reserve power is more profitable than producing with the full capacity. Therefore wind turbines can be down-regulated and sell the differential capacity as the reserve power. In this paper we suggest a model based approach to control wind turbines for active power reference...

  15. Embedded Control System Design A Model Based Approach

    CERN Document Server

    Forrai, Alexandru

    2013-01-01

    Control system design is a challenging task for practicing engineers. It requires knowledge of different engineering fields, a good understanding of technical specifications and good communication skills. The current book introduces the reader into practical control system design, bridging  the gap between theory and practice.  The control design techniques presented in the book are all model based., considering the needs and possibilities of practicing engineers. Classical control design techniques are reviewed and methods are presented how to verify the robustness of the design. It is how the designed control algorithm can be implemented in real-time and tested, fulfilling different safety requirements. Good design practices and the systematic software development process are emphasized in the book according to the generic standard IEC61508. The book is mainly addressed to practicing control and embedded software engineers - working in research and development – as well as graduate students who are face...

  16. TP-model transformation-based-control design frameworks

    CERN Document Server

    Baranyi, Péter

    2016-01-01

    This book covers new aspects and frameworks of control, design, and optimization based on the TP model transformation and its various extensions. The author outlines the three main steps of polytopic and LMI based control design: 1) development of the qLPV state-space model, 2) generation of the polytopic model; and 3) application of LMI to derive controller and observer. He goes on to describe why literature has extensively studied LMI design, but has not focused much on the second step, in part because the generation and manipulation of the polytopic form was not tractable in many cases. The author then shows how the TP model transformation facilitates this second step and hence reveals new directions, leading to powerful design procedures and the formulation of new questions. The chapters of this book, and the complex dynamical control tasks which they cover, are organized so as to present and analyze the beneficial aspect of the family of approaches (control, design, and optimization). Additionally, the b...

  17. Model predictive control based on reduced order models applied to belt conveyor system.

    Science.gov (United States)

    Chen, Wei; Li, Xin

    2016-11-01

    In the paper, a model predictive controller based on reduced order model is proposed to control belt conveyor system, which is an electro-mechanics complex system with long visco-elastic body. Firstly, in order to design low-degree controller, the balanced truncation method is used for belt conveyor model reduction. Secondly, MPC algorithm based on reduced order model for belt conveyor system is presented. Because of the error bound between the full-order model and reduced order model, two Kalman state estimators are applied in the control scheme to achieve better system performance. Finally, the simulation experiments are shown that balanced truncation method can significantly reduce the model order with high-accuracy and model predictive control based on reduced-model performs well in controlling the belt conveyor system. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

  18. Model-predictive control based on Takagi-Sugeno fuzzy model for electrical vehicles delayed model

    DEFF Research Database (Denmark)

    Khooban, Mohammad-Hassan; Vafamand, Navid; Niknam, Taher

    2017-01-01

    Electric vehicles (EVs) play a significant role in different applications, such as commuter vehicles and short distance transport applications. This study presents a new structure of model-predictive control based on the Takagi-Sugeno fuzzy model, linear matrix inequalities, and a non......-quadratic Lyapunov function for the speed control of EVs including time-delay states and parameter uncertainty. Experimental data, using the Federal Test Procedure (FTP-75), is applied to test the performance and robustness of the suggested controller in the presence of time-varying parameters. Besides, a comparison...... is made between the results of the suggested robust strategy and those obtained from some of the most recent studies on the same topic, to assess the efficiency of the suggested controller. Finally, the experimental results based on a TMS320F28335 DSP are performed on a direct current motor. Simulation...

  19. Neural network-based model reference adaptive control system.

    Science.gov (United States)

    Patino, H D; Liu, D

    2000-01-01

    In this paper, an approach to model reference adaptive control based on neural networks is proposed and analyzed for a class of first-order continuous-time nonlinear dynamical systems. The controller structure can employ either a radial basis function network or a feedforward neural network to compensate adaptively the nonlinearities in the plant. A stable controller-parameter adjustment mechanism, which is determined using the Lyapunov theory, is constructed using a sigma-modification-type updating law. The evaluation of control error in terms of the neural network learning error is performed. That is, the control error converges asymptotically to a neighborhood of zero, whose size is evaluated and depends on the approximation error of the neural network. In the design and analysis of neural network-based control systems, it is important to take into account the neural network learning error and its influence on the control error of the plant. Simulation results showing the feasibility and performance of the proposed approach are given.

  20. Control volume based modelling of compressible flow in reciprocating machines

    DEFF Research Database (Denmark)

    Andersen, Stig Kildegård; Thomsen, Per Grove; Carlsen, Henrik

    2004-01-01

    , and multidimensional effects must be calculated using empirical correlations; correlations for steady state flow can be used as an approximation. A transformation that assumes ideal gas is presented for transforming equations for masses and energies in control volumes into the corresponding pressures and temperatures......An approach to modelling unsteady compressible flow that is primarily one dimensional is presented. The approach was developed for creating distributed models of machines with reciprocating pistons but it is not limited to this application. The approach is based on the integral form of the unsteady...... conservation laws for mass, energy, and momentum applied to a staggered mesh consisting of two overlapping strings of control volumes. Loss mechanisms can be included directly in the governing equations of models by including them as terms in the conservation laws. Heat transfer, flow friction...

  1. Developments in model-based optimization and control distributed control and industrial applications

    CERN Document Server

    Grancharova, Alexandra; Pereira, Fernando

    2015-01-01

    This book deals with optimization methods as tools for decision making and control in the presence of model uncertainty. It is oriented to the use of these tools in engineering, specifically in automatic control design with all its components: analysis of dynamical systems, identification problems, and feedback control design. Developments in Model-Based Optimization and Control takes advantage of optimization-based formulations for such classical feedback design objectives as stability, performance and feasibility, afforded by the established body of results and methodologies constituting optimal control theory. It makes particular use of the popular formulation known as predictive control or receding-horizon optimization. The individual contributions in this volume are wide-ranging in subject matter but coordinated within a five-part structure covering material on: · complexity and structure in model predictive control (MPC); · collaborative MPC; · distributed MPC; · optimization-based analysis and desi...

  2. Model-based reasoning and the control of process plants

    International Nuclear Information System (INIS)

    Vaelisuo, Heikki

    1993-02-01

    In addition to feedback control, safe and economic operation of industrial process plants requires discrete-event type logic control like for example automatic control sequences, interlocks, etc. A lot of complex routine reasoning is involved in the design and verification and validation (VandV) of such automatics. Similar reasoning tasks are encountered during plant operation in action planning and fault diagnosis. The low-level part of the required problem solving is so straightforward that it could be accomplished by a computer if only there were plant models which allow versatile mechanised reasoning. Such plant models and corresponding inference algorithms are the main subject of this report. Deep knowledge and qualitative modelling play an essential role in this work. Deep knowledge refers to mechanised reasoning based on the first principles of the phenomena in the problem domain. Qualitative modelling refers to knowledge representation formalism and related reasoning methods which allow solving problems on an abstraction level higher than for example traditional simulation and optimisation. Prolog is a commonly used platform for artificial intelligence (Al) applications. Constraint logic languages like CLP(R) and Prolog-III extend the scope of logic programming to numeric problem solving. In addition they allow a programming style which often reduces the computational complexity significantly. An approach to model-based reasoning implemented in constraint logic programming language CLP(R) is presented. The approach is based on some of the principles of QSIM, an algorithm for qualitative simulation. It is discussed how model-based reasoning can be applied in the design and VandV of plant automatics and in action planning during plant operation. A prototype tool called ISIR is discussed and some initial results obtained during the development of the tool are presented. The results presented originate from preliminary test results of the prototype obtained

  3. Construction project investment control model based on instant information

    Institute of Scientific and Technical Information of China (English)

    WANG Xue-tong

    2006-01-01

    Change of construction conditions always influences project investment by causing the loss of construction work time and extending the duration. To resolve such problem as difficult dynamic control in work construction plan, this article presents a concept of instant optimization by ways of adjustment operation time of each working procedure to minimize investment change. Based on this concept, its mathematical model is established and a strict mathematical justification is performed. An instant optimization model takes advantage of instant information in the construction process to duly complete adjustment of construction; thus we maximize cost efficiency of project investment.

  4. Efficient speed control of induction motor using RBF based model reference adaptive control method

    OpenAIRE

    Kilic, Erdal; Ozcalik, Hasan Riza; Yilmaz, Saban

    2017-01-01

    This paper proposes a model reference adaptive speed controller based on artificial neural network for induction motor drives. The performance of traditional feedback controllers has been insufficient in speed control of induction motors due to nonlinear structure of the system, changing environmental conditions, and disturbance input effects. A successful speed control of induction motor requires a nonlinear control system. On the other hand, in recent years, it has been demonstrated that ar...

  5. Nuclear reactor power control system based on flexibility model

    International Nuclear Information System (INIS)

    Li Gang; Zhao Fuyu; Li Chong; Tai Yun

    2011-01-01

    Design the nuclear reactor power control system in this paper to cater to a nonlinear nuclear reactor. First, calculate linear power models at five power levels of the reactor as five local models and design controllers of the local models as local controllers. Every local controller consists of an optimal controller contrived by the toolbox of Optimal Controller Designer (OCD) and a proportion-integration-differentiation (PID) controller devised via Genetic Algorithm (GA) to set parameters of the PID controller. According to the local models and controllers, apply the principle of flexibility model developed in the paper to obtain the flexibility model and the flexibility controller at every power level. Second, the flexibility model and the flexibility controller at a level structure the power control system of this level. The set of the whole power control systems corresponding to global power levels is to approximately carry out the power control of the reactor. Finally, the nuclear reactor power control system is simulated. The simulation result shows that the idea of flexibility model is feasible and the nuclear reactor power control system is effective. (author)

  6. Semi-active control of magnetorheological elastomer base isolation system utilising learning-based inverse model

    Science.gov (United States)

    Gu, Xiaoyu; Yu, Yang; Li, Jianchun; Li, Yancheng

    2017-10-01

    Magnetorheological elastomer (MRE) base isolations have attracted considerable attention over the last two decades thanks to its self-adaptability and high-authority controllability in semi-active control realm. Due to the inherent nonlinearity and hysteresis of the devices, it is challenging to obtain a reasonably complicated mathematical model to describe the inverse dynamics of MRE base isolators and hence to realise control synthesis of the MRE base isolation system. Two aims have been achieved in this paper: i) development of an inverse model for MRE base isolator based on optimal general regression neural network (GRNN); ii) numerical and experimental validation of a real-time semi-active controlled MRE base isolation system utilising LQR controller and GRNN inverse model. The superiority of GRNN inverse model lays in fewer input variables requirement, faster training process and prompt calculation response, which makes it suitable for online training and real-time control. The control system is integrated with a three-storey shear building model and control performance of the MRE base isolation system is compared with bare building, passive-on isolation system and passive-off isolation system. Testing results show that the proposed GRNN inverse model is able to reproduce desired control force accurately and the MRE base isolation system can effectively suppress the structural responses when compared to the passive isolation system.

  7. Model Based Control of Moisture Sorption in a Historical Interior

    Directory of Open Access Journals (Sweden)

    P. Zítek

    2005-01-01

    Full Text Available This paper deals with a novel scheme for microclimate control in historical exhibition rooms, inhibiting moisture sorption phenomena that are inadmissible from the preventive conservation point of view. The impact of air humidity is the most significant harmful exposure for a great deal of the cultural heritage deposited in remote historical buildings. Leaving the interior temperature to run almost its spontaneous yearly cycle, the proposed non-linear model-based control protects exhibits from harmful variations in moisture content by compensating the temperature drifts with an adequate adjustment of the air humidity. Already implemented in a medieval interior since 1999, the proposed microclimate control has proved capable of permanently maintaining constant a desirable moisture content in organic or porous materials in the interior of a building. 

  8. Enhanced Voltage Control of VSC-HVDC Connected Offshore Wind Farms Based on Model Predictive Control

    DEFF Research Database (Denmark)

    Guo, Yifei; Gao, Houlei; Wu, Qiuwei

    2018-01-01

    This paper proposes an enhanced voltage control strategy (EVCS) based on model predictive control (MPC) for voltage source converter based high voltage direct current (VSCHVDC) connected offshore wind farms (OWFs). In the proposed MPC based EVCS, all wind turbine generators (WTGs) as well...... as the wind farm side VSC are optimally coordinated to keep voltages within the feasible range and reduce system power losses. Considering the high ratio of the OWF collector system, the effects of active power outputs of WTGs on voltage control are also taken into consideration. The predictive model of VSC...

  9. Tuning SISO offset-free Model Predictive Control based on ARX models

    DEFF Research Database (Denmark)

    Huusom, Jakob Kjøbsted; Poulsen, Niels Kjølstad; Jørgensen, Sten Bay

    2012-01-01

    , the proposed controller is simple to tune as it has only one free tuning parameter. These two features are advantageous in predictive process control as they simplify industrial commissioning of MPC. Disturbance rejection and offset-free control is important in industrial process control. To achieve offset......In this paper, we present a tuning methodology for a simple offset-free SISO Model Predictive Controller (MPC) based on autoregressive models with exogenous inputs (ARX models). ARX models simplify system identification as they can be identified from data using convex optimization. Furthermore......-free control in face of unknown disturbances or model-plant mismatch, integrators must be introduced in either the estimator or the regulator. Traditionally, offset-free control is achieved using Brownian disturbance models in the estimator. In this paper we achieve offset-free control by extending the noise...

  10. Tensor Product Model Transformation Based Adaptive Integral-Sliding Mode Controller: Equivalent Control Method

    Directory of Open Access Journals (Sweden)

    Guoliang Zhao

    2013-01-01

    Full Text Available This paper proposes new methodologies for the design of adaptive integral-sliding mode control. A tensor product model transformation based adaptive integral-sliding mode control law with respect to uncertainties and perturbations is studied, while upper bounds on the perturbations and uncertainties are assumed to be unknown. The advantage of proposed controllers consists in having a dynamical adaptive control gain to establish a sliding mode right at the beginning of the process. Gain dynamics ensure a reasonable adaptive gain with respect to the uncertainties. Finally, efficacy of the proposed controller is verified by simulations on an uncertain nonlinear system model.

  11. Model based control of grate combustion; Modellbaserad roststyrning

    Energy Technology Data Exchange (ETDEWEB)

    Broden, Henrik; Kjellstroem, Bjoern; Niklasson, Fredrik; Boecher Poulsen, Kristian

    2006-12-15

    An existing dynamic model for grate combustion has been further developed. The model has been used for studies of possible advantages that can be gained from utilisation of measurements of grate temperatures and fuel bed height for control of a boiler after disturbances caused by varying fuel moisture and fuel feeding. The objective was to asses the possibilities to develop a control system that would adjust for such disturbances quicker than measurements of steam output and oxygen in the exhaust. The model is based on dividing the fuel bed into three layers, where the different layers include fuel being dried, fuel being pyrolysed and char reacting with oxygen. The grate below the fuel bed is also considered. A mass balance, an energy balance and a volume balance is considered for each layer in 22 cells along the grate. The energy balances give the temperature distribution and the volume balances the bed height. The earlier version of the model could not handle layers that are consumed. This weakness has now been eliminated. Comparisons between predicted grate temperatures and measurements in a 25 MW boiler fuelled with biofuel have been used for validation of the model. The comparisons include effects of variations in primary air temperature, fuel moisture and output power. The model shows good agreement with observations for changes in the air temperature but the ability of the model to predict effects of changed fuel moisture is difficult to judge since the steam dome pressure control caused simultaneous changes of the primary air flow, which probably had a larger influence on the grate temperature. A linearised, tuned and reduced version of the model was used for design of a linear quadratic controller. This was used for studies of advantages of using measurements of grate temperatures and bed height for control of pusher velocity, grate speed, primary air flow and air temperature after disturbances of fuel moisture and fuel flow. Measurements of the grate

  12. Fuzzy model-based servo and model following control for nonlinear systems.

    Science.gov (United States)

    Ohtake, Hiroshi; Tanaka, Kazuo; Wang, Hua O

    2009-12-01

    This correspondence presents servo and nonlinear model following controls for a class of nonlinear systems using the Takagi-Sugeno fuzzy model-based control approach. First, the construction method of the augmented fuzzy system for continuous-time nonlinear systems is proposed by differentiating the original nonlinear system. Second, the dynamic fuzzy servo controller and the dynamic fuzzy model following controller, which can make outputs of the nonlinear system converge to target points and to outputs of the reference system, respectively, are introduced. Finally, the servo and model following controller design conditions are given in terms of linear matrix inequalities. Design examples illustrate the utility of this approach.

  13. Demand Management Based on Model Predictive Control Techniques

    Directory of Open Access Journals (Sweden)

    Yasser A. Davizón

    2014-01-01

    Full Text Available Demand management (DM is the process that helps companies to sell the right product to the right customer, at the right time, and for the right price. Therefore the challenge for any company is to determine how much to sell, at what price, and to which market segment while maximizing its profits. DM also helps managers efficiently allocate undifferentiated units of capacity to the available demand with the goal of maximizing revenue. This paper introduces control system approach to demand management with dynamic pricing (DP using the model predictive control (MPC technique. In addition, we present a proper dynamical system analogy based on active suspension and a stability analysis is provided via the Lyapunov direct method.

  14. Attributes Enhanced Role-Based Access Control Model

    DEFF Research Database (Denmark)

    Mahmood Rajpoot, Qasim; Jensen, Christian D.; Krishnan, Ram

    2015-01-01

    as an important area of research. In this paper, we propose an access control model that combines the two models in a novel way in order to unify their benefits. Our approach provides a fine-grained access control mechanism that not only takes contextual information into account while making the access control...... decisions but is also suitable for applications where access to resources is controlled by exploiting contents of the resources in the policy....

  15. Algorithms and procedures in the model based control of accelerators

    International Nuclear Information System (INIS)

    Bozoki, E.

    1987-10-01

    The overall design of a Model Based Control system was presented. The system consists of PLUG-IN MODULES, governed by a SUPERVISORY PROGRAM and communicating via SHARED DATA FILES. Models can be ladded or replaced without affecting the oveall system. There can be more then one module (algorithm) to perform the same task. The user can choose the most appropriate algorithm or can compare the results using different algorithms. Calculations, algorithms, file read and write, etc. which are used in more than one module, will be in a subroutine library. This feature will simplify the maintenance of the system. A partial list of modules is presented, specifying the task they perform. 19 refs., 1 fig

  16. Output-Feedback Model Predictive Control of a Pasteurization Pilot Plant based on an LPV model

    Science.gov (United States)

    Karimi Pour, Fatemeh; Ocampo-Martinez, Carlos; Puig, Vicenç

    2017-01-01

    This paper presents a model predictive control (MPC) of a pasteurization pilot plant based on an LPV model. Since not all the states are measured, an observer is also designed, which allows implementing an output-feedback MPC scheme. However, the model of the plant is not completely observable when augmented with the disturbance models. In order to solve this problem, the following strategies are used: (i) the whole system is decoupled into two subsystems, (ii) an inner state-feedback controller is implemented into the MPC control scheme. A real-time example based on the pasteurization pilot plant is simulated as a case study for testing the behavior of the approaches.

  17. Composite control for raymond mill based on model predictive control and disturbance observer

    Directory of Open Access Journals (Sweden)

    Dan Niu

    2016-03-01

    Full Text Available In the raymond mill grinding process, precise control of operating load is vital for the high product quality. However, strong external disturbances, such as variations of ore size and ore hardness, usually cause great performance degradation. It is not easy to control the current of raymond mill constant. Several control strategies have been proposed. However, most of them (such as proportional–integral–derivative and model predictive control reject disturbances just through feedback regulation, which may lead to poor control performance in the presence of strong disturbances. For improving disturbance rejection, a control method based on model predictive control and disturbance observer is put forward in this article. The scheme employs disturbance observer as feedforward compensation and model predictive control controller as feedback regulation. The test results illustrate that compared with model predictive control method, the proposed disturbance observer–model predictive control method can obtain significant superiority in disturbance rejection, such as shorter settling time and smaller peak overshoot under strong disturbances.

  18. Simple Models for Model-based Portfolio Load Balancing Controller Synthesis

    DEFF Research Database (Denmark)

    Edlund, Kristian Skjoldborg; Mølbak, Tommy; Bendtsen, Jan Dimon

    2010-01-01

    of generation units existing in an electrical power supply network, for instance in model-based predictive control or declarative control schemes. We focus on the effectuators found in the Danish power system. In particular, the paper presents models for boiler load, district heating, condensate throttling...

  19. Neural network-based nonlinear model predictive control vs. linear quadratic gaussian control

    Science.gov (United States)

    Cho, C.; Vance, R.; Mardi, N.; Qian, Z.; Prisbrey, K.

    1997-01-01

    One problem with the application of neural networks to the multivariable control of mineral and extractive processes is determining whether and how to use them. The objective of this investigation was to compare neural network control to more conventional strategies and to determine if there are any advantages in using neural network control in terms of set-point tracking, rise time, settling time, disturbance rejection and other criteria. The procedure involved developing neural network controllers using both historical plant data and simulation models. Various control patterns were tried, including both inverse and direct neural network plant models. These were compared to state space controllers that are, by nature, linear. For grinding and leaching circuits, a nonlinear neural network-based model predictive control strategy was superior to a state space-based linear quadratic gaussian controller. The investigation pointed out the importance of incorporating state space into neural networks by making them recurrent, i.e., feeding certain output state variables into input nodes in the neural network. It was concluded that neural network controllers can have better disturbance rejection, set-point tracking, rise time, settling time and lower set-point overshoot, and it was also concluded that neural network controllers can be more reliable and easy to implement in complex, multivariable plants.

  20. A General Attribute and Rule Based Role-Based Access Control Model

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    Growing numbers of users and many access control policies which involve many different resource attributes in service-oriented environments bring various problems in protecting resource. This paper analyzes the relationships of resource attributes to user attributes in all policies, and propose a general attribute and rule based role-based access control(GAR-RBAC) model to meet the security needs. The model can dynamically assign users to roles via rules to meet the need of growing numbers of users. These rules use different attribute expression and permission as a part of authorization constraints, and are defined by analyzing relations of resource attributes to user attributes in many access policies that are defined by the enterprise. The model is a general access control model, and can support many access control policies, and also can be used to wider application for service. The paper also describes how to use the GAR-RBAC model in Web service environments.

  1. A Nonlinear Dynamic Inversion Predictor-Based Model Reference Adaptive Controller for a Generic Transport Model

    Science.gov (United States)

    Campbell, Stefan F.; Kaneshige, John T.

    2010-01-01

    Presented here is a Predictor-Based Model Reference Adaptive Control (PMRAC) architecture for a generic transport aircraft. At its core, this architecture features a three-axis, non-linear, dynamic-inversion controller. Command inputs for this baseline controller are provided by pilot roll-rate, pitch-rate, and sideslip commands. This paper will first thoroughly present the baseline controller followed by a description of the PMRAC adaptive augmentation to this control system. Results are presented via a full-scale, nonlinear simulation of NASA s Generic Transport Model (GTM).

  2. PD/PID controller tuning based on model approximations: Model reduction of some unstable and higher order nonlinear models

    Directory of Open Access Journals (Sweden)

    Christer Dalen

    2017-10-01

    Full Text Available A model reduction technique based on optimization theory is presented, where a possible higher order system/model is approximated with an unstable DIPTD model by using only step response data. The DIPTD model is used to tune PD/PID controllers for the underlying possible higher order system. Numerous examples are used to illustrate the theory, i.e. both linear and nonlinear models. The Pareto Optimal controller is used as a reference controller.

  3. Coordinated Voltage Control of a Wind Farm based on Model Predictive Control

    DEFF Research Database (Denmark)

    Zhao, Haoran; Wu, Qiuwei; Guo, Qinglai

    2016-01-01

    This paper presents an autonomous wind farm voltage controller based on Model Predictive Control (MPC). The reactive power compensation and voltage regulation devices of the wind farm include Static Var Compensators (SVCs), Static Var Generators (SVGs), Wind Turbine Generators (WTGs) and On...... are calculated based on an analytical method to improve the computation efficiency and overcome the convergence problem. Two control modes are designed for both voltage violated and normal operation conditions. A wind farm with 20 wind turbines was used to conduct case studies to verify the proposed coordinated...

  4. Combined Active and Reactive Power Control of Wind Farms based on Model Predictive Control

    DEFF Research Database (Denmark)

    Zhao, Haoran; Wu, Qiuwei; Wang, Jianhui

    2017-01-01

    This paper proposes a combined wind farm controller based on Model Predictive Control (MPC). Compared with the conventional decoupled active and reactive power control, the proposed control scheme considers the significant impact of active power on voltage variations due to the low X=R ratio...... of wind farm collector systems. The voltage control is improved. Besides, by coordination of active and reactive power, the Var capacity is optimized to prevent potential failures due to Var shortage, especially when the wind farm operates close to its full load. An analytical method is used to calculate...... the sensitivity coefficients to improve the computation efficiency and overcome the convergence problem. Two control modes are designed for both normal and emergency conditions. A wind farm with 20 wind turbines was used to verify the proposed combined control scheme....

  5. Model-Based Approaches to Active Perception and Control

    Directory of Open Access Journals (Sweden)

    Giovanni Pezzulo

    2017-06-01

    Full Text Available There is an on-going debate in cognitive (neuro science and philosophy between classical cognitive theory and embodied, embedded, extended, and enactive (“4-Es” views of cognition—a family of theories that emphasize the role of the body in cognition and the importance of brain-body-environment interaction over and above internal representation. This debate touches foundational issues, such as whether the brain internally represents the external environment, and “infers” or “computes” something. Here we focus on two (4-Es-based criticisms to traditional cognitive theories—to the notions of passive perception and of serial information processing—and discuss alternative ways to address them, by appealing to frameworks that use, or do not use, notions of internal modelling and inference. Our analysis illustrates that: an explicitly inferential framework can capture some key aspects of embodied and enactive theories of cognition; some claims of computational and dynamical theories can be reconciled rather than seen as alternative explanations of cognitive phenomena; and some aspects of cognitive processing (e.g., detached cognitive operations, such as planning and imagination that are sometimes puzzling to explain from enactive and non-representational perspectives can, instead, be captured nicely from the perspective that internal generative models and predictive processing mediate adaptive control loops.

  6. An Inverse Optimal Control Approach to Explain Human Arm Reaching Control Based on Multiple Internal Models.

    Science.gov (United States)

    Oguz, Ozgur S; Zhou, Zhehua; Glasauer, Stefan; Wollherr, Dirk

    2018-04-03

    Human motor control is highly efficient in generating accurate and appropriate motor behavior for a multitude of tasks. This paper examines how kinematic and dynamic properties of the musculoskeletal system are controlled to achieve such efficiency. Even though recent studies have shown that the human motor control relies on multiple models, how the central nervous system (CNS) controls this combination is not fully addressed. In this study, we utilize an Inverse Optimal Control (IOC) framework in order to find the combination of those internal models and how this combination changes for different reaching tasks. We conducted an experiment where participants executed a comprehensive set of free-space reaching motions. The results show that there is a trade-off between kinematics and dynamics based controllers depending on the reaching task. In addition, this trade-off depends on the initial and final arm configurations, which in turn affect the musculoskeletal load to be controlled. Given this insight, we further provide a discomfort metric to demonstrate its influence on the contribution of different inverse internal models. This formulation together with our analysis not only support the multiple internal models (MIMs) hypothesis but also suggest a hierarchical framework for the control of human reaching motions by the CNS.

  7. Optimisation of Marine Boilers using Model-based Multivariable Control

    DEFF Research Database (Denmark)

    Solberg, Brian

    Traditionally, marine boilers have been controlled using classical single loop controllers. To optimise marine boiler performance, reduce new installation time and minimise the physical dimensions of these large steel constructions, a more comprehensive and coherent control strategy is needed....... This research deals with the application of advanced control to a specific class of marine boilers combining well-known design methods for multivariable systems. This thesis presents contributions for modelling and control of the one-pass smoke tube marine boilers as well as for hybrid systems control. Much...... of the focus has been directed towards water level control which is complicated by the nature of the disturbances acting on the system as well as by low frequency sensor noise. This focus was motivated by an estimated large potential to minimise the boiler geometry by reducing water level fluctuations...

  8. A comprehensive gaze stabilization controller based on cerebellar internal models

    DEFF Research Database (Denmark)

    Vannucci, Lorenzo; Falotico, Egidio; Tolu, Silvia

    2017-01-01

    . The VOR works in conjunction with the opto-kinetic reflex (OKR), which is a visual feedback mechanism that allows to move the eye at the same speed as the observed scene. Together they keep the image stationary on the retina. In this work we implement on a humanoid robot a model of gaze stabilization...... based on the coordination of VCR and VOR and OKR. The model, inspired by neuroscientific cerebellar theories, is provided with learning and adaptation capabilities based on internal models. We present the results for the gaze stabilization model on three sets of experiments conducted on the SABIAN robot...

  9. Load management: Model-based control of aggregate power for populations of thermostatically controlled loads

    International Nuclear Information System (INIS)

    Perfumo, Cristian; Kofman, Ernesto; Braslavsky, Julio H.; Ward, John K.

    2012-01-01

    Highlights: ► Characterisation of power response of a population of air conditioners. ► Implementation of demand side management on a group of air conditioners. ► Design of a controller for the power output of a group of air conditioners. ► Quantification of comfort impact of demand side management. - Abstract: Large groups of electrical loads can be controlled as a single entity to reduce their aggregate power demand in the electricity network. This approach, known as load management (LM) or demand response, offers an alternative to the traditional paradigm in the electricity market, where matching supply and demand is achieved solely by regulating how much generation is dispatched. Thermostatically controlled loads (TCLs), such as air conditioners (ACs) and fridges, are particularly suitable for LM, which can be implemented using feedback control techniques to regulate their aggregate power. To achieve high performance, such feedback control techniques require an accurate mathematical model of the TCL aggregate dynamics. Although such models have been developed, they appear too complex to be effectively used in control design. In this paper we develop a mathematical model aimed at the design of a model-based feedback control strategy. The proposed model analytically characterises the aggregate power response of a population of ACs to a simultaneous step change in temperature set points. Based on this model, we then derive, and completely parametrise in terms of the ACs ensemble properties, a reduced-order mathematical model to design an internal-model controller that regulates aggregate power by broadcasting temperature set-point offset changes. The proposed controller achieves high LM performance provided the ACs are equipped with high resolution thermostats. With coarser resolution thermostats, which are typical in present commercial and residential ACs, performance deteriorates significantly. This limitation is overcome by subdividing the population

  10. Smooth Adaptive Internal Model Control Based on U Model for Nonlinear Systems with Dynamic Uncertainties

    Directory of Open Access Journals (Sweden)

    Li Zhao

    2016-01-01

    Full Text Available An improved smooth adaptive internal model control based on U model control method is presented to simplify modeling structure and parameter identification for a class of uncertain dynamic systems with unknown model parameters and bounded external disturbances. Differing from traditional adaptive methods, the proposed controller can simplify the identification of time-varying parameters in presence of bounded external disturbances. Combining the small gain theorem and the virtual equivalent system theory, learning rate of smooth adaptive internal model controller has been analyzed and the closed-loop virtual equivalent system based on discrete U model has been constructed as well. The convergence of this virtual equivalent system is proved, which further shows the convergence of the complex closed-loop discrete U model system. Finally, simulation and experimental results on a typical nonlinear dynamic system verified the feasibility of the proposed algorithm. The proposed method is shown to have lighter identification burden and higher control accuracy than the traditional adaptive controller.

  11. Model-based and model-free “plug-and-play” building energy efficient control

    International Nuclear Information System (INIS)

    Baldi, Simone; Michailidis, Iakovos; Ravanis, Christos; Kosmatopoulos, Elias B.

    2015-01-01

    Highlights: • “Plug-and-play” Building Optimization and Control (BOC) driven by building data. • Ability to handle the large-scale and complex nature of the BOC problem. • Adaptation to learn the optimal BOC policy when no building model is available. • Comparisons with rule-based and advanced BOC strategies. • Simulation and real-life experiments in a ten-office building. - Abstract: Considerable research efforts in Building Optimization and Control (BOC) have been directed toward the development of “plug-and-play” BOC systems that can achieve energy efficiency without compromising thermal comfort and without the need of qualified personnel engaged in a tedious and time-consuming manual fine-tuning phase. In this paper, we report on how a recently introduced Parametrized Cognitive Adaptive Optimization – abbreviated as PCAO – can be used toward the design of both model-based and model-free “plug-and-play” BOC systems, with minimum human effort required to accomplish the design. In the model-based case, PCAO assesses the performance of its control strategy via a simulation model of the building dynamics; in the model-free case, PCAO optimizes its control strategy without relying on any model of the building dynamics. Extensive simulation and real-life experiments performed on a 10-office building demonstrate the effectiveness of the PCAO–BOC system in providing significant energy efficiency and improved thermal comfort. The mechanisms embedded within PCAO render it capable of automatically and quickly learning an efficient BOC strategy either in the presence of complex nonlinear simulation models of the building dynamics (model-based) or when no model for the building dynamics is available (model-free). Comparative studies with alternative state-of-the-art BOC systems show the effectiveness of the PCAO–BOC solution

  12. Electric Vehicle Longitudinal Stability Control Based on a New Multimachine Nonlinear Model Predictive Direct Torque Control

    Directory of Open Access Journals (Sweden)

    M’hamed Sekour

    2017-01-01

    Full Text Available In order to improve the driving performance and the stability of electric vehicles (EVs, a new multimachine robust control, which realizes the acceleration slip regulation (ASR and antilock braking system (ABS functions, based on nonlinear model predictive (NMP direct torque control (DTC, is proposed for four permanent magnet synchronous in-wheel motors. The in-wheel motor provides more possibilities of wheel control. One of its advantages is that it has low response time and almost instantaneous torque generation. Moreover, it can be independently controlled, enhancing the limits of vehicular control. For an EV equipped with four in-wheel electric motors, an advanced control may be envisaged. Taking advantage of the fast and accurate torque of in-wheel electric motors which is directly transmitted to the wheels, a new approach for longitudinal control realized by ASR and ABS is presented in this paper. In order to achieve a high-performance torque control for EVs, the NMP-DTC strategy is proposed. It uses the fuzzy logic control technique that determines online the accurate values of the weighting factors and generates the optimal switching states that optimize the EV drives’ decision. The simulation results built in Matlab/Simulink indicate that the EV can achieve high-performance vehicle longitudinal stability control.

  13. Embarked electrical network robust control based on singular perturbation model.

    Science.gov (United States)

    Abdeljalil Belhaj, Lamya; Ait-Ahmed, Mourad; Benkhoris, Mohamed Fouad

    2014-07-01

    This paper deals with an approach of modelling in view of control for embarked networks which can be described as strongly coupled multi-sources, multi-loads systems with nonlinear and badly known characteristics. This model has to be representative of the system behaviour and easy to handle for easy regulators synthesis. As a first step, each alternator is modelled and linearized around an operating point and then it is subdivided into two lower order systems according to the singular perturbation theory. RST regulators are designed for each subsystem and tested by means of a software test-bench which allows predicting network behaviour in both steady and transient states. Finally, the designed controllers are implanted on an experimental benchmark constituted by two alternators supplying loads in order to test the dynamic performances in realistic conditions. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

  14. Model Based Control of Single-Phase Marine Cooling Systems

    DEFF Research Database (Denmark)

    Hansen, Michael

    2014-01-01

    in this work is on the development of a nonlinear robust control design. The design is based on principles from feedback. linearization to compensate for nonlinearities as well as transport delays by including a delay estimate in the feedback law. To deal with the uncertainties that emerged from the feedback...

  15. Design of model based LQG control for integrated building systems

    NARCIS (Netherlands)

    Yahiaoui, A.; Hensen, J.L.M.; Soethout, L.L.; Paassen, van A.H.C.

    2006-01-01

    The automation of the operation of integrated building systems requires using modern control techniques to enhance the quality of the building indoor environments. This paper describes the theatrical base and practical application of an optimal dynamic regulator using modelbased Linear Quadratic

  16. Integrity Based Access Control Model for Multilevel XML Document

    Institute of Scientific and Technical Information of China (English)

    HONG Fan; FENG Xue-bin; HUANO Zhi; ZHENG Ming-hui

    2008-01-01

    XML's increasing popularity highlights the security demand for XML documents. A mandatory access control model for XML document is presented on the basis of investigation of the function dependency of XML documents and discussion of the integrity properties of multilevel XML document. Then, the algorithms for decomposition/recovery multilevel XML document into/from single level document are given, and the manipulation rules for typical operations of XQuery and XUpdate: QUERY, INSERT,UPDATE, and REMOVE, are elaborated. The multilevel XML document access model can meet the requirement of sensitive information processing application.

  17. Dynamic Modeling, Model-Based Control, and Optimization of Solid Oxide Fuel Cells

    Science.gov (United States)

    Spivey, Benjamin James

    2011-07-01

    Solid oxide fuel cells are a promising option for distributed stationary power generation that offers efficiencies ranging from 50% in stand-alone applications to greater than 80% in cogeneration. To advance SOFC technology for widespread market penetration, the SOFC should demonstrate improved cell lifetime and load-following capability. This work seeks to improve lifetime through dynamic analysis of critical lifetime variables and advanced control algorithms that permit load-following while remaining in a safe operating zone based on stress analysis. Control algorithms typically have addressed SOFC lifetime operability objectives using unconstrained, single-input-single-output control algorithms that minimize thermal transients. Existing SOFC controls research has not considered maximum radial thermal gradients or limits on absolute temperatures in the SOFC. In particular, as stress analysis demonstrates, the minimum cell temperature is the primary thermal stress driver in tubular SOFCs. This dissertation presents a dynamic, quasi-two-dimensional model for a high-temperature tubular SOFC combined with ejector and prereformer models. The model captures dynamics of critical thermal stress drivers and is used as the physical plant for closed-loop control simulations. A constrained, MIMO model predictive control algorithm is developed and applied to control the SOFC. Closed-loop control simulation results demonstrate effective load-following, constraint satisfaction for critical lifetime variables, and disturbance rejection. Nonlinear programming is applied to find the optimal SOFC size and steady-state operating conditions to minimize total system costs.

  18. Stability Analysis for Car Following Model Based on Control Theory

    International Nuclear Information System (INIS)

    Meng Xiang-Pei; Li Zhi-Peng; Ge Hong-Xia

    2014-01-01

    Stability analysis is one of the key issues in car-following theory. The stability analysis with Lyapunov function for the two velocity difference car-following model (for short, TVDM) is conducted and the control method to suppress traffic congestion is introduced. Numerical simulations are given and results are consistent with the theoretical analysis. (electromagnetism, optics, acoustics, heat transfer, classical mechanics, and fluid dynamics)

  19. Characteristic Model-Based Robust Model Predictive Control for Hypersonic Vehicles with Constraints

    Directory of Open Access Journals (Sweden)

    Jun Zhang

    2017-06-01

    Full Text Available Designing robust control for hypersonic vehicles in reentry is difficult, due to the features of the vehicles including strong coupling, non-linearity, and multiple constraints. This paper proposed a characteristic model-based robust model predictive control (MPC for hypersonic vehicles with reentry constraints. First, the hypersonic vehicle is modeled by a characteristic model composed of a linear time-varying system and a lumped disturbance. Then, the identification data are regenerated by the accumulative sum idea in the gray theory, which weakens effects of the random noises and strengthens regularity of the identification data. Based on the regenerated data, the time-varying parameters and the disturbance are online estimated according to the gray identification. At last, the mixed H2/H∞ robust predictive control law is proposed based on linear matrix inequalities (LMIs and receding horizon optimization techniques. Using active tackling system constraints of MPC, the input and state constraints are satisfied in the closed-loop control system. The validity of the proposed control is verified theoretically according to Lyapunov theory and illustrated by simulation results.

  20. Profile control simulations and experiments on TCV: a controller test environment and results using a model-based predictive controller

    Science.gov (United States)

    Maljaars, E.; Felici, F.; Blanken, T. C.; Galperti, C.; Sauter, O.; de Baar, M. R.; Carpanese, F.; Goodman, T. P.; Kim, D.; Kim, S. H.; Kong, M.; Mavkov, B.; Merle, A.; Moret, J. M.; Nouailletas, R.; Scheffer, M.; Teplukhina, A. A.; Vu, N. M. T.; The EUROfusion MST1-team; The TCV-team

    2017-12-01

    The successful performance of a model predictive profile controller is demonstrated in simulations and experiments on the TCV tokamak, employing a profile controller test environment. Stable high-performance tokamak operation in hybrid and advanced plasma scenarios requires control over the safety factor profile (q-profile) and kinetic plasma parameters such as the plasma beta. This demands to establish reliable profile control routines in presently operational tokamaks. We present a model predictive profile controller that controls the q-profile and plasma beta using power requests to two clusters of gyrotrons and the plasma current request. The performance of the controller is analyzed in both simulation and TCV L-mode discharges where successful tracking of the estimated inverse q-profile as well as plasma beta is demonstrated under uncertain plasma conditions and the presence of disturbances. The controller exploits the knowledge of the time-varying actuator limits in the actuator input calculation itself such that fast transitions between targets are achieved without overshoot. A software environment is employed to prepare and test this and three other profile controllers in parallel in simulations and experiments on TCV. This set of tools includes the rapid plasma transport simulator RAPTOR and various algorithms to reconstruct the plasma equilibrium and plasma profiles by merging the available measurements with model-based predictions. In this work the estimated q-profile is merely based on RAPTOR model predictions due to the absence of internal current density measurements in TCV. These results encourage to further exploit model predictive profile control in experiments on TCV and other (future) tokamaks.

  1. Experience with model based display for advanced diagnostics and control

    International Nuclear Information System (INIS)

    Staffon, J.D.; Lindsay, R.W.

    1989-01-01

    A full color, model based display system based on the Rankine thermodynamic cycle has been developed for use at the Experimental Breeder Reactor II by plant operators, engineers, and experimenters. The displays generate a real time thermodynamic model of the plant processes on computer screens to provide a direct indication of the plant performance. Operators and others who view the displays are no longer required to mentally ''construct'' a model of the process before acting. The model based display accurately depicts the plant states. It appears to effectively reduce the gulf of evaluation, which should result in a significant reduction in human operator errors if this plant display approach is adopted by the nuclear industry. Preliminary comments from users, including operators, indicate an overwhelming acceptance of the display approach. The displays incorporate alarm functions as well as levels of detail ''paging'' capability. The system is developed on a computer network which allows the easy addition of displays as well as extra computers. Constructing a complete console can be rapid and inexpensive. 1 ref., 2 figs

  2. Model-based analysis of context-specific cognitive control

    Directory of Open Access Journals (Sweden)

    Joseph A. King

    2012-09-01

    Full Text Available Interference resolution is improved for stimuli presented in contexts (e.g. locations associated with frequent conflict. This phenomenon, the context-specific proportion congruent (CSPC effect, has challenged the traditional juxtaposition of automatic and controlled processing because it suggests that contextual cues can prime top-down control settings in a bottom-up manner. We recently obtained support for this priming of control hypothesis with fMRI by showing that CSPC effects are mediated by contextually-cued adjustments in processing selectivity. However, an equally plausible explanation is that CSPC effects reflect adjustments in response caution triggered by expectancy violations (i.e. prediction errors when encountering rare events as compared to common ones (e.g. high-conflict incongruent trials in a task context associated with infrequent conflict. Here, we applied a quantitative model of choice, the linear ballistic accumulator (LBA, to distil the reaction time and accuracy data from four independent samples that performed a modified flanker task into latent variables representing the psychological processes underlying task-related decision making. We contrasted models which differentially accounted for CSPC effects as arising either from contextually-cued shifts in the rate of sensory evidence accumulation (drift models or in the amount of evidence required to reach a decision (threshold models. For the majority of the participants, the LBA ascribed CSPC effects to increases in response threshold for contextually-infrequent trial types (e.g. low-conflict congruent trials in the frequent conflict context, suggesting that the phenomenon may reflect more a prediction error-triggered shift in decision criterion rather than enhanced sensory evidence accumulation under conditions of frequent conflict.

  3. Modeling of driver's collision avoidance maneuver based on controller switching model.

    Science.gov (United States)

    Kim, Jong-Hae; Hayakawa, Soichiro; Suzuki, Tatsuya; Hayashi, Koji; Okuma, Shigeru; Tsuchida, Nuio; Shimizu, Masayuki; Kido, Shigeyuki

    2005-12-01

    This paper presents a modeling strategy of human driving behavior based on the controller switching model focusing on the driver's collision avoidance maneuver. The driving data are collected by using the three-dimensional (3-D) driving simulator based on the CAVE Automatic Virtual Environment (CAVE), which provides stereoscopic immersive virtual environment. In our modeling, the control scenario of the human driver, that is, the mapping from the driver's sensory information to the operation of the driver such as acceleration, braking, and steering, is expressed by Piecewise Polynomial (PWP) model. Since the PWP model includes both continuous behaviors given by polynomials and discrete logical conditions, it can be regarded as a class of Hybrid Dynamical System (HDS). The identification problem for the PWP model is formulated as the Mixed Integer Linear Programming (MILP) by transforming the switching conditions into binary variables. From the obtained results, it is found that the driver appropriately switches the "control law" according to the sensory information. In addition, the driving characteristics of the beginner driver and the expert driver are compared and discussed. These results enable us to capture not only the physical meaning of the driving skill but the decision-making aspect (switching conditions) in the driver's collision avoidance maneuver as well.

  4. Efficient predictive model-based and fuzzy control for green urban mobility

    NARCIS (Netherlands)

    Jamshidnejad, A.

    2017-01-01

    In this thesis, we develop efficient predictive model-based control approaches, including model-predictive control (MPC) andmodel-based fuzzy control, for application in urban traffic networks with the aim of reducing a combination of the total time spent by the vehicles within the network and the

  5. Comparison of model reference and map based control method for vehicle stability enhancement

    NARCIS (Netherlands)

    Baek, S.; Son, M.; Song, J.; Boo, K.; Kim, H.

    2012-01-01

    A map based controller method to improve a vehicle lateral stability is proposed in this study and compared with the conventional method, a model referenced controller. A model referenced controller to determine compensated yaw moment uses the sliding mode method, but the proposed map based

  6. Progress and improvement of KSTAR plasma control using model-based control simulators

    Energy Technology Data Exchange (ETDEWEB)

    Hahn, Sang-hee, E-mail: hahn76@nfri.re.kr [National Fusion Research Institute, 169-148 Gwahak-ro, yuseong-gu, Daejeon (Korea, Republic of); Welander, A.S. [General Atomics, San Diego, CA (United States); Yoon, S.W.; Bak, J.G. [National Fusion Research Institute, 169-148 Gwahak-ro, yuseong-gu, Daejeon (Korea, Republic of); Eidietis, N.W. [General Atomics, San Diego, CA (United States); Han, H.S. [National Fusion Research Institute, 169-148 Gwahak-ro, yuseong-gu, Daejeon (Korea, Republic of); Humphreys, D.A.; Hyatt, A. [General Atomics, San Diego, CA (United States); Jeon, Y.M. [National Fusion Research Institute, 169-148 Gwahak-ro, yuseong-gu, Daejeon (Korea, Republic of); Johnson, R.D. [General Atomics, San Diego, CA (United States); Kim, H.S.; Kim, J. [National Fusion Research Institute, 169-148 Gwahak-ro, yuseong-gu, Daejeon (Korea, Republic of); Kolemen, E.; Mueller, D. [Princeton Plasma Physics Laboratory, Princeton, NJ (United States); Penaflor, B.G.; Piglowski, D.A. [General Atomics, San Diego, CA (United States); Shin, G.W. [University of Science and Technology, Daejeon (Korea, Republic of); Walker, M.L. [General Atomics, San Diego, CA (United States); Woo, M.H. [National Fusion Research Institute, 169-148 Gwahak-ro, yuseong-gu, Daejeon (Korea, Republic of)

    2014-05-15

    Superconducting tokamaks like KSTAR, EAST and ITER need elaborate magnetic controls mainly due to either the demanding experiment schedule or tighter hardware limitations caused by the superconducting coils. In order to reduce the operation runtime requirements, two types of plasma simulators for the KSTAR plasma control system (PCS) have been developed for improving axisymmetric magnetic controls. The first one is an open-loop type, which can reproduce the control done in an old shot by loading the corresponding diagnostics data and PCS setup. The other one, a closed-loop simulator based on a linear nonrigid plasma model, is designed to simulate dynamic responses of the plasma equilibrium and plasma current (I{sub p}) due to changes of the axisymmetric poloidal field (PF) coil currents, poloidal beta, and internal inductance. The closed-loop simulator is the one that actually can test and enable alteration of the feedback control setup for the next shot. The simulators have been used routinely in 2012 plasma campaign, and the experimental performances of the axisymmetric shape control algorithm are enhanced. Quality of the real-time EFIT has been enhanced by utilizations of the open-loop type. Using the closed-loop type, the decoupling scheme of the plasma current control and axisymmetric shape controls are verified through both the simulations and experiments. By combining with the relay feedback tuning algorithm, the improved controls helped to maintain the shape suitable for longer H-mode (10–16 s) with the number of required commissioning shots largely reduced.

  7. Disturbance Observer based internal Model Controller Design: Applications to Tracking Control of Optical Disk Drive

    Energy Technology Data Exchange (ETDEWEB)

    Choi, Hyun Taek; Suh, Il Hong [Hanyang University (Korea, Republic of)

    1999-02-01

    A digital tracking controller is proposed for a precise positioning control under a large repetitive and/or non repetitive disturbances. The proposed controller consists of the internal model controller and the disturbance observer to eliminate the modeling uncertainty. A sufficient condition is given for robust stability of the proposed control system. Numerical Examples are illustrated for a precise head positioning of optical disk drives regardless of a torque disturbance and/or output disturbance. (author). 8 refs., 19 figs.

  8. Multivariate statistical process control of batch processes based on three-way models

    NARCIS (Netherlands)

    Louwerse, D. J.; Smilde, A. K.

    2000-01-01

    The theory of batch MSPC control charts is extended and improved control charts an developed. Unfold-PCA, PARAFAC and Tucker3 models are discussed and used as a basis for these charts. The results of the different models are compared and the performance of the control charts based on these models is

  9. Inverse grey-box model-based control of a dielectric elastomer actuator

    DEFF Research Database (Denmark)

    Jones, Richard William; Sarban, Rahimullah

    2012-01-01

    control performance across the operating range of the DE actuator, a gain scheduling term, which linearizes the operating characteristics of the tubular dielectric elastomer actuator, is developed and implemented in series with the IMC controller. The IMC-based approach is investigated for servo control......An accurate physical-based electromechanical model of a commercially available tubular dielectric elastomer (DE) actuator has been developed and validated. In this contribution, the use of the physical-based electromechanical model to formulate a model-based controller is examined. The choice...... of control scheme was dictated by the desire for transparency in both controller design and operation. The internal model control (IMC) approach was chosen. In this particular application, the inverse of the linearized form of the grey-box model is used to formulate the IMC controller. To ensure consistent...

  10. An Approach to Enforcing Clark-Wilson Model in Role-based Access Control Model

    Institute of Scientific and Technical Information of China (English)

    LIANGBin; SHIWenchang; SUNYufang; SUNBo

    2004-01-01

    Using one security model to enforce another is a prospective solution to multi-policy support. In this paper, an approach to the enforcing Clark-Wilson data integrity model in the Role-based access control (RBAC) model is proposed. An enforcement construction with great feasibility is presented. In this construction, a direct way to enforce the Clark-Wilson model is provided, the corresponding relations among users, transformation procedures, and constrained data items are strengthened; the concepts of task and subtask are introduced to enhance the support to least-privilege. The proposed approach widens the applicability of RBAC. The theoretical foundation for adopting Clark-Wilson model in a RBAC system with small cost is offered to meet the requirements of multi-policy support and policy flexibility.

  11. Model-based Acceleration Control of Turbofan Engines with a Hammerstein-Wiener Representation

    Science.gov (United States)

    Wang, Jiqiang; Ye, Zhifeng; Hu, Zhongzhi; Wu, Xin; Dimirovsky, Georgi; Yue, Hong

    2017-05-01

    Acceleration control of turbofan engines is conventionally designed through either schedule-based or acceleration-based approach. With the widespread acceptance of model-based design in aviation industry, it becomes necessary to investigate the issues associated with model-based design for acceleration control. In this paper, the challenges for implementing model-based acceleration control are explained; a novel Hammerstein-Wiener representation of engine models is introduced; based on the Hammerstein-Wiener model, a nonlinear generalized minimum variance type of optimal control law is derived; the feature of the proposed approach is that it does not require the inversion operation that usually upsets those nonlinear control techniques. The effectiveness of the proposed control design method is validated through a detailed numerical study.

  12. Task-role-based Access Control Model in Smart Health-care System

    OpenAIRE

    Wang Peng; Jiang Lingyun

    2015-01-01

    As the development of computer science and smart health-care technology, there is a trend for patients to enjoy medical care at home. Taking enormous users in the Smart Health-care System into consideration, access control is an important issue. Traditional access control models, discretionary access control, mandatory access control, and role-based access control, do not properly reflect the characteristics of Smart Health-care System. This paper proposes an advanced access control model for...

  13. Development of Power Controller System based on Model Reference Adaptive Control for a Nuclear Reactor

    International Nuclear Information System (INIS)

    Mohd Sabri Minhat; Izhar Abu Hussin; Ridzuan Abdul Mutalib

    2014-01-01

    The Reactor TRIGA PUSPATI (RTP)-type TRIGA Mark II was installed in the year 1982. The Power Controller System (PCS) or Automated Power Controller System (APCS) is very important for reactor operation and safety reasons. It is a function of controlled reactivity and reactor power. The existing power controller system is under development and due to slow response, low accuracy and low stability on reactor power control affecting the reactor safety. The nuclear reactor is a nonlinear system in nature, and it is power increases continuously with time. The reactor parameters vary as a function of power, fuel burnup and control rod worth. The output power value given by the power control system is not exactly as real value of reactor power. Therefore, controller system design is very important, an adaptive controller seems to be inevitable. The method chooses is a linear controller by using feedback linearization, for example Model Reference Adaptive Control. The developed APCS for RTP will be design by using Model Reference Adaptive Control (MRAC). The structured of RTP model to produce the dynamic behaviour of RTP on entire operating power range from 0 to 1MWatt. The dynamic behavior of RTP model is produced by coupling of neutronic and thermal-hydraulics. It will be developed by using software MATLAB/Simulink and hardware module card to handle analog input signal. A new algorithm for APCS is developed to control the movement of control rods with uniformity and orderly for RTP. Before APCS test to real plant, simulation results shall be obtained from RTP model on reactor power, reactivity, period, control rod positions, fuel and coolant temperatures. Those data are comparable with the real data for validation. After completing the RTP model, APCS will be tested to real plant on power control system performance by using real signal from RTP including fail-safe operation, system reliable, fast response, stability and accuracy. The new algorithm shall be a satisfied

  14. Model predictive controller-based multi-model control system for longitudinal stability of distributed drive electric vehicle.

    Science.gov (United States)

    Shi, Ke; Yuan, Xiaofang; Liu, Liang

    2018-01-01

    Distributed drive electric vehicle(DDEV) has been widely researched recently, its longitudinal stability is a very important research topic. Conventional wheel slip ratio control strategies are usually designed for one special operating mode and the optimal performance cannot be obtained as DDEV works under various operating modes. In this paper, a novel model predictive controller-based multi-model control system (MPC-MMCS) is proposed to solve the longitudinal stability problem of DDEV. Firstly, the operation state of DDEV is summarized as three kinds of typical operating modes. A submodel set is established to accurately represent the state value of the corresponding operating mode. Secondly, the matching degree between the state of actual DDEV and each submodel is analyzed. The matching degree is expressed as the weight coefficient and calculated by a modified recursive Bayes theorem. Thirdly, a nonlinear MPC is designed to achieve the optimal wheel slip ratio for each submodel. The optimal design of MPC is realized by parallel chaos optimization algorithm(PCOA)with computational accuracy and efficiency. Finally, the control output of MPC-MMCS is computed by the weighted output of each MPC to achieve smooth switching between operating modes. The proposed MPC-MMCS is evaluated on eight degrees of freedom(8DOF)DDEV model simulation platform and simulation results of different condition show the benefits of the proposed control system. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

  15. Model based Control of a Continuous Yeast Fermentation

    DEFF Research Database (Denmark)

    Andersen, Maria Yolanda; Brabrand, Henrik; Jørgensen, Sten Bay

    1991-01-01

    Control of a continuous fermentation with Saccharomyces cerevisiae is performed by manipulation of the feed flow rate using an ethanol measurement in the exit gas The process is controlled at the critical dilution rate with a low ethanol concentration of 40-50 mg/l. A standard PI controller is able...

  16. Model-Based Brake Control including Tyre Behaviour

    NARCIS (Netherlands)

    De Vries, E.J.H.

    2012-01-01

    The objective of the thesis is to develop a method for controlled braking of a vehicle. The brake pedal depression has been considered to be proportional to the intended deceleration. The brake controller is not aimed to replace a cruise control; it will have an anti-lock braking (ABS) function. The

  17. Task-and-role-based access-control model for computational grid

    Institute of Scientific and Technical Information of China (English)

    LONG Tao; HONG Fan; WU Chi; SUN Ling-li

    2007-01-01

    Access control in a grid environment is a challenging issue because the heterogeneous nature and independent administration of geographically dispersed resources in grid require access control to use fine-grained policies. We established a task-and-role-based access-control model for computational grid (CG-TRBAC model), integrating the concepts of role-based access control (RBAC) and task-based access control (TBAC). In this model, condition restrictions are defined and concepts specifically tailored to Workflow Management System are simplified or omitted so that role assignment and security administration fit computational grid better than traditional models; permissions are mutable with the task status and system variables, and can be dynamically controlled. The CG-TRBAC model is proved flexible and extendible. It can implement different control policies. It embodies the security principle of least privilege and executes active dynamic authorization. A task attribute can be extended to satisfy different requirements in a real grid system.

  18. Multi-model-based Access Control in Construction Projects

    Directory of Open Access Journals (Sweden)

    Frank Hilbert

    2012-04-01

    Full Text Available During the execution of large scale construction projects performed by Virtual Organizations (VO, relatively complex technical models have to be exchanged between the VO members. For linking the trade and transfer of these models, a so-called multi-model container format was developed. Considering the different skills and tasks of the involved partners, it is not necessary for them to know all the models in every technical detailing. Furthermore, the model size can lead to a delay in communication. In this paper an approach is presented for defining model cut-outs according to the current project context. Dynamic dependencies to the project context as well as static dependencies on the organizational structure are mapped in a context-sensitive rule. As a result, an approach for dynamic filtering of multi-models is obtained which ensures, together with a filtering service, that the involved VO members get a simplified view of complex multi-models as well as sufficient permissions depending on their tasks.

  19. Occupant feedback based model predictive control for thermal comfort and energy optimization: A chamber experimental evaluation

    International Nuclear Information System (INIS)

    Chen, Xiao; Wang, Qian; Srebric, Jelena

    2016-01-01

    Highlights: • This study evaluates an occupant-feedback driven Model Predictive Controller (MPC). • The MPC adjusts indoor temperature based on a dynamic thermal sensation (DTS) model. • A chamber model for predicting chamber air temperature is developed and validated. • Experiments show that MPC using DTS performs better than using Predicted Mean Vote. - Abstract: In current centralized building climate control, occupants do not have much opportunity to intervene the automated control system. This study explores the benefit of using thermal comfort feedback from occupants in the model predictive control (MPC) design based on a novel dynamic thermal sensation (DTS) model. This DTS model based MPC was evaluated in chamber experiments. A hierarchical structure for thermal control was adopted in the chamber experiments. At the high level, an MPC controller calculates the optimal supply air temperature of the chamber heating, ventilation, and air conditioning (HVAC) system, using the feedback of occupants’ votes on thermal sensation. At the low level, the actual supply air temperature is controlled by the chiller/heater using a PI control to achieve the optimal set point. This DTS-based MPC was also compared to an MPC designed based on the Predicted Mean Vote (PMV) model for thermal sensation. The experiment results demonstrated that the DTS-based MPC using occupant feedback allows significant energy saving while maintaining occupant thermal comfort compared to the PMV-based MPC.

  20. Neural-Based Compensation of Nonlinearities in an Airplane Longitudinal Model with Dynamic-Inversion Control

    Directory of Open Access Journals (Sweden)

    YanBin Liu

    2017-01-01

    Full Text Available The inversion design approach is a very useful tool for the complex multiple-input-multiple-output nonlinear systems to implement the decoupling control goal, such as the airplane model and spacecraft model. In this work, the flight control law is proposed using the neural-based inversion design method associated with the nonlinear compensation for a general longitudinal model of the airplane. First, the nonlinear mathematic model is converted to the equivalent linear model based on the feedback linearization theory. Then, the flight control law integrated with this inversion model is developed to stabilize the nonlinear system and relieve the coupling effect. Afterwards, the inversion control combined with the neural network and nonlinear portion is presented to improve the transient performance and attenuate the uncertain effects on both external disturbances and model errors. Finally, the simulation results demonstrate the effectiveness of this controller.

  1. An Efficient Role and Object Based Access Control Model Implemented in a PDM System

    Institute of Scientific and Technical Information of China (English)

    HUANG Xiaowen; TAN Jian; HUANG Xiangguo

    2006-01-01

    An effective and reliable access control is crucial to a PDM system. This article has discussed the commonly used access control models, analyzed their advantages and disadvantages, and proposed a new Role and Object based access control model that suits the particular needs of a PDM system. The new model has been implemented in a commercial PDM system, which has demonstrated enhanced flexibility and convenience.

  2. Artificial intelligence in process control: Knowledge base for the shuttle ECS model

    Science.gov (United States)

    Stiffler, A. Kent

    1989-01-01

    The general operation of KATE, an artificial intelligence controller, is outlined. A shuttle environmental control system (ECS) demonstration system for KATE is explained. The knowledge base model for this system is derived. An experimental test procedure is given to verify parameters in the model.

  3. A Riccati-Based Interior Point Method for Efficient Model Predictive Control of SISO Systems

    DEFF Research Database (Denmark)

    Hagdrup, Morten; Johansson, Rolf; Bagterp Jørgensen, John

    2017-01-01

    model parts separate. The controller is designed based on the deterministic model, while the Kalman filter results from the stochastic part. The controller is implemented as a primal-dual interior point (IP) method using Riccati recursion and the computational savings possible for SISO systems...

  4. A Comparison of Exposure Control Procedures in CAT Systems Based on Different Measurement Models for Testlets

    Science.gov (United States)

    Boyd, Aimee M.; Dodd, Barbara; Fitzpatrick, Steven

    2013-01-01

    This study compared several exposure control procedures for CAT systems based on the three-parameter logistic testlet response theory model (Wang, Bradlow, & Wainer, 2002) and Masters' (1982) partial credit model when applied to a pool consisting entirely of testlets. The exposure control procedures studied were the modified within 0.10 logits…

  5. Cutting-in control of the variable speed constant frequency wind power generator based on internal model controller

    Energy Technology Data Exchange (ETDEWEB)

    Guo Jindong; Xu Honghua; Zhao Dongli [Inst. of Electrical Engineering, CAS, BJ (China)

    2008-07-01

    The no-impact-current cutting-in-network control is the key of variable speed constant frequency (VSCF) wind power control system. Based on the stator flux linkage oriented control theory of doubly fed induction generator (DFIG), the field-oriented vector control technique and the internal model controller (IMC) are transplanted into the voltage control of DFIG and a novel cutting-in control strategy is obtained. The strategy does not need the exact inductor generator model, and has perfect performance without overshoot. The structure of the controller is simple, and the only parameter to be adjusted is directly related to system performance, so the strategy is easy to realize. Finally the strategy is studied by simulation using Matlab, the results of the simulation show that the control strategy can effectively control the stator voltage. (orig.)

  6. Task-role-based Access Control Model in Smart Health-care System

    Directory of Open Access Journals (Sweden)

    Wang Peng

    2015-01-01

    Full Text Available As the development of computer science and smart health-care technology, there is a trend for patients to enjoy medical care at home. Taking enormous users in the Smart Health-care System into consideration, access control is an important issue. Traditional access control models, discretionary access control, mandatory access control, and role-based access control, do not properly reflect the characteristics of Smart Health-care System. This paper proposes an advanced access control model for the medical health-care environment, task-role-based access control model, which overcomes the disadvantages of traditional access control models. The task-role-based access control (T-RBAC model introduces a task concept, dividing tasks into four categories. It also supports supervision role hierarchy. T-RBAC is a proper access control model for Smart Health-care System, and it improves the management of access rights. This paper also proposes an implementation of T-RBAC, a binary two-key-lock pair access control scheme using prime factorization.

  7. Comparison of sensorless dimming control based on building modeling and solar power generation

    International Nuclear Information System (INIS)

    Lee, Naeun; Kim, Jonghun; Jang, Cheolyong; Sung, Yoondong; Jeong, Hakgeun

    2015-01-01

    Artificial lighting in office buildings accounts for about 30% of the total building energy consumption. Lighting energy is important to reduce building energy consumption since artificial lighting typically has a relatively large energy conversion factor. Therefore, previous studies have proposed a dimming control using daylight. When applied dimming control, method based on building modeling does not need illuminance sensors. Thus, it can be applied to existing buildings that do not have illuminance sensors. However, this method does not accurately reflect real-time weather conditions. On the other hand, solar power generation from a PV (photovoltaic) panel reflects real-time weather conditions. The PV panel as the sensor improves the accuracy of dimming control by reflecting disturbance. Therefore, we compared and analyzed two types of sensorless dimming controls: those based on the building modeling and those that based on solar power generation using PV panels. In terms of energy savings, we found that a dimming control based on building modeling is more effective than that based on solar power generation by about 6%. However, dimming control based on solar power generation minimizes the inconvenience to occupants and can also react to changes in solar radiation entering the building caused by dirty window. - Highlights: • We conducted sensorless dimming control based on solar power generation. • Dimming controls using building modeling and solar power generation were compared. • The real time weather conditions can be considered by using solar power generation. • Dimming control using solar power generation minimizes inconvenience to occupants

  8. Multiagent-Based Reactive Power Sharing and Control Model for Islanded Microgrids

    DEFF Research Database (Denmark)

    Chen, Feixiong; Chen, Minyou; Li, Qiang

    2016-01-01

    of the control model, in which the uncertainty of intermittent DGs, variations in load demands, as well as impacts of time delays are considered. The simulation results demonstrate the eectiveness of the control model in proportional reactive power sharing, and the plug and play capability of the control model......In islanded microgrids (MGs), the reactive power cannot be shared proportionally among distributed generators (DGs) with conventional droop control, due to the mismatch in feeder impedances. For the purpose of proportional reactive power sharing, a multiagent system (MAS) based distributed control...

  9. The representation of knowledge within model-based control systems

    International Nuclear Information System (INIS)

    Weygand, D.P.; Koul, R.

    1987-01-01

    The ability to represent knowledge is often considered essential to build systems with reasoning capabilities. In computer science, a good solution often depends on a good representation. The first step in development of most computer applications is selection of a representation for the input, output, and intermediate results that the program will operate upon. For applications in artificial intelligence, this initial choice of representation is especially important. This is because the possible representational paradigms are diverse and the forcing criteria for the choice are usually not clear in the beginning. Yet, the consequences of an inadequate choice can be devastating in the later state of a project if it is discovered that critical information cannot be encoded within the chosen representational paradigm. Problems arise when designing representational systems to support any kind of Knowledge-Base System, that is a computer system that uses knowledge to perform some task. The general case of knowledge-based systems can be thought of as reasoning agents applying knowledge to achieve goals. Artificial Intelligence (AI) research involves building computer systems to perform tasks of perception and reasoning, as well as storage and retrieval of data. The problem of automatically perceiving large patterns in data is a perceptual task that begins to be important for many expert systems applications. Most of AI research assumes that what needs to be represented is known a priori; an AI researcher's job is just figuring out how to encode the information in the system's data structure and procedures. 10 refs

  10. Model-based fuzzy control solutions for a laboratory Antilock Braking System

    DEFF Research Database (Denmark)

    Precup, Radu-Emil; Spataru, Sergiu; Rǎdac, Mircea-Bogdan

    2010-01-01

    This paper gives two original model-based fuzzy control solutions dedicated to the longitudinal slip control of Antilock Braking System laboratory equipment. The parallel distributed compensation leads to linear matrix inequalities which guarantee the global stability of the fuzzy control systems...

  11. Model-based specification, analysis and synthesis of servo controllers for lithoscanners

    NARCIS (Netherlands)

    Schiffelers, R.; Alberts, W.; Voeten, J.P.M.

    2012-01-01

    ASML is the world's leading provider of complex lithography systems for the semiconductor industry. Such systems consist of numerous servo control systems. To design such control systems, a multi-disciplinary model-based development environment has been developed. It is based on a set of domain

  12. International Workshop on Advanced Dynamics and Model Based Control of Structures and Machines

    CERN Document Server

    Belyaev, Alexander; Krommer, Michael

    2017-01-01

    The papers in this volume present and discuss the frontiers in the mechanics of controlled machines and structures. They are based on papers presented at the International Workshop on Advanced Dynamics and Model Based Control of Structures and Machines held in Vienna in September 2015. The workshop continues a series of international workshops held in Linz (2008) and St. Petersburg (2010).

  13. The representation of knowledge within model-based control systems

    International Nuclear Information System (INIS)

    Weygand, D.P.; Koul, R.

    1987-01-01

    Representation of knowledge in artificially intelligent systems is discussed. Types of knowledge that might need to be represented in AI systems are listed, and include knowledge about objects, events, knowledge about how to do things, and knowledge about what human beings know (meta-knowledge). The use of knowledge in AI systems is discussed in terms of acquiring and retrieving knowledge and reasoning about known facts. Different kinds of reasonings or representations are ghen described with some examples given. These include formal reasoning or logical representation, which is related to mathematical logic, production systems, which are based on the idea of condition-action pairs (production), procedural reasoning, which uses pre-formed plans to solve problems, frames, which provide a structure for representing knowledge in an organized manner, direct analogical representations, which represent knowledge in such a manner that permits some observation without deduction

  14. Quadrotor Trajectory Tracking Based on Quasi-LPV System and Internal Model Control

    Directory of Open Access Journals (Sweden)

    ZeFang He

    2015-01-01

    Full Text Available Internal model control (IMC design method based on quasi-LPV (Linear Parameter Varying system is proposed. In this method, the nonlinear model is firstly transformed to the linear model based on quasi-LPV method; then, the quadrotor nonlinear motion function is transformed to transfer function matrix based on the transformation model from the state space to the transfer function; further, IMC is designed to control the controlled object represented by transfer function matrix and realize quadrotor trajectory tracking. The performance of the controller proposed in this paper is tested by tracking for three reference trajectories with drastic changes. The simulation results indicate that the control method proposed in this paper has stronger robustness to parameters uncertainty and disturbance rejection performance.

  15. Model-based design of supervisory controllers for baggage handling systems

    NARCIS (Netherlands)

    Swartjes, L.; van Beek, D.A.; Fokkink, W.J.; van Eekelen, J.A.W.M.

    2017-01-01

    The complexity of airport baggage handling systems in combination with the required high level of robustness makes designing supervisory controllers for these systems a challenging task. We show how a state of the art, formal, model-based design framework has been successfully used for model-based

  16. Analytical Model-based Fault Detection and Isolation in Control Systems

    DEFF Research Database (Denmark)

    Vukic, Z.; Ozbolt, H.; Blanke, M.

    1998-01-01

    The paper gives an introduction and an overview of the field of fault detection and isolation for control systems. The summary of analytical (quantitative model-based) methodds and their implementation are presented. The focus is given to mthe analytical model-based fault-detection and fault...

  17. Application of Transfer Matrix Approach to Modeling and Decentralized Control of Lattice-Based Structures

    Science.gov (United States)

    Cramer, Nick; Swei, Sean Shan-Min; Cheung, Kenny; Teodorescu, Mircea

    2015-01-01

    This paper presents a modeling and control of aerostructure developed by lattice-based cellular materials/components. The proposed aerostructure concept leverages a building block strategy for lattice-based components which provide great adaptability to varying ight scenarios, the needs of which are essential for in- ight wing shaping control. A decentralized structural control design is proposed that utilizes discrete-time lumped mass transfer matrix method (DT-LM-TMM). The objective is to develop an e ective reduced order model through DT-LM-TMM that can be used to design a decentralized controller for the structural control of a wing. The proposed approach developed in this paper shows that, as far as the performance of overall structural system is concerned, the reduced order model can be as e ective as the full order model in designing an optimal stabilizing controller.

  18. Flatness-based control and Kalman filtering for a continuous-time macroeconomic model

    Science.gov (United States)

    Rigatos, G.; Siano, P.; Ghosh, T.; Busawon, K.; Binns, R.

    2017-11-01

    The article proposes flatness-based control for a nonlinear macro-economic model of the UK economy. The differential flatness properties of the model are proven. This enables to introduce a transformation (diffeomorphism) of the system's state variables and to express the state-space description of the model in the linear canonical (Brunowsky) form in which both the feedback control and the state estimation problem can be solved. For the linearized equivalent model of the macroeconomic system, stabilizing feedback control can be achieved using pole placement methods. Moreover, to implement stabilizing feedback control of the system by measuring only a subset of its state vector elements the Derivative-free nonlinear Kalman Filter is used. This consists of the Kalman Filter recursion applied on the linearized equivalent model of the financial system and of an inverse transformation that is based again on differential flatness theory. The asymptotic stability properties of the control scheme are confirmed.

  19. Model-based computer-aided design for controlled release of pesticides

    DEFF Research Database (Denmark)

    Muro Sunè, Nuria; Gani, Rafiqul; Bell, G.

    2005-01-01

    In the field of controlled release technology for pesticides or active ingredients (AI), models that can predict its delivery during application are important for purposes of design and marketing of the pesticide product. Appropriate models for the controlled release of pesticides, if available, ...... extended models have been developed and implemented into a computer-aided system. The total model consisting of the property models embedded into the release models are then employed to study the release of different combinations of AIs and polymer-based microcapsules.......In the field of controlled release technology for pesticides or active ingredients (AI), models that can predict its delivery during application are important for purposes of design and marketing of the pesticide product. Appropriate models for the controlled release of pesticides, if available...

  20. Profile control simulations and experiments on TCV : A controller test environment and results using a model-based predictive controller

    NARCIS (Netherlands)

    Maljaars, E.; Felici, F.; Blanken, T.C.; Galperti, C.; Sauter, O.; de Baar, M.R.; Carpanese, F.; Goodman, T.P.; Kim, D.; Kim, S.H.; Kong, M.G.; Mavkov, B.; Merle, A.; Moret, J.M.; Nouailletas, R.; Scheffer, M.; Teplukhina, A.A.; Vu, N.M.T.

    2017-01-01

    The successful performance of a model predictive profile controller is demonstrated in simulations and experiments on the TCV tokamak, employing a profile controller test environment. Stable high-performance tokamak operation in hybrid and advanced plasma scenarios requires control over the safety

  1. Profile control simulations and experiments on TCV: a controller test environment and results using a model-based predictive controller

    NARCIS (Netherlands)

    Maljaars, B.; Felici, F.; Blanken, T. C.; Galperti, C.; Sauter, O.; de Baar, M. R.; Carpanese, F.; Goodman, T. P.; Kim, D.; Kim, S. H.; Kong, M.; Mavkov, B.; Merle, A.; Moret, J.; Nouailletas, R.; Scheffer, M.; Teplukhina, A.; Vu, T.

    2017-01-01

    The successful performance of a model predictive profile controller is demonstrated in simulations and experiments on the TCV tokamak, employing a profile controller test environment. Stable high-performance tokamak operation in hybrid and advanced plasma scenarios requires control over the safety

  2. Implementation of Model View Controller (Mvc) Architecture on Building Web-based Information System

    OpenAIRE

    'Uyun, Shofwatul; Ma'arif, Muhammad Rifqi

    2010-01-01

    The purpose of this paper is to introduce the use of MVC architecture in web-based information systemsdevelopment. MVC (Model-View-Controller) architecture is a way to decompose the application into threeparts: model, view and controller. Originally applied to the graphical user interaction model of input,processing and output. Expected to use the MVC architecture, applications can be built maintenance of moremodular, rusable, and easy and migrate. We have developed a management system of sch...

  3. IMPLEMENTATION OF MODEL VIEW CONTROLLER (MVC) ARCHITECTURE ON BUILDING WEB-BASED INFORMATION SYSTEM

    OpenAIRE

    'Uyun, Shofwatul; Ma'arif, Muhammad Rifqi

    2010-01-01

    The purpose of this paper is to introduce the use of MVC architecture in web-based information systemsdevelopment. MVC (Model-View-Controller) architecture is a way to decompose the application into threeparts: model, view and controller. Originally applied to the graphical user interaction model of input,processing and output. Expected to use the MVC architecture, applications can be built maintenance of moremodular, rusable, and easy and migrate. We have developed a management system of sch...

  4. Maximum Power Point Tracking Control of Photovoltaic Systems: A Polynomial Fuzzy Model-Based Approach

    DEFF Research Database (Denmark)

    Rakhshan, Mohsen; Vafamand, Navid; Khooban, Mohammad Hassan

    2018-01-01

    This paper introduces a polynomial fuzzy model (PFM)-based maximum power point tracking (MPPT) control approach to increase the performance and efficiency of the solar photovoltaic (PV) electricity generation. The proposed method relies on a polynomial fuzzy modeling, a polynomial parallel......, a direct maximum power (DMP)-based control structure is considered for MPPT. Using the PFM representation, the DMP-based control structure is formulated in terms of SOS conditions. Unlike the conventional approaches, the proposed approach does not require exploring the maximum power operational point...

  5. Model-based Sliding Mode Controller of Anti-lock Braking System

    Science.gov (United States)

    Zheng, Lin; Luo, Yue-Gang; Kang, Jing; Shi, Zhan-Qun

    2016-05-01

    The anti-lock braking system (ABS) used in automobiles is used to prevent wheel from lockup and to maintain the steering ability and stability. The sliding mode controller is able to control nonlinear system steadily. In this research, a one-wheel dynamic model with ABS control is built up using model-based method. Using the sliding model controller, the simulation results by using Matlab/Simulink show qualified data compared with optimal slip rate. By using this method, the ABS brake efficiency is improved efficiently.

  6. Fatigue Load Modeling and Control for Wind Turbines based on Hysteresis Operators

    DEFF Research Database (Denmark)

    Barradas Berglind, Jose de Jesus; Wisniewski, Rafal; Soltani, Mohsen

    2015-01-01

    method based on hysteresis operators, which can be used in control loops. Furthermore, we propose a model predictive control (MPC) strategy that incorporates the online fatigue estimation through the objective function, where the ultimate goal in mind is to reduce the fatigue load of the wind turbine......The focus of this work is on fatigue load modeling and controller design for the wind turbine level. The main purpose is to include a model of the damage effects caused by the fatigue of the wind turbine components in the controller design process. This paper addresses an online fatigue estimation...

  7. Polynomial fuzzy model-based control systems stability analysis and control synthesis using membership function dependent techniques

    CERN Document Server

    Lam, Hak-Keung

    2016-01-01

    This book presents recent research on the stability analysis of polynomial-fuzzy-model-based control systems where the concept of partially/imperfectly matched premises and membership-function dependent analysis are considered. The membership-function-dependent analysis offers a new research direction for fuzzy-model-based control systems by taking into account the characteristic and information of the membership functions in the stability analysis. The book presents on a research level the most recent and advanced research results, promotes the research of polynomial-fuzzy-model-based control systems, and provides theoretical support and point a research direction to postgraduate students and fellow researchers. Each chapter provides numerical examples to verify the analysis results, demonstrate the effectiveness of the proposed polynomial fuzzy control schemes, and explain the design procedure. The book is comprehensively written enclosing detailed derivation steps and mathematical derivations also for read...

  8. Data Analytics Based Dual-Optimized Adaptive Model Predictive Control for the Power Plant Boiler

    Directory of Open Access Journals (Sweden)

    Zhenhao Tang

    2017-01-01

    Full Text Available To control the furnace temperature of a power plant boiler precisely, a dual-optimized adaptive model predictive control (DoAMPC method is designed based on the data analytics. In the proposed DoAMPC, an accurate predictive model is constructed adaptively by the hybrid algorithm of the least squares support vector machine and differential evolution method. Then, an optimization problem is constructed based on the predictive model and many constraint conditions. To control the boiler furnace temperature, the differential evolution method is utilized to decide the control variables by solving the optimization problem. The proposed method can adapt to the time-varying situation by updating the sample data. The experimental results based on practical data illustrate that the DoAMPC can control the boiler furnace temperature with errors of less than 1.5% which can meet the requirements of the real production process.

  9. High-speed tracking control of piezoelectric actuators using an ellipse-based hysteresis model.

    Science.gov (United States)

    Gu, Guoying; Zhu, Limin

    2010-08-01

    In this paper, an ellipse-based mathematic model is developed to characterize the rate-dependent hysteresis in piezoelectric actuators. Based on the proposed model, an expanded input space is constructed to describe the multivalued hysteresis function H[u](t) by a multiple input single output (MISO) mapping Gamma:R(2)-->R. Subsequently, the inverse MISO mapping Gamma(-1)(H[u](t),H[u](t);u(t)) is proposed for real-time hysteresis compensation. In controller design, a hybrid control strategy combining a model-based feedforward controller and a proportional integral differential (PID) feedback loop is used for high-accuracy and high-speed tracking control of piezoelectric actuators. The real-time feedforward controller is developed to cancel the rate-dependent hysteresis based on the inverse hysteresis model, while the PID controller is used to compensate for the creep, modeling errors, and parameter uncertainties. Finally, experiments with and without hysteresis compensation are conducted and the experimental results are compared. The experimental results show that the hysteresis compensation in the feedforward path can reduce the hysteresis-caused error by up to 88% and the tracking performance of the hybrid controller is greatly improved in high-speed tracking control applications, e.g., the root-mean-square tracking error is reduced to only 0.34% of the displacement range under the input frequency of 100 Hz.

  10. Model-based sensorimotor integration for multi-joint control: development of a virtual arm model.

    Science.gov (United States)

    Song, D; Lan, N; Loeb, G E; Gordon, J

    2008-06-01

    An integrated, sensorimotor virtual arm (VA) model has been developed and validated for simulation studies of control of human arm movements. Realistic anatomical features of shoulder, elbow and forearm joints were captured with a graphic modeling environment, SIMM. The model included 15 musculotendon elements acting at the shoulder, elbow and forearm. Muscle actions on joints were evaluated by SIMM generated moment arms that were matched to experimentally measured profiles. The Virtual Muscle (VM) model contained appropriate admixture of slow and fast twitch fibers with realistic physiological properties for force production. A realistic spindle model was embedded in each VM with inputs of fascicle length, gamma static (gamma(stat)) and dynamic (gamma(dyn)) controls and outputs of primary (I(a)) and secondary (II) afferents. A piecewise linear model of Golgi Tendon Organ (GTO) represented the ensemble sampling (I(b)) of the total muscle force at the tendon. All model components were integrated into a Simulink block using a special software tool. The complete VA model was validated with open-loop simulation at discrete hand positions within the full range of alpha and gamma drives to extrafusal and intrafusal muscle fibers. The model behaviors were consistent with a wide variety of physiological phenomena. Spindle afferents were effectively modulated by fusimotor drives and hand positions of the arm. These simulations validated the VA model as a computational tool for studying arm movement control. The VA model is available to researchers at website http://pt.usc.edu/cel .

  11. CAD-model based remote handling control system for NET and JET

    International Nuclear Information System (INIS)

    Leinemann, K.; Kuehneapfel, U.; Ludwig, A.

    1989-01-01

    For maintenance work in fusion plants a supervisory control system concept was developed, which organized a close, problem-suited cooperation of man and machine, based on shared control and mutual help. The central module on the task control level of the control system is a real-time simulator based on a three-dimensional CAD-model. This simulator serves for planning and of-line programming of maintenance sequences, and, in th execution phase, for integrated viewing, combining TV and synthetic scene presentation. A first implementation of a geometric simulator and its integration in an overall control system was realized for JET. (author). 5 refs.; 7 figs

  12. Nonlinear model-based robust control of a nuclear reactor using adaptive PIF gains and variable structure controller

    International Nuclear Information System (INIS)

    Park, Moon Ghu; Cho, Nam Zin

    1993-01-01

    A Nonlinear model-based Hybrid Controller (NHC) is developed which consists of the adaptive proportional-integral-feedforward (PIF) gains and variable structure controller. The controller has the robustness against modeling uncertainty and is applied to the trajectory tracking control of single-input, single-output nonlinear systems. The essence of the scheme is to divide the control into four different terms. Namely, the adaptive P-I-F gains and variable structure controller are used to accomplish the specific control actions by each terms. The robustness of the controller is guaranteed by the feedback of estimated uncertainty and the performance specification given by the adaptation of PIF gains using the second method of Lyapunov. The variable structure controller is incorporated to regulate the initial peak of the tracking error during the parameter adaptation is not settled yet. The newly developed NHC method is applied to the power tracking control of a nuclear reactor and the simulation results show great improvement in tracking performance compared with the conventional model-based control methods. (Author)

  13. Variable cycle control model for intersection based on multi-source information

    Science.gov (United States)

    Sun, Zhi-Yuan; Li, Yue; Qu, Wen-Cong; Chen, Yan-Yan

    2018-05-01

    In order to improve the efficiency of traffic control system in the era of big data, a new variable cycle control model based on multi-source information is presented for intersection in this paper. Firstly, with consideration of multi-source information, a unified framework based on cyber-physical system is proposed. Secondly, taking into account the variable length of cell, hysteresis phenomenon of traffic flow and the characteristics of lane group, a Lane group-based Cell Transmission Model is established to describe the physical properties of traffic flow under different traffic signal control schemes. Thirdly, the variable cycle control problem is abstracted into a bi-level programming model. The upper level model is put forward for cycle length optimization considering traffic capacity and delay. The lower level model is a dynamic signal control decision model based on fairness analysis. Then, a Hybrid Intelligent Optimization Algorithm is raised to solve the proposed model. Finally, a case study shows the efficiency and applicability of the proposed model and algorithm.

  14. Wind farms providing secondary frequency regulation: evaluating the performance of model-based receding horizon control

    Directory of Open Access Journals (Sweden)

    C. R. Shapiro

    2018-01-01

    Full Text Available This paper is an extended version of our paper presented at the 2016 TORQUE conference (Shapiro et al., 2016. We investigate the use of wind farms to provide secondary frequency regulation for a power grid using a model-based receding horizon control framework. In order to enable real-time implementation, the control actions are computed based on a time-varying one-dimensional wake model. This model describes wake advection and wake interactions, both of which play an important role in wind farm power production. In order to test the control strategy, it is implemented in a large-eddy simulation (LES model of an 84-turbine wind farm using the actuator disk turbine representation. Rotor-averaged velocity measurements at each turbine are used to provide feedback for error correction. The importance of including the dynamics of wake advection in the underlying wake model is tested by comparing the performance of this dynamic-model control approach to a comparable static-model control approach that relies on a modified Jensen model. We compare the performance of both control approaches using two types of regulation signals, RegA and RegD, which are used by PJM, an independent system operator in the eastern United States. The poor performance of the static-model control relative to the dynamic-model control demonstrates that modeling the dynamics of wake advection is key to providing the proposed type of model-based coordinated control of large wind farms. We further explore the performance of the dynamic-model control via composite performance scores used by PJM to qualify plants for regulation services or markets. Our results demonstrate that the dynamic-model-controlled wind farm consistently performs well, passing the qualification threshold for all fast-acting RegD signals. For the RegA signal, which changes over slower timescales, the dynamic-model control leads to average performance that surpasses the qualification threshold, but further

  15. Quasilinear Extreme Learning Machine Model Based Internal Model Control for Nonlinear Process

    Directory of Open Access Journals (Sweden)

    Dazi Li

    2015-01-01

    Full Text Available A new strategy for internal model control (IMC is proposed using a regression algorithm of quasilinear model with extreme learning machine (QL-ELM. Aimed at the chemical process with nonlinearity, the learning process of the internal model and inverse model is derived. The proposed QL-ELM is constructed as a linear ARX model with a complicated nonlinear coefficient. It shows some good approximation ability and fast convergence. The complicated coefficients are separated into two parts. The linear part is determined by recursive least square (RLS, while the nonlinear part is identified through extreme learning machine. The parameters of linear part and the output weights of ELM are estimated iteratively. The proposed internal model control is applied to CSTR process. The effectiveness and accuracy of the proposed method are extensively verified through numerical results.

  16. Artificial intelligence-based computer modeling tools for controlling slag foaming in electric arc furnaces

    Science.gov (United States)

    Wilson, Eric Lee

    Due to increased competition in a world economy, steel companies are currently interested in developing techniques that will allow for the improvement of the steelmaking process, either by increasing output efficiency or by improving the quality of their product, or both. Slag foaming is one practice that has been shown to contribute to both these goals. However, slag foaming is highly dynamic and difficult to model or control. This dissertation describes an effort to use artificial intelligence-based tools (genetic algorithms, fuzzy logic, and neural networks) to both model and control the slag foaming process. Specifically, a neural network is trained and tested on slag foaming data provided by a steel plant. This neural network model is then controlled by a fuzzy logic controller, which in turn is optimized by a genetic algorithm. This tuned controller is then installed at a steel plant and given control be a more efficient slag foaming controller than what was previously used by the steel plant.

  17. T-S Fuzzy Model Based Control Strategy for the Networked Suspension Control System of Maglev Train

    Directory of Open Access Journals (Sweden)

    Guang He

    2015-01-01

    Full Text Available The control problem for the networked suspension control system of maglev train with random induced time delay and packet dropouts is investigated. First, Takagi-Sugeno (T-S fuzzy models are utilized to represent the discrete-time nonlinear networked suspension control system, and the parameters uncertainties of the nonlinear model have also been taken into account. The controllers take the form of parallel distributed compensation. Then, a sufficient condition for the stability of the networked suspension control system is derived. Based on the criteria, the state feedback fuzzy controllers are obtained, and the controller gains can be computed by using MATLAB LMI Toolbox directly. Finally, both the numerical simulations and physical experiments on the full-scale single bogie of CMS-04 maglev train have been accomplished to demonstrate the effectiveness of this proposed method.

  18. Stabilizing model predictive control of a gantry crane based on flexible set-membership constraints

    NARCIS (Netherlands)

    Iles, Sandor; Lazar, M.; Kolonic, Fetah; Jadranko, Matusko

    2015-01-01

    This paper presents a stabilizing distributed model predictive control of a gantry crane taking into account the variation of cable length. The proposed algorithm is based on the off-line computation of a sequence of 1-step controllable sets and a condition that enables flexible convergence towards

  19. Model ZD-I paper base weight measuring and controlling system

    International Nuclear Information System (INIS)

    Li Nianzu; Song Debin; Wu Guoliang; Hou Yaoxin; Li Dazhen

    1988-01-01

    Model ZD-I Base Weight Measuring and Controlling System has been developed for the automation process in paper-making industry. A single-board microprocessor is installed in the system. The mass thickness can be controlled within 1 g/m 2 if the changing range of concentration and water content is less than 10%

  20. Model-based control of the resistive wall mode in DIII-D: A comparison study

    International Nuclear Information System (INIS)

    Dalessio, J.; Schuster, E.; Humphreys, D.A.; Walker, M.L.; In, Y.; Kim, J.-S.

    2009-01-01

    One of the major non-axisymmetric instabilities under study in the DIII-D tokamak is the resistive wall mode (RWM), a form of plasma kink instability whose growth rate is moderated by the influence of a resistive wall. One of the approaches for RWM stabilization, referred to as magnetic control, uses feedback control to produce magnetic fields opposing the moving field that accompanies the growth of the mode. These fields are generated by coils arranged around the tokamak. One problem with RWM control methods used in present experiments is that they predominantly use simple non-model-based proportional-derivative (PD) controllers requiring substantial derivative gain for stabilization, which implies a large response to noise and perturbations, leading to a requirement for high peak voltages and coil currents, usually leading to actuation saturation and instability. Motivated by this limitation, current efforts in DIII-D include the development of model-based RWM controllers. The General Atomics (GA)/Far-Tech DIII-D RWM model represents the plasma surface as a toroidal current sheet and characterizes the wall using an eigenmode approach. Optimal and robust controllers have been designed exploiting the availability of the RWM dynamic model. The controllers are tested through simulations, and results are compared to present non-model-based PD controllers. This comparison also makes use of the μ structured singular value as a measure of robust stability and performance of the closed-loop system.

  1. Dynamic modeling and performance evaluation of axial flux PMSG based wind turbine system with MPPT control

    Directory of Open Access Journals (Sweden)

    Vahid Behjat

    2014-12-01

    Full Text Available This research work develops dynamic model of a gearless small scale wind power generation system based on a direct driven single sided outer rotor AFPMSG with coreless armature winding. Dynamic modeling of the AFPMSG based wind turbine requires machine parameters. To this end, a 3D FEM model of the generator is developed and from magnetostatic and transient analysis of the FEM model, machine parameters are calculated and utilized in dynamic modeling of the system. A maximum power point tracking (MPPT-based FOC control approach is used to obtain maximum power from the variable wind speed. The simulation results show the proper performance of the developed dynamic model of the AFPMSG, control approach and power generation system.

  2. Wind farms providing secondary frequency regulation: Evaluating the performance of model-based receding horizon control

    International Nuclear Information System (INIS)

    Shapiro, Carl R.; Meneveau, Charles; Gayme, Dennice F.; Meyers, Johan

    2016-01-01

    We investigate the use of wind farms to provide secondary frequency regulation for a power grid. Our approach uses model-based receding horizon control of a wind farm that is tested using a large eddy simulation (LES) framework. In order to enable real-time implementation, the control actions are computed based on a time-varying one-dimensional wake model. This model describes wake advection and interactions, both of which play an important role in wind farm power production. This controller is implemented in an LES model of an 84-turbine wind farm represented by actuator disk turbine models. Differences between the velocities at each turbine predicted by the wake model and measured in LES are used for closed-loop feedback. The controller is tested on two types of regulation signals, “RegA” and “RegD”, obtained from PJM, an independent system operator in the eastern United States. Composite performance scores, which are used by PJM to qualify plants for regulation, are used to evaluate the performance of the controlled wind farm. Our results demonstrate that the controlled wind farm consistently performs well, passing the qualification threshold for all fastacting RegD signals. For the RegA signal, which changes over slower time scales, the controlled wind farm's average performance surpasses the threshold, but further work is needed to enable the controlled system to achieve qualifying performance all of the time. (paper)

  3. Force control of a magnetorheological damper using an elementary hysteresis model-based feedforward neural network

    International Nuclear Information System (INIS)

    Ekkachai, Kittipong; Nilkhamhang, Itthisek; Tungpimolrut, Kanokvate

    2013-01-01

    An inverse controller is proposed for a magnetorheological (MR) damper that consists of a hysteresis model and a voltage controller. The force characteristics of the MR damper caused by excitation signals are represented by a feedforward neural network (FNN) with an elementary hysteresis model (EHM). The voltage controller is constructed using another FNN to calculate a suitable input signal that will allow the MR damper to produce the desired damping force. The performance of the proposed EHM-based FNN controller is experimentally compared to existing control methodologies, such as clipped-optimal control, signum function control, conventional FNN, and recurrent neural network with displacement or velocity inputs. The results show that the proposed controller, which does not require force feedback to implement, provides excellent accuracy, fast response time, and lower energy consumption. (paper)

  4. Nonlinearity measure and internal model control based linearization in anti-windup design

    Energy Technology Data Exchange (ETDEWEB)

    Perev, Kamen [Systems and Control Department, Technical University of Sofia, 8 Cl. Ohridski Blvd., 1756 Sofia (Bulgaria)

    2013-12-18

    This paper considers the problem of internal model control based linearization in anti-windup design. The nonlinearity measure concept is used for quantifying the control system degree of nonlinearity. The linearizing effect of a modified internal model control structure is presented by comparing the nonlinearity measures of the open-loop and closed-loop systems. It is shown that the linearization properties are improved by increasing the control system local feedback gain. However, it is emphasized that at the same time the stability of the system deteriorates. The conflicting goals of stability and linearization are resolved by solving the design problem in different frequency ranges.

  5. Nonlinear Model Predictive Control of a Cable-Robot-Based Motion Simulator

    DEFF Research Database (Denmark)

    Katliar, Mikhail; Fischer, Joerg; Frison, Gianluca

    2017-01-01

    In this paper we present the implementation of a model-predictive controller (MPC) for real-time control of a cable-robot-based motion simulator. The controller computes control inputs such that a desired acceleration and angular velocity at a defined point in simulator's cabin are tracked while...... satisfying constraints imposed by working space and allowed cable forces of the robot. In order to fully use the simulator capabilities, we propose an approach that includes the motion platform actuation in the MPC model. The tracking performance and computation time of the algorithm are investigated...

  6. Model Based Controller Design for a Shell and Tube Heat Exchanger

    Directory of Open Access Journals (Sweden)

    S. Nithya

    2007-10-01

    Full Text Available In all the process industries the process variables like flow, pressure, level and temperature are the main parameters that need to be controlled in both set point and load changes. The transfer of heat is one of the main important operation in the heat exchanger .The transfer of heat may be fluid to fluid, gas to gas i.e. in the same phase or the phase change can occur on either side of the heat exchanger. The control of heat exchanger is complex due to its nonlinear dynamics. For this nonlinear process of a heat exchanger the model is identified to be First Order plus Dead Time (FOPDT.The Internal Model Control (IMC is one of the model predictive control methods based on the predictive output of the process model. The conventional controller tuning is compared with IMC techniques and it found to be suitable for heat exchanger than the conventional PI tuning.

  7. A comparison between model and rule based control of a periodic activated sludge process

    DEFF Research Database (Denmark)

    Isaacs, Steven Howard; Thornberg, D.

    1997-01-01

    Two strategies for control of nitrogen removal in an alternating activated sludge plant are compared. One is based on simple model predictions determining the cycle length at the beginning of each cycle. The other is based on simple rules relating present ammonia and nitrate concentrations. Both ...

  8. A Biomechanical Model of Single-joint Arm Movement Control Based on the Equilibrium Point Hypothesis

    OpenAIRE

    Masataka, SUZUKI; Yoshihiko, YAMAZAKI; Yumiko, TANIGUCHI; Department of Psychology, Kinjo Gakuin University; Department of Health and Physical Education, Nagoya Institute of Technology; College of Human Life and Environment, Kinjo Gakuin University

    2003-01-01

    SUZUKI,M., YAMAZAKI,Y. and TANIGUCHI,Y., A Biomechanical Model of Single-joint Arm Movement Control Based on the Equilibrium Point Hypothesis. Adv. Exerc. Sports Physiol., Vol.9, No.1 pp.7-25, 2003. According to the equilibrium point hypothesis of motor control, control action of muscles is not explicitly computed, but rather arises as a consequence of interaction among moving equilibrium point, reflex feedback and muscle mechanical properties. This approach is attractive as it obviates the n...

  9. Dynamic flowgraph modeling of process and control systems of a nuclear-based hydrogen production plant

    Energy Technology Data Exchange (ETDEWEB)

    Al-Dabbagh, Ahmad W. [Faculty of Engineering and Applied Science, University of Ontario Institute of Technology, 2000 Simcoe Street North, Oshawa, Ontario (Canada); Lu, Lixuan [Faculty of Energy Systems and Nuclear Science, Faculty of Engineering and Applied Science, University of Ontario Institute of Technology, 2000 Simcoe Street North, Oshawa, Ontario (Canada)

    2010-09-15

    Modeling and analysis of system reliability facilitate the identification of areas of potential improvement. The Dynamic Flowgraph Methodology (DFM) is an emerging discrete modeling framework that allows for capturing time dependent behaviour, switching logic and multi-state representation of system components. The objective of this research is to demonstrate the process of dynamic flowgraph modeling of a nuclear-based hydrogen production plant with the copper-chlorine (Cu-Cl) cycle. Modeling of the thermochemical process of the Cu-Cl cycle in conjunction with a networked control system proposed for monitoring and control of the process is provided. This forms the basis for future component selection. (author)

  10. Internal-Model-Principle-Based Specific Harmonics Repetitive Controller for Grid-Connected PWM Inverters

    Directory of Open Access Journals (Sweden)

    Wenzhou Lu

    2016-01-01

    Full Text Available This paper analyzes the general properties of IMP-based controller and presents an internal-model-principle-based (IMP-based specific harmonics repetitive control (SHRC scheme. The proposed SHRC is effective for specific nk±m order harmonics, with n>m≥0 and k=0,1,2,…. Using the properties of exponential function, SHRC can also be rewritten into the format of multiple resonant controllers in parallel, where the control gain of SHRC is n/2 multiple of that of conventional RC (CRC. Therefore, including SHRC in a stable closed-loop feedback control system, asymptotic disturbance eliminating, or reference tracking for any periodic signal only including these specific harmonic components at n/2 times faster error convergence rate compared with CRC can be achieved. Application examples of SHRC controlled three-phase/single-phase grid-connected PWM inverters demonstrate the effectiveness and advantages of the proposed SHRC scheme.

  11. Model-Based Development and Evaluation of Control for Complex Multi-Domain Systems

    DEFF Research Database (Denmark)

    Grujic, Ivan; Nilsson, Rene

    A Cyber-Physical System (CPS) incorporates sensing, actuating, computing and communicative capabilities, which are often combined to control the system. The development of CPSs poses a challenge, since the complexity of the physical system dynamics must be taken into account when designing...... Unmanned Aerial Vehicle (UAV) has been constructed and used to develop an attitude controller based on Model Predictive Control (MPC). The MPC controller has been compared to an existing open source Proportional Integral Derivative (PID) attitude controller. This thesis contributes to the discipline...

  12. Modeling and control design of a stand alone wind energy conversion system based on functional model predictive control

    Energy Technology Data Exchange (ETDEWEB)

    Kassem, Ahmed M. [Beni-Suef University, Electrical Dept., Beni Suef (Egypt)

    2012-09-15

    This paper investigates the application of the model predictive control (MPC) approach to control the voltage and frequency of a stand alone wind generation system. This scheme consists of a wind turbine which drives an induction generator feeding an isolated load. A static VAR compensator is connected at the induction generator terminals to regulate the load voltage. The rotor speed, and thereby the load frequency are controlled via adjusting the mechanical power input using the blade pitch-angle. The MPC is used to calculate the optimal control actions including system constraints. To alleviate computational effort and to reduce numerical problems, particularly in large prediction horizon, an exponentially weighted functional model predictive control (FMPC) is employed. Digital simulations have been carried out in order to validate the effectiveness of the proposed scheme. The proposed controller has been tested through step changes in the wind speed and the load impedance. Simulation results show that adequate performance of the proposed wind energy scheme has been achieved. Moreover, this scheme is robust against the parameters variation and eliminates the influence of modeling and measurement errors. (orig.)

  13. Dynamic Modeling of Steam Condenser and Design of PI Controller Based on Grey Wolf Optimizer

    OpenAIRE

    Shu-Xia Li; Jie-Sheng Wang

    2015-01-01

    Shell-and-tube condenser is a heat exchanger for cooling steam with high temperature and pressure, which is one of the main kinds of heat exchange equipment in thermal, nuclear, and marine power plant. Based on the lumped parameter modeling method, the dynamic mathematical model of the simplified steam condenser is established. Then, the pressure PI control system of steam condenser based on the Matlab/Simulink simulation platform is designed. In order to obtain better performance, a new meta...

  14. Model-based control strategies for systems with constraints of the program type

    Science.gov (United States)

    Jarzębowska, Elżbieta

    2006-08-01

    The paper presents a model-based tracking control strategy for constrained mechanical systems. Constraints we consider can be material and non-material ones referred to as program constraints. The program constraint equations represent tasks put upon system motions and they can be differential equations of orders higher than one or two, and be non-integrable. The tracking control strategy relies upon two dynamic models: a reference model, which is a dynamic model of a system with arbitrary order differential constraints and a dynamic control model. The reference model serves as a motion planner, which generates inputs to the dynamic control model. It is based upon a generalized program motion equations (GPME) method. The method enables to combine material and program constraints and merge them both into the motion equations. Lagrange's equations with multipliers are the peculiar case of the GPME, since they can be applied to systems with constraints of first orders. Our tracking strategy referred to as a model reference program motion tracking control strategy enables tracking of any program motion predefined by the program constraints. It extends the "trajectory tracking" to the "program motion tracking". We also demonstrate that our tracking strategy can be extended to a hybrid program motion/force tracking.

  15. Nonlinear Model Predictive Control for Solid Oxide Fuel Cell System Based On Wiener Model

    OpenAIRE

    T. H. Lee; J. H. Park; S. M. Lee; S. C. Lee

    2010-01-01

    In this paper, we consider Wiener nonlinear model for solid oxide fuel cell (SOFC). The Wiener model of the SOFC consists of a linear dynamic block and a static output non-linearity followed by the block, in which linear part is approximated by state-space model and the nonlinear part is identified by a polynomial form. To control the SOFC system, we have to consider various view points such as operating conditions, another constraint conditions, change of load current and so on. A change of ...

  16. Consistency maintenance for constraint in role-based access control model

    Institute of Scientific and Technical Information of China (English)

    韩伟力; 陈刚; 尹建伟; 董金祥

    2002-01-01

    Constraint is an important aspect of role-based access control and is sometimes argued to be the principal motivation for role-based access control (RBAC). But so far few authors have discussed consistency maintenance for constraint in RBAC model. Based on researches of constraints among roles and types of inconsistency among constraints, this paper introduces corresponding formal rules, rule-based reasoning and corresponding methods to detect, avoid and resolve these inconsistencies. Finally, the paper introduces briefly the application of consistency maintenance in ZD-PDM, an enterprise-oriented product data management (PDM) system.

  17. A control strategy for electro-magneto-mechanical system based on virtual system model

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Hong Youn; Heo, Hoon [Dept. of Control and Instrumentation Engineering, Korea University, Seoul (Korea, Republic of); Yun, Young Min [TPC Mechatronics Co., Ltd., Incheon (Korea, Republic of)

    2016-09-15

    A new approach to the control of electro-magneto-mechanical system is proposed in this paper. Conventionally, these systems are controlled based on the Maxwell system model via an on-off or PID control technique, which displays acceptable performance in the low frequency region, but not in the high frequency region where position control performance is greatly degraded. In order to improve the performance, a newly developed virtual 2nd order system modeling technique, SSID, is adopted for a complex electro-magnetomechanical system in the study. This technique states that any unknown system exposed to a random disturbance with unknown intensity can be identified in terms of a virtual 2nd order system model via the inverse process of a certain stochastic analysis. As a typical hybrid system, a solenoid valve is used as the target electro-magneto-mechanical system to study the modeling of the virtual 2nd order system. In order to confirm the performance of the proposed control strategy, autotuning PID controller in PWM mode is utilized. Simulations based on the conventional Maxwell system model with control via the bang-bang, autotuning PID, and the proposed virtual 2nd order system model approaches are conducted using MATLAB Simulink. Performance of these three systems in the low and high frequency bands is also compared. The simulation results reveal that the control performance of the virtual 2nd order system model is much improved compared with that of the Maxwell system model under autotuning PID and bang-bang controls in both low and high frequency regions, where the error is drastically reduced to approximately 1/5 of the original value.

  18. Rectifier Current Control for an LLC Resonant Converter Based on a Simplified Linearized Model

    OpenAIRE

    Zhijian Fang; Junhua Wang; Shanxu Duan; Liangle Xiao; Guozheng Hu; Qisheng Liu

    2018-01-01

    In this paper, a rectifier current control for an LLC resonant converter is proposed, based on a simplified, two-order, linearized model that adds a rectifier current feedback inner loop to improve dynamic performance. Compared to the traditional large-signal model with seven resonant states, this paper utilizes a rectifier current state to represent the characteristics of the resonant states, simplifying the LLC resonant model from seven orders to two orders. Then, the rectifier current feed...

  19. Automatic Traffic-Based Internet Control Message Protocol (ICMP) Model Generation for ns-3

    Science.gov (United States)

    2015-12-01

    more protocols (especially at different layers of the OSI model ), implementing an inference engine to extract inter- and intrapacket dependencies, and...ARL-TR-7543 ● DEC 2015 US Army Research Laboratory Automatic Traffic-Based Internet Control Message Protocol (ICMP) Model ...ICMP) Model Generation for ns-3 by Jaime C Acosta and Felipe Jovel Survivability/Lethality Analysis Directorate, ARL Felipe Sotelo and Caesar

  20. A Sarsa(λ)-based control model for real-time traffic light coordination.

    Science.gov (United States)

    Zhou, Xiaoke; Zhu, Fei; Liu, Quan; Fu, Yuchen; Huang, Wei

    2014-01-01

    Traffic problems often occur due to the traffic demands by the outnumbered vehicles on road. Maximizing traffic flow and minimizing the average waiting time are the goals of intelligent traffic control. Each junction wants to get larger traffic flow. During the course, junctions form a policy of coordination as well as constraints for adjacent junctions to maximize their own interests. A good traffic signal timing policy is helpful to solve the problem. However, as there are so many factors that can affect the traffic control model, it is difficult to find the optimal solution. The disability of traffic light controllers to learn from past experiences caused them to be unable to adaptively fit dynamic changes of traffic flow. Considering dynamic characteristics of the actual traffic environment, reinforcement learning algorithm based traffic control approach can be applied to get optimal scheduling policy. The proposed Sarsa(λ)-based real-time traffic control optimization model can maintain the traffic signal timing policy more effectively. The Sarsa(λ)-based model gains traffic cost of the vehicle, which considers delay time, the number of waiting vehicles, and the integrated saturation from its experiences to learn and determine the optimal actions. The experiment results show an inspiring improvement in traffic control, indicating the proposed model is capable of facilitating real-time dynamic traffic control.

  1. A Sarsa(λ-Based Control Model for Real-Time Traffic Light Coordination

    Directory of Open Access Journals (Sweden)

    Xiaoke Zhou

    2014-01-01

    Full Text Available Traffic problems often occur due to the traffic demands by the outnumbered vehicles on road. Maximizing traffic flow and minimizing the average waiting time are the goals of intelligent traffic control. Each junction wants to get larger traffic flow. During the course, junctions form a policy of coordination as well as constraints for adjacent junctions to maximize their own interests. A good traffic signal timing policy is helpful to solve the problem. However, as there are so many factors that can affect the traffic control model, it is difficult to find the optimal solution. The disability of traffic light controllers to learn from past experiences caused them to be unable to adaptively fit dynamic changes of traffic flow. Considering dynamic characteristics of the actual traffic environment, reinforcement learning algorithm based traffic control approach can be applied to get optimal scheduling policy. The proposed Sarsa(λ-based real-time traffic control optimization model can maintain the traffic signal timing policy more effectively. The Sarsa(λ-based model gains traffic cost of the vehicle, which considers delay time, the number of waiting vehicles, and the integrated saturation from its experiences to learn and determine the optimal actions. The experiment results show an inspiring improvement in traffic control, indicating the proposed model is capable of facilitating real-time dynamic traffic control.

  2. Design of Model-based Controller with Disturbance Estimation in Steer-by-wire System

    Directory of Open Access Journals (Sweden)

    Jung Sanghun

    2018-01-01

    Full Text Available The steer-by-wire system is a next generation steering control technology that has been actively studied because it has many advantages such as fast response, space efficiency due to removal of redundant mechanical elements, and high connectivity with vehicle chassis control, such as active steering. Steer-by-wire system has disturbance composed of tire friction torque and self-aligning torque. These disturbances vary widely due to the weight or friction coefficient change. Therefore, disturbance compensation logic is strongly required to obtain desired performance. This paper proposes model-based controller with disturbance compensation to achieve the robust control performance. Targeted steer-by-wire system is identified through the experiment and system identification method. Moreover, model-based controller is designed using the identified plant model. Disturbance of targeted steer-by-wire is estimated using disturbance observer(DOB, and compensate the estimated disturbance into control input. Experiment of various scenarios are conducted to validate the robust performance of proposed model-based controller.

  3. Offset-Free Model Predictive Control of Open Water Channel Based on Moving Horizon Estimation

    Science.gov (United States)

    Ekin Aydin, Boran; Rutten, Martine

    2016-04-01

    Model predictive control (MPC) is a powerful control option which is increasingly used by operational water managers for managing water systems. The explicit consideration of constraints and multi-objective management are important features of MPC. However, due to the water loss in open water systems by seepage, leakage and evaporation a mismatch between the model and the real system will be created. These mismatch affects the performance of MPC and creates an offset from the reference set point of the water level. We present model predictive control based on moving horizon estimation (MHE-MPC) to achieve offset free control of water level for open water canals. MHE-MPC uses the past predictions of the model and the past measurements of the system to estimate unknown disturbances and the offset in the controlled water level is systematically removed. We numerically tested MHE-MPC on an accurate hydro-dynamic model of the laboratory canal UPC-PAC located in Barcelona. In addition, we also used well known disturbance modeling offset free control scheme for the same test case. Simulation experiments on a single canal reach show that MHE-MPC outperforms disturbance modeling offset free control scheme.

  4. Artificial intelligence-based modeling and control of fluidized bed combustion

    Energy Technology Data Exchange (ETDEWEB)

    Ikonen, E.; Leppaekoski, K. (Univ. of Oulu, Dept. of Process and Environmental Engineering (Finland)). email: enso.ikonen@oulu.fi

    2009-07-01

    AI-inspired techniques have a lot to offer when developing methods for advanced identification, monitoring, control and optimization of industrial processes, such as power plants. Advanced control methods have been extensively examined in the research of the Power Plant Automation group at the Systems Engineering Laboratory, e.g., in fuel inventory modelling, combustion power control, modelling and control of flue gas oxygen, drum control, modelling and control of superheaters, or in optimization of flue-gas emissions. Most engineering approaches to artificial intelligence (AI) are characterized by two fundamental properties: the ability to learn from various sources and the ability to deal with plant complexity. Learning systems that are able to operate in uncertain environments based on incomplete information are commonly referred to as being intelligent. A number of other approaches exist, characterized by these properties, but not easily categorized as AI-systems. Advanced control methods (adaptive, predictive, multivariable, robust, etc.) are based on the availability of a model of the process to be controlled. Hence identification of processes becomes a key issue, leading to the use of adaptation and learning techniques. A typical learning control system concerns a selection of learning techniques applied for updating a process model, which in turn is used for the controller design. When design of learning control systems is complemented with concerns for dealing with uncertainties or vaguenesses in models, measurements, or even objectives, particularly close connections exist between advanced process control and methods of artificial intelligence and machine learning. Needs for advanced techniques are typically characterized by the desire to properly handle plant non-linearities, the multivariable nature of the dynamic problems, and the necessity to adapt to changing plant conditions. In the field of fluidized bed combustion (FBC) control, the many promising

  5. Advanced Emergency Braking Control Based on a Nonlinear Model Predictive Algorithm for Intelligent Vehicles

    Directory of Open Access Journals (Sweden)

    Ronghui Zhang

    2017-05-01

    Full Text Available Focusing on safety, comfort and with an overall aim of the comprehensive improvement of a vision-based intelligent vehicle, a novel Advanced Emergency Braking System (AEBS is proposed based on Nonlinear Model Predictive Algorithm. Considering the nonlinearities of vehicle dynamics, a vision-based longitudinal vehicle dynamics model is established. On account of the nonlinear coupling characteristics of the driver, surroundings, and vehicle itself, a hierarchical control structure is proposed to decouple and coordinate the system. To avoid or reduce the collision risk between the intelligent vehicle and collision objects, a coordinated cost function of tracking safety, comfort, and fuel economy is formulated. Based on the terminal constraints of stable tracking, a multi-objective optimization controller is proposed using the theory of non-linear model predictive control. To quickly and precisely track control target in a finite time, an electronic brake controller for AEBS is designed based on the Nonsingular Fast Terminal Sliding Mode (NFTSM control theory. To validate the performance and advantages of the proposed algorithm, simulations are implemented. According to the simulation results, the proposed algorithm has better integrated performance in reducing the collision risk and improving the driving comfort and fuel economy of the smart car compared with the existing single AEBS.

  6. Model-based nonlinear control of hydraulic servo systems: Challenges, developments and perspectives

    Science.gov (United States)

    Yao, Jianyong

    2018-06-01

    Hydraulic servo system plays a significant role in industries, and usually acts as a core point in control and power transmission. Although linear theory-based control methods have been well established, advanced controller design methods for hydraulic servo system to achieve high performance is still an unending pursuit along with the development of modern industry. Essential nonlinearity is a unique feature and makes model-based nonlinear control more attractive, due to benefit from prior knowledge of the servo valve controlled hydraulic system. In this paper, a discussion for challenges in model-based nonlinear control, latest developments and brief perspectives of hydraulic servo systems are presented: Modelling uncertainty in hydraulic system is a major challenge, which includes parametric uncertainty and time-varying disturbance; some specific requirements also arise ad hoc difficulties such as nonlinear friction during low velocity tracking, severe disturbance, periodic disturbance, etc.; to handle various challenges, nonlinear solutions including parameter adaptation, nonlinear robust control, state and disturbance observation, backstepping design and so on, are proposed and integrated, theoretical analysis and lots of applications reveal their powerful capability to solve pertinent problems; and at the end, some perspectives and associated research topics (measurement noise, constraints, inner valve dynamics, input nonlinearity, etc.) in nonlinear hydraulic servo control are briefly explored and discussed.

  7. Support vector regression model based predictive control of water level of U-tube steam generators

    Energy Technology Data Exchange (ETDEWEB)

    Kavaklioglu, Kadir, E-mail: kadir.kavaklioglu@pau.edu.tr

    2014-10-15

    Highlights: • Water level of U-tube steam generators was controlled in a model predictive fashion. • Models for steam generator water level were built using support vector regression. • Cost function minimization for future optimal controls was performed by using the steepest descent method. • The results indicated the feasibility of the proposed method. - Abstract: A predictive control algorithm using support vector regression based models was proposed for controlling the water level of U-tube steam generators of pressurized water reactors. Steam generator data were obtained using a transfer function model of U-tube steam generators. Support vector regression based models were built using a time series type model structure for five different operating powers. Feedwater flow controls were calculated by minimizing a cost function that includes the level error, the feedwater change and the mismatch between feedwater and steam flow rates. Proposed algorithm was applied for a scenario consisting of a level setpoint change and a steam flow disturbance. The results showed that steam generator level can be controlled at all powers effectively by the proposed method.

  8. An Inverse Neural Controller Based on the Applicability Domain of RBF Network Models

    Directory of Open Access Journals (Sweden)

    Alex Alexandridis

    2018-01-01

    Full Text Available This paper presents a novel methodology of generic nature for controlling nonlinear systems, using inverse radial basis function neural network models, which may combine diverse data originating from various sources. The algorithm starts by applying the particle swarm optimization-based non-symmetric variant of the fuzzy means (PSO-NSFM algorithm so that an approximation of the inverse system dynamics is obtained. PSO-NSFM offers models of high accuracy combined with small network structures. Next, the applicability domain concept is suitably tailored and embedded into the proposed control structure in order to ensure that extrapolation is avoided in the controller predictions. Finally, an error correction term, estimating the error produced by the unmodeled dynamics and/or unmeasured external disturbances, is included to the control scheme to increase robustness. The resulting controller guarantees bounded input-bounded state (BIBS stability for the closed loop system when the open loop system is BIBS stable. The proposed methodology is evaluated on two different control problems, namely, the control of an experimental armature-controlled direct current (DC motor and the stabilization of a highly nonlinear simulated inverted pendulum. For each one of these problems, appropriate case studies are tested, in which a conventional neural controller employing inverse models and a PID controller are also applied. The results reveal the ability of the proposed control scheme to handle and manipulate diverse data through a data fusion approach and illustrate the superiority of the method in terms of faster and less oscillatory responses.

  9. Modeling and control of PMSG-based variable-speed wind turbine

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Hong-Woo; Ko, Hee-Sang [Wind Energy Research Center, Korea Institute of Energy Research, Yuseong-gu Jang-Dong 71-2,305-343 Daejeon (Korea); Kim, Sung-Soo [Chungbuk National University (Korea)

    2010-01-15

    This paper presents a control scheme of a variable-speed wind turbine with a permanent-magnetic synchronous generator (PMSG) and full-scale back-to-back voltage source converter. A comprehensive dynamical model of the PMSG wind turbine and its control scheme is presented. The control scheme comprises both the wind-turbine control itself and the power-converter control. In addition, since the PMSG wind turbine is able to support actively the grid due to its capability to control independently active and reactive power production to the imposed set-values with taking into account its operating state and limits, this paper presents the supervisory reactive power control scheme in order to regulate/contribute the voltage at a remote location. The ability of the control scheme is assessed and discussed by means of simulations, based on a candidate site of the offshore wind farm in Jeju, Korea. (author)

  10. Robust stabilization control based on guardian maps theory for a longitudinal model of hypersonic vehicle.

    Science.gov (United States)

    Liu, Yanbin; Liu, Mengying; Sun, Peihua

    2014-01-01

    A typical model of hypersonic vehicle has the complicated dynamics such as the unstable states, the nonminimum phases, and the strong coupling input-output relations. As a result, designing a robust stabilization controller is essential to implement the anticipated tasks. This paper presents a robust stabilization controller based on the guardian maps theory for hypersonic vehicle. First, the guardian maps theories are provided to explain the constraint relations between the open subsets of complex plane and the eigenvalues of the state matrix of closed-loop control system. Then, a general control structure in relation to the guardian maps theories is proposed to achieve the respected design demands. Furthermore, the robust stabilization control law depending on the given general control structure is designed for the longitudinal model of hypersonic vehicle. Finally, a simulation example is provided to verify the effectiveness of the proposed methods.

  11. Virtual Inertia Control-Based Model Predictive Control for Microgrid Frequency Stabilization Considering High Renewable Energy Integration

    Directory of Open Access Journals (Sweden)

    Thongchart Kerdphol

    2017-05-01

    Full Text Available Renewable energy sources (RESs, such as wind and solar generations, equip inverters to connect to the microgrids. These inverters do not have any rotating mass, thus lowering the overall system inertia. This low system inertia issue could affect the microgrid stability and resiliency in the situation of uncertainties. Today’s microgrids will become unstable if the capacity of RESs become larger and larger, leading to the weakening of microgrid stability and resilience. This paper addresses a new concept of a microgrid control incorporating a virtual inertia system based on the model predictive control (MPC to emulate virtual inertia into the microgrid control loop, thus stabilizing microgrid frequency during high penetration of RESs. The additional controller of virtual inertia is applied to the microgrid, employing MPC with virtual inertia response. System modeling and simulations are carried out using MATLAB/Simulink® software. The simulation results confirm the superior robustness and frequency stabilization effect of the proposed MPC-based virtual inertia control in comparison to the fuzzy logic system and conventional virtual inertia control in a system with high integration of RESs. The proposed MPC-based virtual inertia control is able to improve the robustness and frequency stabilization of the microgrid effectively.

  12. Model-Based Control of an Aircraft Engine using an Optimal Tuner Approach

    Science.gov (United States)

    Connolly, Joseph W.; Chicatelli, Amy; Garg, Sanjay

    2012-01-01

    This paper covers the development of a model-based engine control (MBEC) method- ology applied to an aircraft turbofan engine. Here, a linear model extracted from the Commercial Modular Aero-Propulsion System Simulation 40,000 (CMAPSS40k) at a cruise operating point serves as the engine and the on-board model. The on-board model is up- dated using an optimal tuner Kalman Filter (OTKF) estimation routine, which enables the on-board model to self-tune to account for engine performance variations. The focus here is on developing a methodology for MBEC with direct control of estimated parameters of interest such as thrust and stall margins. MBEC provides the ability for a tighter control bound of thrust over the entire life cycle of the engine that is not achievable using traditional control feedback, which uses engine pressure ratio or fan speed. CMAPSS40k is capable of modeling realistic engine performance, allowing for a verification of the MBEC tighter thrust control. In addition, investigations of using the MBEC to provide a surge limit for the controller limit logic are presented that could provide benefits over a simple acceleration schedule that is currently used in engine control architectures.

  13. H∞ Control of Supply Chain Based on Switched Model of Stock Level

    Directory of Open Access Journals (Sweden)

    Junzhi Luo

    2014-01-01

    Full Text Available This paper is concerned with the problem of H∞ control for a class of discrete supply chain systems. A new method based on network control technique is presented to address this issue. Supply chain systems are modeled as networked systems with stochastic time delay. Sufficient conditions for H∞ controller design are given in terms of a set of linear matrix inequalities, based on which the mean-square asymptotic stability as well as H∞ performance is satisfied for such systems. Simulation results are provided to demonstrate the effectiveness of the proposed method.

  14. Model-based safety analysis of a control system using Simulink and Simscape extended models

    Directory of Open Access Journals (Sweden)

    Shao Nian

    2017-01-01

    Full Text Available The aircraft or system safety assessment process is an integral part of the overall aircraft development cycle. It is usually characterized by a very high timely and financial effort and can become a critical design driver in certain cases. Therefore, an increasing demand of effective methods to assist the safety assessment process arises within the aerospace community. One approach is the utilization of model-based technology, which is already well-established in the system development, for safety assessment purposes. This paper mainly describes a new tool for Model-Based Safety Analysis. A formal model for an example system is generated and enriched with extended models. Then, system safety analyses are performed on the model with the assistance of automation tools and compared to the results of a manual analysis. The objective of this paper is to improve the increasingly complex aircraft systems development process. This paper develops a new model-based analysis tool in Simulink/Simscape environment.

  15. Model-based closed-loop glucose control in type 1 diabetes

    DEFF Research Database (Denmark)

    Schmidt, Signe; Boiroux, Dimitri; Duun-Henriksen, Anne Katrine

    2013-01-01

    To improve type 1 diabetes mellitus (T1DM) management, we developed a model predictive control (MPC) algorithm for closed-loop (CL) glucose control based on a linear second-order deterministic-stochastic model. The deterministic part of the model is specified by three patient-specific parameters......: insulin sensitivity factor, insulin action time, and basal insulin infusion rate. The stochastic part is identical for all patients but identified from data from a single patient. Results of the first clinical feasibility test of the algorithm are presented....

  16. Environmental optimal control strategies based on plant canopy photosynthesis responses and greenhouse climate model

    Science.gov (United States)

    Deng, Lujuan; Xie, Songhe; Cui, Jiantao; Liu, Tao

    2006-11-01

    It is the essential goal of intelligent greenhouse environment optimal control to enhance income of cropper and energy save. There were some characteristics such as uncertainty, imprecision, nonlinear, strong coupling, bigger inertia and different time scale in greenhouse environment control system. So greenhouse environment optimal control was not easy and especially model-based optimal control method was more difficult. So the optimal control problem of plant environment in intelligent greenhouse was researched. Hierarchical greenhouse environment control system was constructed. In the first level data measuring was carried out and executive machine was controlled. Optimal setting points of climate controlled variable in greenhouse was calculated and chosen in the second level. Market analysis and planning were completed in third level. The problem of the optimal setting point was discussed in this paper. Firstly the model of plant canopy photosynthesis responses and the model of greenhouse climate model were constructed. Afterwards according to experience of the planting expert, in daytime the optimal goals were decided according to the most maximal photosynthesis rate principle. In nighttime on plant better growth conditions the optimal goals were decided by energy saving principle. Whereafter environment optimal control setting points were computed by GA. Compared the optimal result and recording data in real system, the method is reasonable and can achieve energy saving and the maximal photosynthesis rate in intelligent greenhouse

  17. Model predictive control-based efficient energy recovery control strategy for regenerative braking system of hybrid electric bus

    International Nuclear Information System (INIS)

    Li, Liang; Zhang, Yuanbo; Yang, Chao; Yan, Bingjie; Marina Martinez, C.

    2016-01-01

    Highlights: • A 7-degree-of-freedom model of hybrid electric vehicle with regenerative braking system is built. • A modified nonlinear model predictive control strategy is developed. • The particle swarm optimization algorithm is employed to solve the optimization problem. • The proposed control strategy is verified by simulation and hardware-in-loop tests. • Test results verify the effectiveness of the proposed control strategy. - Abstract: As one of the main working modes, the energy recovered with regenerative braking system provides an effective approach so as to greatly improve fuel economy of hybrid electric bus. However, it is still a challenging issue to ensure braking stability while maximizing braking energy recovery. To solve this problem, an efficient energy recovery control strategy is proposed based on the modified nonlinear model predictive control method. Firstly, combined with the characteristics of the compound braking process of single-shaft parallel hybrid electric bus, a 7 degrees of freedom model of the vehicle longitudinal dynamics is built. Secondly, considering nonlinear characteristic of the vehicle model and the efficiency of regenerative braking system, the particle swarm optimization algorithm within the modified nonlinear model predictive control is adopted to optimize the torque distribution between regenerative braking system and pneumatic braking system at the wheels. So as to reduce the computational time of modified nonlinear model predictive control, a nearest point method is employed during the braking process. Finally, the simulation and hardware-in-loop test are carried out on road conditions with different tire–road adhesion coefficients, and the proposed control strategy is verified by comparing it with the conventional control method employed in the baseline vehicle controller. The simulation and hardware-in-loop test results show that the proposed strategy can ensure vehicle safety during emergency braking

  18. Neuro-adaptive control in beating heart surgery based on the viscoelastic tissue model

    Directory of Open Access Journals (Sweden)

    Setareh Rezakhani

    2014-04-01

    Full Text Available In this paper, the problem of 3D heart motion in beating heart surgery is resolved by proposing a parallel force-motion controller. Motion controller is designed based on neuro-adaptive approach to compensate 3D heart motion and deal with uncertainity in dynamic parameters, while an implicit force control is implemented by considering a viscoelastic tissue model. Stability analysis is proved through Lypanov’s stability theory and Barballet’s lemma. Simulation results, for D2M2 robot, which is done in nominal case and viscoelastic parameter mismatches demonstrate the robust performance of the controller.

  19. Model Reference Sliding Mode Control of Small Helicopter X.R.B based on Vision

    Directory of Open Access Journals (Sweden)

    Wei Wang

    2008-09-01

    Full Text Available This paper presents autonomous control for indoor small helicopter X.R.B. In case of natural disaster like earthquake, a MAV (Micro Air Vehicle which can fly autonomously will be very effective for surveying the site and environment in dangerous area or narrow space, where human cannot access safely. In addition, it will be helpful to prevent secondary disaster. This paper describes vision based autonomous hovering control, guidance control for X.R.B by model reference sliding mode control.

  20. Modelling and Controller Design of Electro-Pneumatic Actuator Based on PWM

    Directory of Open Access Journals (Sweden)

    Behrouz Najjari

    2012-07-01

    Full Text Available In this paper, a nonlinear model associated to the fast switching on-off solenoid valve and pneumatic cylinder was dynamically presented. Furthermore, an investigation into the electrical, magnetic, mechanical and fluid subsystems are made. Two common control policies to track valve position, a Proportional Integrator (PI based on Pulse Width Modulation (PWM and hysteresis controllers, are investigated. To control cylinder position, a Programmable Logic Controller (PLC on a simulated unit and an experimental setup regulated with AVR microcontroller are carried out. Experimental results show effective validation to the simulation results from PLC.

  1. Consistency maintenance for constraint in role-based access control model

    Institute of Scientific and Technical Information of China (English)

    韩伟力; 陈刚; 尹建伟; 董金祥

    2002-01-01

    Constraint is an important aspect of role-based access control and is sometimes argued to be the principal motivation for role-based access control (RBAC). But so far'few authors have discussed consistency maintenance for constraint in RBAC model. Based on researches of constraints among roles and types of inconsistency among constraints, this paper introduces correaponding formal rules, rulebased reasoning and corresponding methods to detect, avoid and resolve these inconsistencies. Finally,the paper introduces briefly the application of consistency maintenance in ZD-PDM, an enterprise-ori-ented product data management (PDM) system.

  2. Internal Model-Based Robust Tracking Control Design for the MEMS Electromagnetic Micromirror.

    Science.gov (United States)

    Tan, Jiazheng; Sun, Weijie; Yeow, John T W

    2017-05-26

    The micromirror based on micro-electro-mechanical systems (MEMS) technology is widely employed in different areas, such as scanning, imaging and optical switching. This paper studies the MEMS electromagnetic micromirror for scanning or imaging application. In these application scenarios, the micromirror is required to track the command sinusoidal signal, which can be converted to an output regulation problem theoretically. In this paper, based on the internal model principle, the output regulation problem is solved by designing a robust controller that is able to force the micromirror to track the command signal accurately. The proposed controller relies little on the accuracy of the model. Further, the proposed controller is implemented, and its effectiveness is examined by experiments. The experimental results demonstrate that the performance of the proposed controller is satisfying.

  3. On the comparison of stochastic model predictive control strategies applied to a hydrogen-based microgrid

    Science.gov (United States)

    Velarde, P.; Valverde, L.; Maestre, J. M.; Ocampo-Martinez, C.; Bordons, C.

    2017-03-01

    In this paper, a performance comparison among three well-known stochastic model predictive control approaches, namely, multi-scenario, tree-based, and chance-constrained model predictive control is presented. To this end, three predictive controllers have been designed and implemented in a real renewable-hydrogen-based microgrid. The experimental set-up includes a PEM electrolyzer, lead-acid batteries, and a PEM fuel cell as main equipment. The real experimental results show significant differences from the plant components, mainly in terms of use of energy, for each implemented technique. Effectiveness, performance, advantages, and disadvantages of these techniques are extensively discussed and analyzed to give some valid criteria when selecting an appropriate stochastic predictive controller.

  4. Linear Model-Based Predictive Control of the LHC 1.8 K Cryogenic Loop

    CERN Document Server

    Blanco-Viñuela, E; De Prada-Moraga, C

    1999-01-01

    The LHC accelerator will employ 1800 superconducting magnets (for guidance and focusing of the particle beams) in a pressurized superfluid helium bath at 1.9 K. This temperature is a severely constrained control parameter in order to avoid the transition from the superconducting to the normal state. Cryogenic processes are difficult to regulate due to their highly non-linear physical parameters (heat capacity, thermal conductance, etc.) and undesirable peculiarities like non self-regulating process, inverse response and variable dead time. To reduce the requirements on either temperature sensor or cryogenic system performance, various control strategies have been investigated on a reduced-scale LHC prototype built at CERN (String Test). Model Based Predictive Control (MBPC) is a regulation algorithm based on the explicit use of a process model to forecast the plant output over a certain prediction horizon. This predicted controlled variable is used in an on-line optimization procedure that minimizes an approp...

  5. Dynamic Modeling of Steam Condenser and Design of PI Controller Based on Grey Wolf Optimizer

    Directory of Open Access Journals (Sweden)

    Shu-Xia Li

    2015-01-01

    Full Text Available Shell-and-tube condenser is a heat exchanger for cooling steam with high temperature and pressure, which is one of the main kinds of heat exchange equipment in thermal, nuclear, and marine power plant. Based on the lumped parameter modeling method, the dynamic mathematical model of the simplified steam condenser is established. Then, the pressure PI control system of steam condenser based on the Matlab/Simulink simulation platform is designed. In order to obtain better performance, a new metaheuristic intelligent algorithm, grey wolf optimizer (GWO, is used to realize the fine-tuning of PI controller parameters. On the other hand, the Z-N engineering tuning method, genetic algorithm, and particle swarm algorithm are adopted for tuning PI controller parameters and compared with GWO algorithm. Simulation results show that GWO algorithm has better control performance than other four algorithms.

  6. Modeling and Optimal Control of a Class of Warfare Hybrid Dynamic Systems Based on Lanchester (n,1 Attrition Model

    Directory of Open Access Journals (Sweden)

    Xiangyong Chen

    2014-01-01

    hybrid dynamic systems is established based on Lanchester equation in a (n,1 battle, where a heterogeneous force of n different troop types faces a homogeneous force. This model can be characterized by the interaction of continuous-time models (governed by Lanchester equation, and discrete event systems (described by variable tactics. Furthermore, an expository discussion is presented on an optimal variable tactics control problem for warfare hybrid dynamic system. The optimal control strategies are designed based on dynamic programming and differential game theory. As an example of the consequences of this optimal control problem, we take the (2, 1 case and solve the optimal strategies in a (2, 1 case. Simulation results show the feasibility of warfare hybrid system model and the effectiveness of the optimal control strategies designed.

  7. Complex fluid network optimization and control integrative design based on nonlinear dynamic model

    International Nuclear Information System (INIS)

    Sui, Jinxue; Yang, Li; Hu, Yunan

    2016-01-01

    In view of distribution according to complex fluid network’s needs, this paper proposed one optimization computation method of the nonlinear programming mathematical model based on genetic algorithm. The simulation result shows that the overall energy consumption of the optimized fluid network has a decrease obviously. The control model of the fluid network is established based on nonlinear dynamics. We design the control law based on feedback linearization, take the optimal value by genetic algorithm as the simulation data, can also solve the branch resistance under the optimal value. These resistances can provide technical support and reference for fluid network design and construction, so can realize complex fluid network optimization and control integration design.

  8. Capability-based Access Control Delegation Model on the Federated IoT Network

    DEFF Research Database (Denmark)

    Anggorojati, Bayu; Mahalle, Parikshit N.; Prasad, Neeli R.

    2012-01-01

    Flexibility is an important property for general access control system and especially in the Internet of Things (IoT), which can be achieved by access or authority delegation. Delegation mechanisms in access control that have been studied until now have been intended mainly for a system that has...... no resource constraint, such as a web-based system, which is not very suitable for a highly pervasive system such as IoT. To this end, this paper presents an access delegation method with security considerations based on Capability-based Context Aware Access Control (CCAAC) model intended for federated...... machine-to-machine communication or IoT networks. The main idea of our proposed model is that the access delegation is realized by means of a capability propagation mechanism, and incorporating the context information as well as secure capability propagation under federated IoT environments. By using...

  9. Model-Based Evolution of a Fast Hybrid Fuzzy Adaptive Controller for a Pneumatic Muscle Actuator

    Directory of Open Access Journals (Sweden)

    Alexander Hošovský

    2012-07-01

    Full Text Available Pneumatic artificial muscle-based robotic systems usually necessitate the use of various nonlinear control techniques in order to improve their performance. Their robustness to parameter variation, which is generally difficult to predict, should also be tested. Here a fast hybrid adaptive control is proposed, where a conventional PD controller is placed into the feedforward branch and a fuzzy controller is placed into the adaptation branch. The fuzzy controller compensates for the actions of the PD controller under conditions of inertia moment variation. The fuzzy controller of Takagi-Sugeno type is evolved through a genetic algorithm using the dynamic model of a pneumatic muscle actuator. The results confirm the capability of the designed system to provide robust performance under the conditions of varying inertia.

  10. Adaptive control of Parkinson's state based on a nonlinear computational model with unknown parameters.

    Science.gov (United States)

    Su, Fei; Wang, Jiang; Deng, Bin; Wei, Xi-Le; Chen, Ying-Yuan; Liu, Chen; Li, Hui-Yan

    2015-02-01

    The objective here is to explore the use of adaptive input-output feedback linearization method to achieve an improved deep brain stimulation (DBS) algorithm for closed-loop control of Parkinson's state. The control law is based on a highly nonlinear computational model of Parkinson's disease (PD) with unknown parameters. The restoration of thalamic relay reliability is formulated as the desired outcome of the adaptive control methodology, and the DBS waveform is the control input. The control input is adjusted in real time according to estimates of unknown parameters as well as the feedback signal. Simulation results show that the proposed adaptive control algorithm succeeds in restoring the relay reliability of the thalamus, and at the same time achieves accurate estimation of unknown parameters. Our findings point to the potential value of adaptive control approach that could be used to regulate DBS waveform in more effective treatment of PD.

  11. Modeling of low frequency dynamics of a smart system and its state feedback based active control

    Science.gov (United States)

    Kant, Mohit; Parameswaran, Arun P.

    2018-01-01

    Major physical systems/structures suffer from unwanted vibrations. For efficient working of such systems, these vibrations have to be controlled. In this paper, mathematical modeling of an aluminum cantilever beam with bonded multiple piezoelectric patches which act as the disturbance generator, sensor as well as control actuator has been presented. This piezoelectric laminate cantilever beam is assumed to be vibrating in a single degree of freedom i.e. in the flexural mode only and the corresponding state space models have been derived analytically using the finite element technique. Dominant modes of flexural vibration are identified from the frequency response of the developed model of the system and finally a state feedback controller based on pole placement technique is designed to actively suppress the vibrations. Through numerous simulations as well as experimental validation, the effectiveness of the active controller in damping the vibrations at various excitation frequencies as well as frequency ranges along the flexural mode is established.

  12. A general U-block model-based design procedure for nonlinear polynomial control systems

    Science.gov (United States)

    Zhu, Q. M.; Zhao, D. Y.; Zhang, Jianhua

    2016-10-01

    The proposition of U-model concept (in terms of 'providing concise and applicable solutions for complex problems') and a corresponding basic U-control design algorithm was originated in the first author's PhD thesis. The term of U-model appeared (not rigorously defined) for the first time in the first author's other journal paper, which established a framework for using linear polynomial control system design approaches to design nonlinear polynomial control systems (in brief, linear polynomial approaches → nonlinear polynomial plants). This paper represents the next milestone work - using linear state-space approaches to design nonlinear polynomial control systems (in brief, linear state-space approaches → nonlinear polynomial plants). The overall aim of the study is to establish a framework, defined as the U-block model, which provides a generic prototype for using linear state-space-based approaches to design the control systems with smooth nonlinear plants/processes described by polynomial models. For analysing the feasibility and effectiveness, sliding mode control design approach is selected as an exemplary case study. Numerical simulation studies provide a user-friendly step-by-step procedure for the readers/users with interest in their ad hoc applications. In formality, this is the first paper to present the U-model-oriented control system design in a formal way and to study the associated properties and theorems. The previous publications, in the main, have been algorithm-based studies and simulation demonstrations. In some sense, this paper can be treated as a landmark for the U-model-based research from intuitive/heuristic stage to rigour/formal/comprehensive studies.

  13. Template model inspired leg force feedback based control can assist human walking.

    Science.gov (United States)

    Zhao, Guoping; Sharbafi, Maziar; Vlutters, Mark; van Asseldonk, Edwin; Seyfarth, Andre

    2017-07-01

    We present a novel control approach for assistive lower-extremity exoskeletons. In particular, we implement a virtual pivot point (VPP) template model inspired leg force feedback based controller on a lower-extremity powered exoskeleton (LOPES II) and demonstrate that it can effectively assist humans during walking. It has been shown that the VPP template model is capable of stabilizing the trunk and reproduce a human-like hip torque during the stance phase of walking. With leg force and joint angle feedback inspired by the VPP template model, our controller provides hip and knee torque assistance during the stance phase. A pilot experiment was conducted with four healthy subjects. Joint kinematics, leg muscle electromyography (EMG), and metabolic cost were measured during walking with and without assistance. Results show that, for 0.6 m/s walking, our controller can reduce leg muscle activations, especially for the medial gastrocnemius (about 16.0%), while hip and knee joint kinematics remain similar to the condition without the controller. Besides, the controller also reduces 10% of the net metabolic cost during walking. This paper demonstrates walking assistance benefits of the VPP template model for the first time. The support of human walking is achieved by a force feedback of leg force applied to the control of hip and knee joints. It can help us to provide a framework for investigating walking assistance control in the future.

  14. Correlation of a hypoxia based tumor control model with observed local control rates in nasopharyngeal carcinoma treated with chemoradiotherapy

    Energy Technology Data Exchange (ETDEWEB)

    Avanzo, Michele; Stancanello, Joseph; Franchin, Giovanni; Sartor, Giovanna; Jena, Rajesh; Drigo, Annalisa; Dassie, Andrea; Gigante, Marco; Capra, Elvira [Department of Medical Physics, Centro di Riferimento Oncologico, Aviano 33081 (Italy); Research and Clinical Collaborations, Siemens Healthcare, Erlangen 91052 (Germany); Department of Radiation Oncology, Centro di Riferimento Oncologico, Aviano 33081 (Italy); Department of Medical Physics, Centro di Riferimento Oncologico, Aviano 33081 (Italy); Oncology Centre, Cambridge University Hospitals NHS Foundation Trust, Cambridge CB2 0QQ (United Kingdom); Department of Medical Physics, Centro di Riferimento Oncologico, Aviano 33081 (Italy); Department of Radiation Oncology, Centro di Riferimento Oncologico, Aviano 33081 (Italy); Department of Medical Physics, Centro di Riferimento Oncologico, Aviano 33081 (Italy)

    2010-04-15

    Purpose: To extend the application of current radiation therapy (RT) based tumor control probability (TCP) models of nasopharyngeal carcinoma (NPC) to include the effects of hypoxia and chemoradiotherapy (CRT). Methods: A TCP model is described based on the linear-quadratic model modified to account for repopulation, chemotherapy, heterogeneity of dose to the tumor, and hypoxia. Sensitivity analysis was performed to determine which parameters exert the greatest influence on the uncertainty of modeled TCP. On the basis of the sensitivity analysis, the values of specific radiobiological parameters were set to nominal values reported in the literature for NPC or head and neck tumors. The remaining radiobiological parameters were determined by fitting TCP to clinical local control data from published randomized studies using both RT and CRT. Validation of the model was performed by comparison of estimated TCP and average overall local control rate (LCR) for 45 patients treated at the institution with conventional linear-accelerator-based or helical tomotherapy based intensity-modulated RT and neoadjuvant chemotherapy. Results: Sensitivity analysis demonstrates that the model is most sensitive to the radiosensitivity term {alpha} and the dose per fraction. The estimated values of {alpha} and OER from data fitting were 0.396 Gy{sup -1} and 1.417. The model estimate of TCP (average 90.9%, range 26.9%-99.2%) showed good correlation with the LCR (86.7%). Conclusions: The model implemented in this work provides clinicians with a useful tool to predict the success rate of treatment, optimize treatment plans, and compare the effects of multimodality therapy.

  15. Correlation of a hypoxia based tumor control model with observed local control rates in nasopharyngeal carcinoma treated with chemoradiotherapy

    International Nuclear Information System (INIS)

    Avanzo, Michele; Stancanello, Joseph; Franchin, Giovanni; Sartor, Giovanna; Jena, Rajesh; Drigo, Annalisa; Dassie, Andrea; Gigante, Marco; Capra, Elvira

    2010-01-01

    Purpose: To extend the application of current radiation therapy (RT) based tumor control probability (TCP) models of nasopharyngeal carcinoma (NPC) to include the effects of hypoxia and chemoradiotherapy (CRT). Methods: A TCP model is described based on the linear-quadratic model modified to account for repopulation, chemotherapy, heterogeneity of dose to the tumor, and hypoxia. Sensitivity analysis was performed to determine which parameters exert the greatest influence on the uncertainty of modeled TCP. On the basis of the sensitivity analysis, the values of specific radiobiological parameters were set to nominal values reported in the literature for NPC or head and neck tumors. The remaining radiobiological parameters were determined by fitting TCP to clinical local control data from published randomized studies using both RT and CRT. Validation of the model was performed by comparison of estimated TCP and average overall local control rate (LCR) for 45 patients treated at the institution with conventional linear-accelerator-based or helical tomotherapy based intensity-modulated RT and neoadjuvant chemotherapy. Results: Sensitivity analysis demonstrates that the model is most sensitive to the radiosensitivity term α and the dose per fraction. The estimated values of α and OER from data fitting were 0.396 Gy -1 and 1.417. The model estimate of TCP (average 90.9%, range 26.9%-99.2%) showed good correlation with the LCR (86.7%). Conclusions: The model implemented in this work provides clinicians with a useful tool to predict the success rate of treatment, optimize treatment plans, and compare the effects of multimodality therapy.

  16. A model of reward- and effort-based optimal decision making and motor control.

    Directory of Open Access Journals (Sweden)

    Lionel Rigoux

    Full Text Available Costs (e.g. energetic expenditure and benefits (e.g. food are central determinants of behavior. In ecology and economics, they are combined to form a utility function which is maximized to guide choices. This principle is widely used in neuroscience as a normative model of decision and action, but current versions of this model fail to consider how decisions are actually converted into actions (i.e. the formation of trajectories. Here, we describe an approach where decision making and motor control are optimal, iterative processes derived from the maximization of the discounted, weighted difference between expected rewards and foreseeable motor efforts. The model accounts for decision making in cost/benefit situations, and detailed characteristics of control and goal tracking in realistic motor tasks. As a normative construction, the model is relevant to address the neural bases and pathological aspects of decision making and motor control.

  17. An Effective Way to Control Numerical Instability of a Nonordinary State-Based Peridynamic Elastic Model

    Directory of Open Access Journals (Sweden)

    Xin Gu

    2017-01-01

    Full Text Available The constitutive modeling and numerical implementation of a nonordinary state-based peridynamic (NOSB-PD model corresponding to the classical elastic model are presented. Besides, the numerical instability problem of the NOSB-PD model is analyzed, and a penalty method involving the hourglass force is proposed to control the instabilities. Further, two benchmark problems, the static elastic deformation of a simple supported beam and the elastic wave propagation in a two-dimensional rod, are discussed with the present method. It proves that the penalty instability control method is effective in suppressing the displacement oscillations and improving the accuracy of calculated stress fields with a proper hourglass force coefficient, and the NOSB-PD approach with instability control can analyze the problems of structure deformation and elastic wave propagation well.

  18. Universal block diagram based modeling and simulation schemes for fractional-order control systems.

    Science.gov (United States)

    Bai, Lu; Xue, Dingyü

    2017-05-08

    Universal block diagram based schemes are proposed for modeling and simulating the fractional-order control systems in this paper. A fractional operator block in Simulink is designed to evaluate the fractional-order derivative and integral. Based on the block, the fractional-order control systems with zero initial conditions can be modeled conveniently. For modeling the system with nonzero initial conditions, the auxiliary signal is constructed in the compensation scheme. Since the compensation scheme is very complicated, therefore the integrator chain scheme is further proposed to simplify the modeling procedures. The accuracy and effectiveness of the schemes are assessed in the examples, the computation results testify the block diagram scheme is efficient for all Caputo fractional-order ordinary differential equations (FODEs) of any complexity, including the implicit Caputo FODEs. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

  19. Nonlinear Model Predictive Control Based on a Self-Organizing Recurrent Neural Network.

    Science.gov (United States)

    Han, Hong-Gui; Zhang, Lu; Hou, Ying; Qiao, Jun-Fei

    2016-02-01

    A nonlinear model predictive control (NMPC) scheme is developed in this paper based on a self-organizing recurrent radial basis function (SR-RBF) neural network, whose structure and parameters are adjusted concurrently in the training process. The proposed SR-RBF neural network is represented in a general nonlinear form for predicting the future dynamic behaviors of nonlinear systems. To improve the modeling accuracy, a spiking-based growing and pruning algorithm and an adaptive learning algorithm are developed to tune the structure and parameters of the SR-RBF neural network, respectively. Meanwhile, for the control problem, an improved gradient method is utilized for the solution of the optimization problem in NMPC. The stability of the resulting control system is proved based on the Lyapunov stability theory. Finally, the proposed SR-RBF neural network-based NMPC (SR-RBF-NMPC) is used to control the dissolved oxygen (DO) concentration in a wastewater treatment process (WWTP). Comparisons with other existing methods demonstrate that the SR-RBF-NMPC can achieve a considerably better model fitting for WWTP and a better control performance for DO concentration.

  20. Model-Based State Feedback Controller Design for a Turbocharged Diesel Engine with an EGR System

    Directory of Open Access Journals (Sweden)

    Tianpu Dong

    2015-05-01

    Full Text Available This paper describes a method for the control of transient exhaust gas recirculation (EGR systems. Firstly, a state space model of the air system is developed by simplifying a mean value model. The state space model is linearized by using linearization theory and validated by the GT-Power data with an operating point of the diesel engine. Secondly, a state feedback controller based on the intake oxygen mass fraction is designed for EGR control. Since direct measurement of the intake oxygen mass fraction is unavailable on the engine, the estimation method for intake oxygen mass fraction has been proposed in this paper. The control strategy is analyzed by using co-simulation with the Matlab/Simulink and GT-Powers software. Finally, the whole control system is experimentally validated against experimental data of a turbocharged diesel engine. The control effect of the state feedback controller compared with PID controller proved to be further verify the feasibility and advantages of the proposed state feedback controller.

  1. Hybrid Multi-Agent Control in Microgrids: Framework, Models and Implementations Based on IEC 61850

    Directory of Open Access Journals (Sweden)

    Xiaobo Dou

    2014-12-01

    Full Text Available Operation control is a vital and complex issue for microgrids. The objective of this paper is to explore the practical means of applying decentralized control by using a multi agent system in actual microgrids and devices. This paper presents a hierarchical control framework (HCF consisting of local reaction control (LRC level, local decision control (LDC level, horizontal cooperation control (HCC level and vertical cooperation control (VCC level to meet different control requirements of a microgrid. Then, a hybrid multi-agent control model (HAM is proposed to implement HCF, and the properties, functionalities and operating rules of HAM are described. Furthermore, the paper elaborates on the implementation of HAM based on the IEC 61850 Standard, and proposes some new implementation methods, such as extended information models of IEC 61850 with agent communication language and bidirectional interaction mechanism of generic object oriented substation event (GOOSE communication. A hardware design and software system are proposed and the results of simulation and laboratory tests verify the effectiveness of the proposed strategies, models and implementations.

  2. College Students Coping with Interpersonal Stress: Examining a Control-Based Model of Coping

    Science.gov (United States)

    Coiro, Mary Jo; Bettis, Alexandra H.; Compas, Bruce E.

    2017-01-01

    Objective: The ways that college students cope with stress, particularly interpersonal stress, may be a critical factor in determining which students are at risk for impairing mental health disorders. Using a control-based model of coping, the present study examined associations between interpersonal stress, coping strategies, and symptoms.…

  3. Model-based control of the temporal patterns of intracellular signaling in silico

    Science.gov (United States)

    Murakami, Yohei; Koyama, Masanori; Oba, Shigeyuki; Kuroda, Shinya; Ishii, Shin

    2017-01-01

    The functions of intracellular signal transduction systems are determined by the temporal behavior of intracellular molecules and their interactions. Of the many dynamical properties of the system, the relationship between the dynamics of upstream molecules and downstream molecules is particularly important. A useful tool in understanding this relationship is a methodology to control the dynamics of intracellular molecules with an extracellular stimulus. However, this is a difficult task because the relationship between the levels of upstream molecules and those of downstream molecules is often not only stochastic, but also time-inhomogeneous, nonlinear, and not one-to-one. In this paper, we present an easy-to-implement model-based control method that makes the target downstream molecule to trace a desired time course by changing the concentration of a controllable upstream molecule. Our method uses predictions from Monte Carlo simulations of the model to decide the strength of the stimulus, while using a particle-based approach to make inferences regarding unobservable states. We applied our method to in silico control problems of insulin-dependent AKT pathway model and EGF-dependent Akt pathway model with system noise. We show that our method can robustly control the dynamics of the intracellular molecules against unknown system noise of various strengths, even in the absence of complete knowledge of the true model of the target system. PMID:28275530

  4. Multiobjective Traffic Signal Control Model for Intersection Based on Dynamic Turning Movements Estimation

    Directory of Open Access Journals (Sweden)

    Pengpeng Jiao

    2014-01-01

    Full Text Available The real-time traffic signal control for intersection requires dynamic turning movements as the basic input data. It is impossible to detect dynamic turning movements directly through current traffic surveillance systems, but dynamic origin-destination (O-D estimation can obtain it. However, the combined models of dynamic O-D estimation and real-time traffic signal control are rare in the literature. A framework for the multiobjective traffic signal control model for intersection based on dynamic O-D estimation (MSC-DODE is presented. A state-space model using Kalman filtering is first formulated to estimate the dynamic turning movements; then a revised sequential Kalman filtering algorithm is designed to solve the model, and the root mean square error and mean percentage error are used to evaluate the accuracy of estimated dynamic turning proportions. Furthermore, a multiobjective traffic signal control model is put forward to achieve real-time signal control parameters and evaluation indices. Finally, based on practical survey data, the evaluation indices from MSC-DODE are compared with those from Webster method. The actual and estimated turning movements are further input into MSC-DODE, respectively, and results are also compared. Case studies show that results of MSC-DODE are better than those of Webster method and are very close to unavailable actual values.

  5. Economic policy optimization based on both one stochastic model and the parametric control theory

    Science.gov (United States)

    Ashimov, Abdykappar; Borovskiy, Yuriy; Onalbekov, Mukhit

    2016-06-01

    A nonlinear dynamic stochastic general equilibrium model with financial frictions is developed to describe two interacting national economies in the environment of the rest of the world. Parameters of nonlinear model are estimated based on its log-linearization by the Bayesian approach. The nonlinear model is verified by retroprognosis, estimation of stability indicators of mappings specified by the model, and estimation the degree of coincidence for results of internal and external shocks' effects on macroeconomic indicators on the basis of the estimated nonlinear model and its log-linearization. On the base of the nonlinear model, the parametric control problems of economic growth and volatility of macroeconomic indicators of Kazakhstan are formulated and solved for two exchange rate regimes (free floating and managed floating exchange rates)

  6. Means-End based Functional Modeling for Intelligent Control: Modeling and Experiments with an Industrial Heat Pump System

    DEFF Research Database (Denmark)

    Saleem, Arshad

    2007-01-01

    The purpose of this paper is to present a Multilevel Flow Model (MFM) of an industrial heat pump system and its use for diagnostic reasoning. MFM is functional modeling language supporting an explicit means-ends intelligent control strategy for large industrial process plants. The model is used...... in several diagnostic experiments analyzing different fault scenarios. The model and results of the experiments are explained and it is shown how MFM based intelligent modeling and automated reasoning can improve the fault diagnosis process significantly....

  7. A new adaptive control scheme based on the interacting multiple model (IMM) estimation

    International Nuclear Information System (INIS)

    Afshari, Hamed H.; Al-Ani, Dhafar; Habibi, Saeid

    2016-01-01

    In this paper, an Interacting multiple model (IMM) adaptive estimation approach is incorporated to design an optimal adaptive control law for stabilizing an Unmanned vehicle. Due to variations of the forward velocity of the Unmanned vehicle, its aerodynamic derivatives are constantly changing. In order to stabilize the unmanned vehicle and achieve the control objectives for in-flight conditions, one seeks for an adaptive control strategy that can adjust itself to varying flight conditions. In this context, a bank of linear models is used to describe the vehicle dynamics in different operating modes. Each operating mode represents a particular dynamic with a different forward velocity. These models are then used within an IMM filter containing a bank of Kalman filters (KF) in a parallel operating mechanism. To regulate and stabilize the vehicle, a Linear quadratic regulator (LQR) law is designed and implemented for each mode. The IMM structure determines the particular mode based on the stored models and in-flight input-output measurements. The LQR controller also provides a set of controllers; each corresponds to a particular flight mode and minimizes the tracking error. Finally, the ultimate control law is obtained as a weighted summation of all individual controllers whereas weights are obtained using mode probabilities of each operating mode.

  8. Droop Control with an Adjustable Complex Virtual Impedance Loop based on Cloud Model Theory

    DEFF Research Database (Denmark)

    Li, Yan; Shuai, Zhikang; Xu, Qinming

    2016-01-01

    Droop control framework with an adjustable virtual impedance loop is proposed in this paper, which is based on the cloud model theory. The proposed virtual impedance loop includes two terms: a negative virtual resistor and an adjustable virtual inductance. The negative virtual resistor term...... sometimes. The cloud model theory is applied to get online the changing line impedance value, which relies on the relevance of the reactive power responding the changing line impedance. The verification of the proposed control strategy is done according to the simulation in a low voltage microgrid in Matlab....

  9. TS Fuzzy Model-Based Controller Design for a Class of Nonlinear Systems Including Nonsmooth Functions

    DEFF Research Database (Denmark)

    Vafamand, Navid; Asemani, Mohammad Hassan; Khayatiyan, Alireza

    2018-01-01

    This paper proposes a novel robust controller design for a class of nonlinear systems including hard nonlinearity functions. The proposed approach is based on Takagi-Sugeno (TS) fuzzy modeling, nonquadratic Lyapunov function, and nonparallel distributed compensation scheme. In this paper, a novel...... criterion, new robust controller design conditions in terms of linear matrix inequalities are derived. Three practical case studies, electric power steering system, a helicopter model and servo-mechanical system, are presented to demonstrate the importance of such class of nonlinear systems comprising...

  10. Nonlinear model-based control of the Czochralski process III: Proper choice of manipulated variables and controller parameter scheduling

    Science.gov (United States)

    Neubert, M.; Winkler, J.

    2012-12-01

    This contribution continues an article series [1,2] about the nonlinear model-based control of the Czochralski crystal growth process. The key idea of the presented approach is to use a sophisticated combination of nonlinear model-based and conventional (linear) PI controllers for tracking of both, crystal radius and growth rate. Using heater power and pulling speed as manipulated variables several controller structures are possible. The present part tries to systematize the properties of the materials to be grown in order to get unambiguous decision criteria for a most profitable choice of the controller structure. For this purpose a material specific constant M called interface mobility and a more process specific constant S called system response number are introduced. While the first one summarizes important material properties like thermal conductivity and latent heat the latter one characterizes the process by evaluating the average axial thermal gradients at the phase boundary and the actual growth rate at which the crystal is grown. Furthermore these characteristic numbers are useful for establishing a scheduling strategy for the PI controller parameters in order to improve the controller performance. Finally, both numbers give a better understanding of the general thermal system dynamics of the Czochralski technique.

  11. Parameterized data-driven fuzzy model based optimal control of a semi-batch reactor.

    Science.gov (United States)

    Kamesh, Reddi; Rani, K Yamuna

    2016-09-01

    A parameterized data-driven fuzzy (PDDF) model structure is proposed for semi-batch processes, and its application for optimal control is illustrated. The orthonormally parameterized input trajectories, initial states and process parameters are the inputs to the model, which predicts the output trajectories in terms of Fourier coefficients. Fuzzy rules are formulated based on the signs of a linear data-driven model, while the defuzzification step incorporates a linear regression model to shift the domain from input to output domain. The fuzzy model is employed to formulate an optimal control problem for single rate as well as multi-rate systems. Simulation study on a multivariable semi-batch reactor system reveals that the proposed PDDF modeling approach is capable of capturing the nonlinear and time-varying behavior inherent in the semi-batch system fairly accurately, and the results of operating trajectory optimization using the proposed model are found to be comparable to the results obtained using the exact first principles model, and are also found to be comparable to or better than parameterized data-driven artificial neural network model based optimization results. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

  12. Validation and implementation of model based control strategies at an industrial wastewater treatment plant.

    Science.gov (United States)

    Demey, D; Vanderhaegen, B; Vanhooren, H; Liessens, J; Van Eyck, L; Hopkins, L; Vanrolleghem, P A

    2001-01-01

    In this paper, the practical implementation and validation of advanced control strategies, designed using model based techniques, at an industrial wastewater treatment plant is demonstrated. The plant under study is treating the wastewater of a large pharmaceutical production facility. The process characteristics of the wastewater treatment were quantified by means of tracer tests, intensive measurement campaigns and the use of on-line sensors. In parallel, a dynamical model of the complete wastewater plant was developed according to the specific kinetic characteristics of the sludge and the highly varying composition of the industrial wastewater. Based on real-time data and dynamic models, control strategies for the equalisation system, the polymer dosing and phosphorus addition were established. The control strategies are being integrated in the existing SCADA system combining traditional PLC technology with robust PC based control calculations. The use of intelligent control in wastewater treatment offers a wide spectrum of possibilities to upgrade existing plants, to increase the capacity of the plant and to eliminate peaks. This can result in a more stable and secure overall performance and, finally, in cost savings. The use of on-line sensors has a potential not only for monitoring concentrations, but also for manipulating flows and concentrations. This way the performance of the plant can be secured.

  13. D-FNN Based Modeling and BP Neural Network Decoupling Control of PVC Stripping Process

    Directory of Open Access Journals (Sweden)

    Shu-zhi Gao

    2014-01-01

    Full Text Available PVC stripping process is a kind of complicated industrial process with characteristics of highly nonlinear and time varying. Aiming at the problem of establishing the accurate mathematics model due to the multivariable coupling and big time delay, the dynamic fuzzy neural network (D-FNN is adopted to establish the PVC stripping process model based on the actual process operation datum. Then, the PVC stripping process is decoupled by the distributed neural network decoupling module to obtain two single-input-single-output (SISO subsystems (slurry flow to top tower temperature and steam flow to bottom tower temperature. Finally, the PID controller based on BP neural networks is used to control the decoupled PVC stripper system. Simulation results show the effectiveness of the proposed integrated intelligent control method.

  14. Parameters Tuning of Model Free Adaptive Control Based on Minimum Entropy

    Institute of Scientific and Technical Information of China (English)

    Chao Ji; Jing Wang; Liulin Cao; Qibing Jin

    2014-01-01

    Dynamic linearization based model free adaptive control(MFAC) algorithm has been widely used in practical systems, in which some parameters should be tuned before it is successfully applied to process industries. Considering the random noise existing in real processes, a parameter tuning method based on minimum entropy optimization is proposed,and the feature of entropy is used to accurately describe the system uncertainty. For cases of Gaussian stochastic noise and non-Gaussian stochastic noise, an entropy recursive optimization algorithm is derived based on approximate model or identified model. The extensive simulation results show the effectiveness of the minimum entropy optimization for the partial form dynamic linearization based MFAC. The parameters tuned by the minimum entropy optimization index shows stronger stability and more robustness than these tuned by other traditional index,such as integral of the squared error(ISE) or integral of timeweighted absolute error(ITAE), when the system stochastic noise exists.

  15. Visual Trajectory-Tracking Model-Based Control for Mobile Robots

    Directory of Open Access Journals (Sweden)

    Andrej Zdešar

    2013-09-01

    Full Text Available In this paper we present a visual-control algorithm for driving a mobile robot along the reference trajectory. The configuration of the system consists of a two-wheeled differentially driven mobile robot that is observed by an overhead camera, which can be placed at arbitrary, but reasonable, inclination with respect to the ground plane. The controller must be capable of generating appropriate tangential and angular control velocities for the trajectory-tracking problem, based on the information received about the robot position obtained in the image. To be able to track the position of the robot through a sequence of images in real-time, the robot is marked with an artificial marker that can be distinguishably recognized by the image recognition subsystem. Using the property of differential flatness, a dynamic feedback compensator can be designed for the system, thereby extending the system into a linear form. The presented control algorithm for reference tracking combines a feedforward and a feedback loop, the structure also known as a two DOF control scheme. The feedforward part should drive the system to the vicinity of the reference trajectory and the feedback part should eliminate any errors that occur due to noise and other disturbances etc. The feedforward control can never achieve accurate reference following, but this deficiency can be eliminated with the introduction of the feedback loop. The design of the model predictive control is based on the linear error model. The model predictive control is given in analytical form, so the computational burden is kept at a reasonable level for real-time implementation. The control algorithm requires that a reference trajectory is at least twice differentiable function. A suitable approach to design such a trajectory is by exploiting some useful properties of the Bernstein-Bézier parametric curves. The simulation experiments as well as real system experiments on a robot normally used in the

  16. Extended state observer based fuzzy model predictive control for ultra-supercritical boiler-turbine unit

    International Nuclear Information System (INIS)

    Zhang, Fan; Wu, Xiao; Shen, Jiong

    2017-01-01

    Highlights: • A novel ESOFMPC is proposed based on the combination of ESO and stable MPC. • The improved ESO can overcome unknown disturbances on any channel of MIMO system. • Nonlinearity and disturbance of boiler-turbine unit can be handled simultaneously. - Abstract: The regulation of ultra-supercritical (USC) boiler-turbine unit in large-scale power plants is vulnerable to various unknown disturbances, meanwhile, the internal nonlinearity makes it a challenging task for wide range load tracking. To overcome these two issues simultaneously, an extended state observer based fuzzy model predictive control is proposed for the USC boiler-turbine unit. Firstly, the fuzzy model of a 1000-MW coal-fired USC boiler-turbine unit is established through the nonlinearity analysis. Then a fuzzy stable model predictive controller is devised on the fuzzy model using output cost function for the purpose of wide range load tracking. An improved linear extended state observer, which can estimate plant behavior variations and unknown disturbances regardless of the direct feedthrough characteristic of the system, is synthesized with the predictive controller to enhance its disturbance rejection property. Closed-loop stability of the overall control system is guaranteed. Simulation results on a 1000-MW USC boiler-turbine unit model demonstrate the effectiveness of the proposed approach.

  17. Switching and optimizing control for coal flotation process based on a hybrid model

    Science.gov (United States)

    Dong, Zhiyong; Wang, Ranfeng; Fan, Minqiang; Fu, Xiang

    2017-01-01

    Flotation is an important part of coal preparation, and the flotation column is widely applied as efficient flotation equipment. This process is complex and affected by many factors, with the froth depth and reagent dosage being two of the most important and frequently manipulated variables. This paper proposes a new method of switching and optimizing control for the coal flotation process. A hybrid model is built and evaluated using industrial data. First, wavelet analysis and principal component analysis (PCA) are applied for signal pre-processing. Second, a control model for optimizing the set point of the froth depth is constructed based on fuzzy control, and a control model is designed to optimize the reagent dosages based on expert system. Finally, the least squares-support vector machine (LS-SVM) is used to identify the operating conditions of the flotation process and to select one of the two models (froth depth or reagent dosage) for subsequent operation according to the condition parameters. The hybrid model is developed and evaluated on an industrial coal flotation column and exhibits satisfactory performance. PMID:29040305

  18. Access Control Mechanism for IoT Environments Based on Modelling Communication Procedures as Resources.

    Science.gov (United States)

    Cruz-Piris, Luis; Rivera, Diego; Marsa-Maestre, Ivan; de la Hoz, Enrique; Velasco, Juan R

    2018-03-20

    Internet growth has generated new types of services where the use of sensors and actuators is especially remarkable. These services compose what is known as the Internet of Things (IoT). One of the biggest current challenges is obtaining a safe and easy access control scheme for the data managed in these services. We propose integrating IoT devices in an access control system designed for Web-based services by modelling certain IoT communication elements as resources. This would allow us to obtain a unified access control scheme between heterogeneous devices (IoT devices, Internet-based services, etc.). To achieve this, we have analysed the most relevant communication protocols for these kinds of environments and then we have proposed a methodology which allows the modelling of communication actions as resources. Then, we can protect these resources using access control mechanisms. The validation of our proposal has been carried out by selecting a communication protocol based on message exchange, specifically Message Queuing Telemetry Transport (MQTT). As an access control scheme, we have selected User-Managed Access (UMA), an existing Open Authorization (OAuth) 2.0 profile originally developed for the protection of Internet services. We have performed tests focused on validating the proposed solution in terms of the correctness of the access control system. Finally, we have evaluated the energy consumption overhead when using our proposal.

  19. Access Control Mechanism for IoT Environments Based on Modelling Communication Procedures as Resources

    Directory of Open Access Journals (Sweden)

    Luis Cruz-Piris

    2018-03-01

    Full Text Available Internet growth has generated new types of services where the use of sensors and actuators is especially remarkable. These services compose what is known as the Internet of Things (IoT. One of the biggest current challenges is obtaining a safe and easy access control scheme for the data managed in these services. We propose integrating IoT devices in an access control system designed for Web-based services by modelling certain IoT communication elements as resources. This would allow us to obtain a unified access control scheme between heterogeneous devices (IoT devices, Internet-based services, etc.. To achieve this, we have analysed the most relevant communication protocols for these kinds of environments and then we have proposed a methodology which allows the modelling of communication actions as resources. Then, we can protect these resources using access control mechanisms. The validation of our proposal has been carried out by selecting a communication protocol based on message exchange, specifically Message Queuing Telemetry Transport (MQTT. As an access control scheme, we have selected User-Managed Access (UMA, an existing Open Authorization (OAuth 2.0 profile originally developed for the protection of Internet services. We have performed tests focused on validating the proposed solution in terms of the correctness of the access control system. Finally, we have evaluated the energy consumption overhead when using our proposal.

  20. Access Control Mechanism for IoT Environments Based on Modelling Communication Procedures as Resources

    Science.gov (United States)

    2018-01-01

    Internet growth has generated new types of services where the use of sensors and actuators is especially remarkable. These services compose what is known as the Internet of Things (IoT). One of the biggest current challenges is obtaining a safe and easy access control scheme for the data managed in these services. We propose integrating IoT devices in an access control system designed for Web-based services by modelling certain IoT communication elements as resources. This would allow us to obtain a unified access control scheme between heterogeneous devices (IoT devices, Internet-based services, etc.). To achieve this, we have analysed the most relevant communication protocols for these kinds of environments and then we have proposed a methodology which allows the modelling of communication actions as resources. Then, we can protect these resources using access control mechanisms. The validation of our proposal has been carried out by selecting a communication protocol based on message exchange, specifically Message Queuing Telemetry Transport (MQTT). As an access control scheme, we have selected User-Managed Access (UMA), an existing Open Authorization (OAuth) 2.0 profile originally developed for the protection of Internet services. We have performed tests focused on validating the proposed solution in terms of the correctness of the access control system. Finally, we have evaluated the energy consumption overhead when using our proposal. PMID:29558406

  1. Model predictive control for a smart solar tank based on weather and consumption forecasts

    DEFF Research Database (Denmark)

    Halvgaard, Rasmus; Bacher, Peder; Perers, Bengt

    2012-01-01

    In this work the heat dynamics of a storage tank were modelled on the basis of data and maximum likelihood methods. The resulting grey-box model was used for Economic Model Predictive Control (MPC) of the energy in the tank. The control objective was to balance the energy from a solar collector...... and the heat consumption in a residential house. The storage tank provides heat in periods where there is low solar radiation and stores heat when there is surplus solar heat. The forecasts of consumption patterns were based on data obtained from meters in a group of single-family houses in Denmark. The tank...... can also be heated by electric heating elements if necessary, but the electricity costs of operating these heating elements should be minimized. Consequently, the heating elements should be used in periods with cheap electricity. It is proposed to integrate a price-sensitive control to enable...

  2. Petri Nets Based Modelling of Control Flow for Memory-Aid Interactive Programs in Telemedicine

    CERN Document Server

    Khoromskaia, V K

    2004-01-01

    Petri Nets (PN) based modelling of the control flow for the interactive memory assistance programs designed for personal pocket computers and having special requirements for robustness is considered. The proposed concept allows one to elaborate the programs which can give users a variety of possibilities for a day-time planning in the presence of environmental and time restrictions. First, a PN model for a known simple algorithm is constructed and analyzed using the corresponding state equations and incidence matrix. Then a PN graph for a complicated algorithm with overlapping actions and choice possibilities is designed, supplemented by an example of its analysis. Dynamic behaviour of this graph is tested by tracing of all possible paths of the flow of control using the PN simulator. It is shown that PN based modelling provides reliably predictable performance of interactive algorithms with branched structures and concurrency requirements.

  3. Comparative Study of SSVEP- and P300-Based Models for the Telepresence Control of Humanoid Robots.

    Directory of Open Access Journals (Sweden)

    Jing Zhao

    Full Text Available In this paper, we evaluate the control performance of SSVEP (steady-state visual evoked potential- and P300-based models using Cerebot-a mind-controlled humanoid robot platform. Seven subjects with diverse experience participated in experiments concerning the open-loop and closed-loop control of a humanoid robot via brain signals. The visual stimuli of both the SSVEP- and P300- based models were implemented on a LCD computer monitor with a refresh frequency of 60 Hz. Considering the operation safety, we set the classification accuracy of a model over 90.0% as the most important mandatory for the telepresence control of the humanoid robot. The open-loop experiments demonstrated that the SSVEP model with at most four stimulus targets achieved the average accurate rate about 90%, whereas the P300 model with the six or more stimulus targets under five repetitions per trial was able to achieve the accurate rates over 90.0%. Therefore, the four SSVEP stimuli were used to control four types of robot behavior; while the six P300 stimuli were chosen to control six types of robot behavior. Both of the 4-class SSVEP and 6-class P300 models achieved the average success rates of 90.3% and 91.3%, the average response times of 3.65 s and 6.6 s, and the average information transfer rates (ITR of 24.7 bits/min 18.8 bits/min, respectively. The closed-loop experiments addressed the telepresence control of the robot; the objective was to cause the robot to walk along a white lane marked in an office environment using live video feedback. Comparative studies reveal that the SSVEP model yielded faster response to the subject's mental activity with less reliance on channel selection, whereas the P300 model was found to be suitable for more classifiable targets and required less training. To conclude, we discuss the existing SSVEP and P300 models for the control of humanoid robots, including the models proposed in this paper.

  4. Model predictive control of an air suspension system with damping multi-mode switching damper based on hybrid model

    Science.gov (United States)

    Sun, Xiaoqiang; Yuan, Chaochun; Cai, Yingfeng; Wang, Shaohua; Chen, Long

    2017-09-01

    This paper presents the hybrid modeling and the model predictive control of an air suspension system with damping multi-mode switching damper. Unlike traditional damper with continuously adjustable damping, in this study, a new damper with four discrete damping modes is applied to vehicle semi-active air suspension. The new damper can achieve different damping modes by just controlling the on-off statuses of two solenoid valves, which makes its damping adjustment more efficient and more reliable. However, since the damping mode switching induces different modes of operation, the air suspension system with the new damper poses challenging hybrid control problem. To model both the continuous/discrete dynamics and the switching between different damping modes, the framework of mixed logical dynamical (MLD) systems is used to establish the system hybrid model. Based on the resulting hybrid dynamical model, the system control problem is recast as a model predictive control (MPC) problem, which allows us to optimize the switching sequences of the damping modes by taking into account the suspension performance requirements. Numerical simulations results demonstrate the efficacy of the proposed control method finally.

  5. Modeling and control of PEMFC based on least squares support vector machines

    International Nuclear Information System (INIS)

    Li Xi; Cao Guangyi; Zhu Xinjian

    2006-01-01

    The proton exchange membrane fuel cell (PEMFC) is one of the most important power supplies. The operating temperature of the stack is an important controlled variable, which impacts the performance of the PEMFC. In order to improve the generating performance of the PEMFC, prolong its life and guarantee safety, credibility and low cost of the PEMFC system, it must be controlled efficiently. A nonlinear predictive control algorithm based on a least squares support vector machine (LS-SVM) model is presented for a family of complex systems with severe nonlinearity, such as the PEMFC, in this paper. The nonlinear off line model of the PEMFC is built by a LS-SVM model with radial basis function (RBF) kernel so as to implement nonlinear predictive control of the plant. During PEMFC operation, the off line model is linearized at each sampling instant, and the generalized predictive control (GPC) algorithm is applied to the predictive control of the plant. Experimental results demonstrate the effectiveness and advantages of this approach

  6. Model-based active control of a continuous structure subjected to moving loads

    Science.gov (United States)

    Stancioiu, D.; Ouyang, H.

    2016-09-01

    Modelling of a structure is an important preliminary step of structural control. The main objectives of the modelling, which are almost always antagonistic are accuracy and simplicity of the model. The first part of this study focuses on the experimental and theoretical modelling of a structure subjected to the action of one or two decelerating moving carriages modelled as masses. The aim of this part is to obtain a simple but accurate model which will include not only the structure-moving load interaction but also the actuators dynamics. A small scale rig is designed to represent a four-span continuous metallic bridge structure with miniature guiding rails. A series of tests are run subjecting the structure to the action of one or two minicarriages with different loads that were launched along the structure at different initial speeds. The second part is dedicated to model based control design where a feedback controller is designed and tested against the validated model. The study shows that a positive position feedback is able to improve system dynamics but also shows some of the limitations of state- space methods for this type of system.

  7. Rectifier Current Control for an LLC Resonant Converter Based on a Simplified Linearized Model

    Directory of Open Access Journals (Sweden)

    Zhijian Fang

    2018-03-01

    Full Text Available In this paper, a rectifier current control for an LLC resonant converter is proposed, based on a simplified, two-order, linearized model that adds a rectifier current feedback inner loop to improve dynamic performance. Compared to the traditional large-signal model with seven resonant states, this paper utilizes a rectifier current state to represent the characteristics of the resonant states, simplifying the LLC resonant model from seven orders to two orders. Then, the rectifier current feedback inner loop is proposed to increase the control system damping, improving dynamic performance. The modeling and design methodology for the LLC resonant converter are also presented in this paper. A frequency analysis is conducted to verify the accuracy of the simplified model. Finally, a 200 W LLC resonant converter prototype is built to verify the effectiveness of the proposed control strategy. Compared to a traditional single-loop controller, the settling time and voltage droop were reduced from 10.8 ms to 8.6 ms and from 6.8 V to 4.8 V, respectively, using the proposed control strategy.

  8. Modeling and the analysis of control logic for a digital PWM controller based on a nano electronic single electron transistor

    Directory of Open Access Journals (Sweden)

    Rathnakannan Kailasam

    2008-01-01

    Full Text Available This paper describes the modelling and the analysis of control logic for a Nano-Device- based PWM controller. A comprehensive simple SPICE schematic model for Single Electron transistor has been proposed. The operation of basic Single Electron Transistor logic gates and SET flip flops were successfully designed and their performances analyzed. The proposed design for realizing the logic gates and flip-flops is used in constructing the PWM controller utilized for switching the buck converter circuit. The output of the converter circuit is compared with reference voltage, and when the error voltage and the reference are matched the latch is reset so as to generate the PWM signal. Due to the simplicity and accuracy of the compact model, the simulation time and speed are much faster, which makes it potentially applicable in large-scale circuit simulation. This study confirms that the SET-based PWM controller is small in size, consumes ultra low power and operates at high speeds without compromising any performance. In addition these devices are capable of measuring charges of extremely high sensitivity.

  9. Method for mapping population-based case-control studies: an application using generalized additive models

    Directory of Open Access Journals (Sweden)

    Aschengrau Ann

    2006-06-01

    Full Text Available Abstract Background Mapping spatial distributions of disease occurrence and risk can serve as a useful tool for identifying exposures of public health concern. Disease registry data are often mapped by town or county of diagnosis and contain limited data on covariates. These maps often possess poor spatial resolution, the potential for spatial confounding, and the inability to consider latency. Population-based case-control studies can provide detailed information on residential history and covariates. Results Generalized additive models (GAMs provide a useful framework for mapping point-based epidemiologic data. Smoothing on location while controlling for covariates produces adjusted maps. We generate maps of odds ratios using the entire study area as a reference. We smooth using a locally weighted regression smoother (loess, a method that combines the advantages of nearest neighbor and kernel methods. We choose an optimal degree of smoothing by minimizing Akaike's Information Criterion. We use a deviance-based test to assess the overall importance of location in the model and pointwise permutation tests to locate regions of significantly increased or decreased risk. The method is illustrated with synthetic data and data from a population-based case-control study, using S-Plus and ArcView software. Conclusion Our goal is to develop practical methods for mapping population-based case-control and cohort studies. The method described here performs well for our synthetic data, reproducing important features of the data and adequately controlling the covariate. When applied to the population-based case-control data set, the method suggests spatial confounding and identifies statistically significant areas of increased and decreased odds ratios.

  10. Optimization and Control of Agent-Based Models in Biology: A Perspective.

    Science.gov (United States)

    An, G; Fitzpatrick, B G; Christley, S; Federico, P; Kanarek, A; Neilan, R Miller; Oremland, M; Salinas, R; Laubenbacher, R; Lenhart, S

    2017-01-01

    Agent-based models (ABMs) have become an increasingly important mode of inquiry for the life sciences. They are particularly valuable for systems that are not understood well enough to build an equation-based model. These advantages, however, are counterbalanced by the difficulty of analyzing and using ABMs, due to the lack of the type of mathematical tools available for more traditional models, which leaves simulation as the primary approach. As models become large, simulation becomes challenging. This paper proposes a novel approach to two mathematical aspects of ABMs, optimization and control, and it presents a few first steps outlining how one might carry out this approach. Rather than viewing the ABM as a model, it is to be viewed as a surrogate for the actual system. For a given optimization or control problem (which may change over time), the surrogate system is modeled instead, using data from the ABM and a modeling framework for which ready-made mathematical tools exist, such as differential equations, or for which control strategies can explored more easily. Once the optimization problem is solved for the model of the surrogate, it is then lifted to the surrogate and tested. The final step is to lift the optimization solution from the surrogate system to the actual system. This program is illustrated with published work, using two relatively simple ABMs as a demonstration, Sugarscape and a consumer-resource ABM. Specific techniques discussed include dimension reduction and approximation of an ABM by difference equations as well systems of PDEs, related to certain specific control objectives. This demonstration illustrates the very challenging mathematical problems that need to be solved before this approach can be realistically applied to complex and large ABMs, current and future. The paper outlines a research program to address them.

  11. Integration of model-based control systems with artificial intelligence and workstations

    International Nuclear Information System (INIS)

    Lee, M.; Clearwater, S.

    1987-01-01

    Experience with model based accelerator control started at SPEAR. Since that SPEAR. Since that time nearly all accelerator beam lines have been controlled using model-based application programs, for example, PEP and SLC at SLAC. In order to take advantage of state-of-the-art hardware and software technology, the design and implementation of the accelerator control programs have undergone radical changes with time. Consequently, SPEAR, PEP, and SLC all use different control programs. Since many of these application programs are imbedded deep into the control system, they had to be rewritten each time. Each time this rewriting has occurred a great deal of time and effort has been spent on training physicists and programmers to do the job. Now, these application programs have been developed for a fourth time. This time, however, the programs being developed are generic so that they will not have to be done again. An integrated system called GOLD (Generic Orbit ampersand Lattice Debugger) has been developed for debugging and correcting trajectory errors in accelerator lattices. The system consists of a lattice modeling program (COMFORT), a beam simulator (PLUS), a graphical workstation environment (micro-VAX) and an expert system (ABLE). This paper will describe some of the features and applications of our integrated system with emphasis on the automation offered by expert systems. 5 refs., 4 figs

  12. GOLD: Integration of model-based control systems with artificial intelligence and workstations

    International Nuclear Information System (INIS)

    Lee, M.; Clearwater, S.

    1987-08-01

    Our experience with model-based accelerator control started at SPEAR. Since that time nearly all accelerator beamlines have been controlled using model-based application programs, for example, PEP and SLC at SLAC. In order to take advantage of state-of-the-art hardware and software technology, the design and implementation of the accelerator control programs have undergone radical changes with time. Consequently, SPEAR, PEP and SLC all use different control programs. Since many of these application programs are embedded deep into the control system, they had to be rewritten each time. Each time this rewriting has occurred a great deal of time and effort has been spent on training physicists and programmers to do the job. Now, we have developed an integrated system called GOLD (Genetic Orbit and Lattice Debugger) for debugging and correcting trajectory errors in accelerator lattices. The system consists of a lattice modeling program (COMFORT), a beam simulator (PLUS), a graphical workstation environment (micro-VAX) and an expert system (ABLE). This paper will describe some of the features and applications of our integrated system with emphasis on the automation offered by expert systems. 5 refs

  13. GOLD: Integration of model-based control systems with artificial intelligence and workstations

    International Nuclear Information System (INIS)

    Lee, M.; Clearwater, S.

    1987-08-01

    Our experience with model based accelerator control started at SPEAR. Since that time nearly all accelerator beam lines have been controlled using model-based application programs, for example, PEP and SLC at SLAC. In order to take advantage of state-of-the-art hardware and software technology, the design and implementation of the accelerator control programs have undergone radical change with time. Consequently, SPEAR, PEP, and SLC all use different control programs. Since many of these application programs are imbedded deep into the control system, they had to be rewritten each time. Each time this rewriting has occurred a great deal of time and effort has been spent on training physicists and programmers to do the job. Now, we have developed these application programs for a fourth time. This time, however, the programs we are developing are generic so that we will not have to do it again. We have developed an integrated system called GOLD (Generic Orbit and Lattice Debugger) for debugging and correcting trajectory errors in accelerator lattices. The system consists of a lattice modeling program (COMFORT), a beam simulator (PLUS), a graphical workstation environment (micro-VAX) and an expert system (ABLE). This paper will describe some of the features and applications of our integrated system with emphasis on the automation offered by expert systems. 5 refs

  14. Non-fragile observer-based output feedback control for polytopic uncertain system under distributed model predictive control approach

    Science.gov (United States)

    Zhu, Kaiqun; Song, Yan; Zhang, Sunjie; Zhong, Zhaozhun

    2017-07-01

    In this paper, a non-fragile observer-based output feedback control problem for the polytopic uncertain system under distributed model predictive control (MPC) approach is discussed. By decomposing the global system into some subsystems, the computation complexity is reduced, so it follows that the online designing time can be saved.Moreover, an observer-based output feedback control algorithm is proposed in the framework of distributed MPC to deal with the difficulties in obtaining the states measurements. In this way, the presented observer-based output-feedback MPC strategy is more flexible and applicable in practice than the traditional state-feedback one. What is more, the non-fragility of the controller has been taken into consideration in favour of increasing the robustness of the polytopic uncertain system. After that, a sufficient stability criterion is presented by using Lyapunov-like functional approach, meanwhile, the corresponding control law and the upper bound of the quadratic cost function are derived by solving an optimisation subject to convex constraints. Finally, some simulation examples are employed to show the effectiveness of the method.

  15. Active Power Optimal Control of Wind Turbines with Doubly Fed Inductive Generators Based on Model Predictive Control

    Directory of Open Access Journals (Sweden)

    Guo Jiuwang

    2015-01-01

    Full Text Available Because of the randomness and fluctuation of wind energy, as well as the impact of strongly nonlinear characteristic of variable speed constant frequency (VSCF wind power generation system with doubly fed induction generators (DFIG, traditional active power control strategies are difficult to achieve high precision control and the output power of wind turbines is more fluctuated. In order to improve the quality of output electric energy of doubly fed wind turbines, on the basis of analyzing the operating principles and dynamic characteristics of doubly fed wind turbines, this paper proposes a new active power optimal control method of doubly fed wind turbines based on predictive control theory. This method uses state space model of wind turbines, based on the prediction of the future state of wind turbines, moves horizon optimization, and meanwhile, gets the control signals of pitch angle and generator torque. Simulation results show that the proposed control strategies can guarantee the utilization efficiency for wind energy. Simultaneously, they can improve operation stability of wind turbines and the quality of electric energy.

  16. A model-based approach to predict muscle synergies using optimization: application to feedback control

    Directory of Open Access Journals (Sweden)

    Reza eSharif Razavian

    2015-10-01

    Full Text Available This paper presents a new model-based method to define muscle synergies. Unlike the conventional factorization approach, which extracts synergies from electromyographic data, the proposed method employs a biomechanical model and formally defines the synergies as the solution of an optimal control problem. As a result, the number of required synergies is directly related to the dimensions of the operational space. The estimated synergies are posture-dependent, which correlate well with the results of standard factorization methods. Two examples are used to showcase this method: a two-dimensional forearm model, and a three-dimensional driver arm model. It has been shown here that the synergies need to be task-specific (i.e. they are defined for the specific operational spaces: the elbow angle and the steering wheel angle in the two systems. This functional definition of synergies results in a low-dimensional control space, in which every force in the operational space is accurately created by a unique combination of synergies. As such, there is no need for extra criteria (e.g., minimizing effort in the process of motion control. This approach is motivated by the need for fast and bio-plausible feedback control of musculoskeletal systems, and can have important implications in engineering, motor control, and biomechanics.

  17. A model-based approach to predict muscle synergies using optimization: application to feedback control.

    Science.gov (United States)

    Sharif Razavian, Reza; Mehrabi, Naser; McPhee, John

    2015-01-01

    This paper presents a new model-based method to define muscle synergies. Unlike the conventional factorization approach, which extracts synergies from electromyographic data, the proposed method employs a biomechanical model and formally defines the synergies as the solution of an optimal control problem. As a result, the number of required synergies is directly related to the dimensions of the operational space. The estimated synergies are posture-dependent, which correlate well with the results of standard factorization methods. Two examples are used to showcase this method: a two-dimensional forearm model, and a three-dimensional driver arm model. It has been shown here that the synergies need to be task-specific (i.e., they are defined for the specific operational spaces: the elbow angle and the steering wheel angle in the two systems). This functional definition of synergies results in a low-dimensional control space, in which every force in the operational space is accurately created by a unique combination of synergies. As such, there is no need for extra criteria (e.g., minimizing effort) in the process of motion control. This approach is motivated by the need for fast and bio-plausible feedback control of musculoskeletal systems, and can have important implications in engineering, motor control, and biomechanics.

  18. A Modified Multifrequency Passivity-Based Control for Shunt Active Power Filter With Model-Parameter-Adaptive Capability

    DEFF Research Database (Denmark)

    Mu, Xiaobin; Wang, Jiuhe; Wu, Weimin

    2018-01-01

    The passivity-based control (PBC) has a better control performance using an accurate mathematical model of the control object. It can offer an alternative tracking control scheme for the shunt active power filter (SAPF). However, the conventional PBC-based SAPF cannot achieve zero steady...

  19. Robust control of chaos in Chua's circuit based on internal model principle

    International Nuclear Information System (INIS)

    Lee, Keum W.; Singh, Sahjendra N.

    2007-01-01

    The paper treats the question of robust control of chaos in Chua's circuit based on the internal model principle. The Chua's diode has polynomial non-linearity and it is assumed that the parameters of the circuit are not known. A robust control law for the asymptotic regulation of the output (node voltage) along constant and sinusoidal reference trajectories is derived. For the derivation of the control law, the non-linear regulator equations are solved to obtain a manifold in the state space on which the output error is zero and an internal model of the k-fold exosystem (k = 3 here) is constructed. Then a feedback control law using the optimal control theory or pole placement technique for the stabilization of the augmented system including the Chua's circuit and the internal model is derived. In the closed-loop system, robust output node voltage trajectory tracking of sinusoidal and constant reference trajectories are accomplished and in the steady state, the remaining state variables converge to periodic and constant trajectories, respectively. Simulation results are presented which show that in the closed-loop system, asymptotic trajectory control, disturbance rejection and suppression of chaotic motion in spite of uncertainties in the system are accomplished

  20. Bilinear Approximate Model-Based Robust Lyapunov Control for Parabolic Distributed Collectors

    KAUST Repository

    Elmetennani, Shahrazed

    2016-11-09

    This brief addresses the control problem of distributed parabolic solar collectors in order to maintain the field outlet temperature around a desired level. The objective is to design an efficient controller to force the outlet fluid temperature to track a set reference despite the unpredictable varying working conditions. In this brief, a bilinear model-based robust Lyapunov control is proposed to achieve the control objectives with robustness to the environmental changes. The bilinear model is a reduced order approximate representation of the solar collector, which is derived from the hyperbolic distributed equation describing the heat transport dynamics by means of a dynamical Gaussian interpolation. Using the bilinear approximate model, a robust control strategy is designed applying Lyapunov stability theory combined with a phenomenological representation of the system in order to stabilize the tracking error. On the basis of the error analysis, simulation results show good performance of the proposed controller, in terms of tracking accuracy and convergence time, with limited measurement even under unfavorable working conditions. Furthermore, the presented work is of interest for a large category of dynamical systems knowing that the solar collector is representative of physical systems involving transport phenomena constrained by unknown external disturbances.

  1. Robust control of chaos in Chua's circuit based on internal model principle

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Keum W. [Department of Electrical and Computer Engineering, University of Nevada Las Vegas, 4505 Maryland Parkway, Las Vegas, NV, 89154-4026 (United States); Singh, Sahjendra N. [Department of Electrical and Computer Engineering, University of Nevada Las Vegas, 4505 Maryland Parkway, Las Vegas, NV, 89154-4026 (United States)]. E-mail: sahaj@ee.unlv.edu

    2007-03-15

    The paper treats the question of robust control of chaos in Chua's circuit based on the internal model principle. The Chua's diode has polynomial non-linearity and it is assumed that the parameters of the circuit are not known. A robust control law for the asymptotic regulation of the output (node voltage) along constant and sinusoidal reference trajectories is derived. For the derivation of the control law, the non-linear regulator equations are solved to obtain a manifold in the state space on which the output error is zero and an internal model of the k-fold exosystem (k = 3 here) is constructed. Then a feedback control law using the optimal control theory or pole placement technique for the stabilization of the augmented system including the Chua's circuit and the internal model is derived. In the closed-loop system, robust output node voltage trajectory tracking of sinusoidal and constant reference trajectories are accomplished and in the steady state, the remaining state variables converge to periodic and constant trajectories, respectively. Simulation results are presented which show that in the closed-loop system, asymptotic trajectory control, disturbance rejection and suppression of chaotic motion in spite of uncertainties in the system are accomplished.

  2. Model-based power control strategy development of a fuel cell hybrid vehicle

    Energy Technology Data Exchange (ETDEWEB)

    Haitao, Yun [School of Automobile and Traffic, Qingdao Technological University, Qingdao Shandong 266033 (China); School of Automobile, Tongji University, ShangHai 201804 (China); Yulan, Zhao [School of Automobile and Traffic, Qingdao Technological University, Qingdao Shandong 266033 (China); Zechang, Sun; Gang, Wan [School of Automobile, Tongji University, ShangHai 201804 (China)

    2008-06-01

    An integrated procedure for math modeling and power control strategy design for a fuel cell hybrid vehicle (FCHV) is presented in this paper. Dynamic math model of the powertrain is constructed firstly, which includes four modules: fuel cell engine, DC/DC inverter, motor-driver, and power battery. Based on the mathematic model, a power control principle is designed, which uses full-states closed-loop feedback algorithm. To implement full-states feedback, a Luenberger state observer is designed to estimate open circuit voltage (OCV) of the battery, which make the control principle not sensitive to the battery SOC (state of charge) estimated error. Full-states feedback controller is then designed through analyzing step responding of the powertrain and test data. At last of the paper, the results of simulation and field test are illustrated. The results show that the power control strategy designed takes into account the performance and economy characteristics of components of the FCHV powertrain and achieves the control object excellently. (author)

  3. Reliability–based economic model predictive control for generalised flow–based networks including actuators’ health–aware capabilities

    Directory of Open Access Journals (Sweden)

    Grosso Juan M.

    2016-09-01

    Full Text Available This paper proposes a reliability-based economic model predictive control (MPC strategy for the management of generalised flow-based networks, integrating some ideas on network service reliability, dynamic safety stock planning, and degradation of equipment health. The proposed strategy is based on a single-layer economic optimisation problem with dynamic constraints, which includes two enhancements with respect to existing approaches. The first enhancement considers chance-constraint programming to compute an optimal inventory replenishment policy based on a desired risk acceptability level, leading to dynamical allocation of safety stocks in flow-based networks to satisfy non-stationary flow demands. The second enhancement computes a smart distribution of the control effort and maximises actuators’ availability by estimating their degradation and reliability. The proposed approach is illustrated with an application of water transport networks using the Barcelona network as the case study considered.

  4. Space vector-based modeling and control of a modular multilevel converter in HVDC applications

    DEFF Research Database (Denmark)

    Bonavoglia, M.; Casadei, G.; Zarri, L.

    2013-01-01

    Modular multilevel converter (MMC) is an emerging multilevel topology for high-voltage applications that has been developed in recent years. In this paper, the modeling and the control of MMCs are restated in terms of space vectors, which may allow a deeper understanding of the converter behavior....... As a result, a control scheme for three-phase MMCs based on the previous theoretical analysis is presented. Numerical simulations are used to test its feasibility.......Modular multilevel converter (MMC) is an emerging multilevel topology for high-voltage applications that has been developed in recent years. In this paper, the modeling and the control of MMCs are restated in terms of space vectors, which may allow a deeper understanding of the converter behavior...

  5. Research on torsional vibration modelling and control of printing cylinder based on particle swarm optimization

    Science.gov (United States)

    Wang, Y. M.; Xu, W. C.; Wu, S. Q.; Chai, C. W.; Liu, X.; Wang, S. H.

    2018-03-01

    The torsional oscillation is the dominant vibration form for the impression cylinder of printing machine (printing cylinder for short), directly restricting the printing speed up and reducing the quality of the prints. In order to reduce torsional vibration, the active control method for the printing cylinder is obtained. Taking the excitation force and moment from the cylinder gap and gripper teeth open & closing cam mechanism as variable parameters, authors establish the dynamic mathematical model of torsional vibration for the printing cylinder. The torsional active control method is based on Particle Swarm Optimization(PSO) algorithm to optimize input parameters for the serve motor. Furthermore, the input torque of the printing cylinder is optimized, and then compared with the numerical simulation results. The conclusions are that torsional vibration active control based on PSO is an availability method to the torsional vibration of printing cylinder.

  6. An Improved Car-Following Model in Vehicle Networking Based on Network Control

    Directory of Open Access Journals (Sweden)

    D. Y. Kong

    2014-01-01

    Full Text Available Vehicle networking is a system to realize information interoperability between vehicles and people, vehicles and roads, vehicles and vehicles, and cars and transport facilities, through the network information exchange, in order to achieve the effective monitoring of the vehicle and traffic flow. Realizing information interoperability between vehicles and vehicles, which can affect the traffic flow, is an important application of network control system (NCS. In this paper, a car-following model using vehicle networking theory is established, based on network control principle. The car-following model, which is an improvement of the traditional traffic model, describes the traffic in vehicle networking condition. The impact that vehicle networking has on the traffic flow is quantitatively assessed in a particular scene of one-way, no lane changing highway. The examples show that the capacity of the road is effectively enhanced by using vehicle networking.

  7. Parametric Study of Synthetic-Jet-Based Flow Control on a Vertical Tail Model

    Science.gov (United States)

    Monastero, Marianne; Lindstrom, Annika; Beyar, Michael; Amitay, Michael

    2015-11-01

    Separation control over the rudder of the vertical tail of a commercial airplane using synthetic-jet-based flow control can lead to a reduction in tail size, with an associated decrease in drag and increase in fuel savings. A parametric, experimental study was undertaken using an array of finite span synthetic jets to investigate the sensitivity of the enhanced vertical tail side force to jet parameters, such as jet spanwise spacing and jet momentum coefficient. A generic wind tunnel model was designed and fabricated to fundamentally study the effects of the jet parameters at varying rudder deflection and model sideslip angles. Wind tunnel results obtained from pressure measurements and tuft flow visualization in the Rensselaer Polytechnic Subsonic Wind Tunnel show a decrease in separation severity and increase in model performance in comparison to the baseline, non-actuated case. The sensitivity to various parameters will be presented.

  8. Adaptive control of servo system based on LuGre model

    Science.gov (United States)

    Jin, Wang; Niancong, Liu; Jianlong, Chen; Weitao, Geng

    2018-03-01

    This paper established a mechanical model of feed system based on LuGre model. In order to solve the influence of nonlinear factors on the system running stability, a nonlinear single observer is designed to estimate the parameter z in the LuGre model and an adaptive friction compensation controller is designed. Simulink simulation results show that the control method can effectively suppress the adverse effects of friction and external disturbances. The simulation show that the adaptive parameter kz is between 0.11-0.13, and the value of gamma1 is between 1.9-2.1. Position tracking error reaches level 10-3 and is stabilized near 0 values within 0.3 seconds, the compensation method has better tracking accuracy and robustness.

  9. Access Control Mechanism for IoT Environments Based on Modelling Communication Procedures as Resources

    OpenAIRE

    Luis Cruz-Piris; Diego Rivera; Ivan Marsa-Maestre; Enrique de la Hoz; Juan R. Velasco

    2018-01-01

    Internet growth has generated new types of services where the use of sensors and actuators is especially remarkable. These services compose what is known as the Internet of Things (IoT). One of the biggest current challenges is obtaining a safe and easy access control scheme for the data managed in these services. We propose integrating IoT devices in an access control system designed for Web-based services by modelling certain IoT communication elements as resources. This would allow us to o...

  10. Traffic Congestion Evaluation and Signal Control Optimization Based on Wireless Sensor Networks: Model and Algorithms

    Directory of Open Access Journals (Sweden)

    Wei Zhang

    2012-01-01

    Full Text Available This paper presents the model and algorithms for traffic flow data monitoring and optimal traffic light control based on wireless sensor networks. Given the scenario that sensor nodes are sparsely deployed along the segments between signalized intersections, an analytical model is built using continuum traffic equation and develops the method to estimate traffic parameter with the scattered sensor data. Based on the traffic data and principle of traffic congestion formation, we introduce the congestion factor which can be used to evaluate the real-time traffic congestion status along the segment and to predict the subcritical state of traffic jams. The result is expected to support the timing phase optimization of traffic light control for the purpose of avoiding traffic congestion before its formation. We simulate the traffic monitoring based on the Mobile Century dataset and analyze the performance of traffic light control on VISSIM platform when congestion factor is introduced into the signal timing optimization model. The simulation result shows that this method can improve the spatial-temporal resolution of traffic data monitoring and evaluate traffic congestion status with high precision. It is helpful to remarkably alleviate urban traffic congestion and decrease the average traffic delays and maximum queue length.

  11. On Synergistic Integration of Adaptive Dithering Based Internal Model Control for Hysteresis Compensation in Piezoactuated Nanopositioner

    Directory of Open Access Journals (Sweden)

    Saikat Kumar Shome

    2015-01-01

    Full Text Available Piezoelectric-stack actuated platforms are very popular in the parlance of nanopositioning with myriad applications like micro/nanofactory, atomic force microscopy, scanning probe microscopy, wafer design, biological cell manipulation, and so forth. Motivated by the necessity to improve trajectory tracking in such applications, this paper addresses the problem of rate dependent hysteretic nonlinearity in piezoelectric actuators (PEA. The classical second order Dahl model for hysteresis encapsulation is introduced first, followed by the identification of parameters through particle swarm optimization. A novel inversion based feedforward mechanism in combination with a feedback compensator is proposed to achieve high-precision tracking wherein the paradoxical concept of noise as a performance enhancer is introduced in the realm of PZAs. Having observed that dither induced stochastic resonance in the presence of periodic forcing reduces tracking error, dither capability is further explored in conjunction with a novel output harmonics based adaptive control scheme. The proposed adaptive controller is then augmented with an internal model control based approach to impart robustness against parametric variations and external disturbances. The proposed control law has been employed to track multifrequency signals with consistent compensation of rate dependent hysteresis of the PEA. The results indicate a greatly improved positioning accuracy along with considerable robustness achieved with the proposed integrated approach even for dual axis tracking applications.

  12. Performance-based parameter tuning method of model-driven PID control systems.

    Science.gov (United States)

    Zhao, Y M; Xie, W F; Tu, X W

    2012-05-01

    In this paper, performance-based parameter tuning method of model-driven Two-Degree-of-Freedom PID (MD TDOF PID) control system has been proposed to enhance the control performances of a process. Known for its ability of stabilizing the unstable processes, fast tracking to the change of set points and rejecting disturbance, the MD TDOF PID has gained research interest recently. The tuning methods for the reported MD TDOF PID are based on internal model control (IMC) method instead of optimizing the performance indices. In this paper, an Integral of Time Absolute Error (ITAE) zero-position-error optimal tuning and noise effect minimizing method is proposed for tuning two parameters in MD TDOF PID control system to achieve the desired regulating and disturbance rejection performance. The comparison with Two-Degree-of-Freedom control scheme by modified smith predictor (TDOF CS MSP) and the designed MD TDOF PID tuned by the IMC tuning method demonstrates the effectiveness of the proposed tuning method. Copyright © 2012 ISA. Published by Elsevier Ltd. All rights reserved.

  13. Reducing Turbine Mechanical Loads Using Flow Model-Based Wind Farm Controller

    DEFF Research Database (Denmark)

    Kazda, Jonas; Cutululis, Nicolaos Antonio

    Cumulated O&M costs of offshore wind farms are comparable with wind turbine CAPEX of such wind farm. In wind farms, wake effects can result in up to 80% higher fatigue loads at downstream wind turbines [1] and consequently larger O&M costs. The present work therefore investigates to reduce...... these loads during the provision of grid balancing services using optimal model-based wind farm control. Wind farm controllers coordinate the operating point of wind turbines in a wind farm in order to achieve a given objective. The investigated objective of the control in this work is to follow a total wind...... farm power reference while reducing the tower bending moments of the turbines in the wind farm. The wind farm controller is tested on a 8 turbine array, which is representative of a typical offshore wind farm. The operation of the wind farm is simulated using the dynamic wind farm simulation tool S imWind...

  14. Disturbance observer based model predictive control for accurate atmospheric entry of spacecraft

    Science.gov (United States)

    Wu, Chao; Yang, Jun; Li, Shihua; Li, Qi; Guo, Lei

    2018-05-01

    Facing the complex aerodynamic environment of Mars atmosphere, a composite atmospheric entry trajectory tracking strategy is investigated in this paper. External disturbances, initial states uncertainties and aerodynamic parameters uncertainties are the main problems. The composite strategy is designed to solve these problems and improve the accuracy of Mars atmospheric entry. This strategy includes a model predictive control for optimized trajectory tracking performance, as well as a disturbance observer based feedforward compensation for external disturbances and uncertainties attenuation. 500-run Monte Carlo simulations show that the proposed composite control scheme achieves more precise Mars atmospheric entry (3.8 km parachute deployment point distribution error) than the baseline control scheme (8.4 km) and integral control scheme (5.8 km).

  15. Model Predictive Control-based gait pattern generation for wearable exoskeletons.

    Science.gov (United States)

    Wang, Letian; van Asseldonk, Edwin H F; van der Kooij, Herman

    2011-01-01

    This paper introduces a new method for controlling wearable exoskeletons that do not need predefined joint trajectories. Instead, it only needs basic gait descriptors such as step length, swing duration, and walking speed. End point Model Predictive Control (MPC) is used to generate the online joint trajectories based on these gait parameters. Real-time ability and control performance of the method during the swing phase of gait cycle is studied in this paper. Experiments are performed by helping a human subject swing his leg with different patterns in the LOPES gait trainer. Results show that the method is able to assist subjects to make steps with different step length and step duration without predefined joint trajectories and is fast enough for real-time implementation. Future study of the method will focus on controlling the exoskeletons in the entire gait cycle. © 2011 IEEE

  16. Model Predictive Control Based on Kalman Filter for Constrained Hammerstein-Wiener Systems

    Directory of Open Access Journals (Sweden)

    Man Hong

    2013-01-01

    Full Text Available To precisely track the reactor temperature in the entire working condition, the constrained Hammerstein-Wiener model describing nonlinear chemical processes such as in the continuous stirred tank reactor (CSTR is proposed. A predictive control algorithm based on the Kalman filter for constrained Hammerstein-Wiener systems is designed. An output feedback control law regarding the linear subsystem is derived by state observation. The size of reaction heat produced and its influence on the output are evaluated by the Kalman filter. The observation and evaluation results are calculated by the multistep predictive approach. Actual control variables are computed while considering the constraints of the optimal control problem in a finite horizon through the receding horizon. The simulation example of the CSTR tester shows the effectiveness and feasibility of the proposed algorithm.

  17. Stabilization of nonlinear systems using sampled-data output-feedback fuzzy controller based on polynomial-fuzzy-model-based control approach.

    Science.gov (United States)

    Lam, H K

    2012-02-01

    This paper investigates the stability of sampled-data output-feedback (SDOF) polynomial-fuzzy-model-based control systems. Representing the nonlinear plant using a polynomial fuzzy model, an SDOF fuzzy controller is proposed to perform the control process using the system output information. As only the system output is available for feedback compensation, it is more challenging for the controller design and system analysis compared to the full-state-feedback case. Furthermore, because of the sampling activity, the control signal is kept constant by the zero-order hold during the sampling period, which complicates the system dynamics and makes the stability analysis more difficult. In this paper, two cases of SDOF fuzzy controllers, which either share the same number of fuzzy rules or not, are considered. The system stability is investigated based on the Lyapunov stability theory using the sum-of-squares (SOS) approach. SOS-based stability conditions are obtained to guarantee the system stability and synthesize the SDOF fuzzy controller. Simulation examples are given to demonstrate the merits of the proposed SDOF fuzzy control approach.

  18. A novel model-based control strategy for aerobic filamentous fungal fed-batch fermentation processes

    DEFF Research Database (Denmark)

    Mears, Lisa; Stocks, Stuart M.; Albaek, Mads O.

    2017-01-01

    A novel model-based control strategy has been developed for filamentous fungal fed-batch fermentation processes. The system of interest is a pilot scale (550 L) filamentous fungus process operating at Novozymes A/S. In such processes, it is desirable to maximize the total product achieved...... is recursively updated using on-line measurements. The model was applied in order to predict the current system states, including the biomass concentration, and to simulate the expected future trajectory of the system until a specified end time. In this way, the desired feed rate is updated along the progress...

  19. Economic Model Predictive Control for Hot Water Based Heating Systems in Smart Buildings

    DEFF Research Database (Denmark)

    Awadelrahman, M. A. Ahmed; Zong, Yi; Li, Hongwei

    2017-01-01

    This paper presents a study to optimize the heating energy costs in a residential building with varying electricity price signals based on an Economic Model Predictive Controller (EMPC). The investigated heating system consists of an air source heat pump (ASHP) incorporated with a hot water tank...... as active Thermal Energy Storage (TES), where two optimization problems are integrated together to optimize both the ASHP electricity consumption and the building heating consumption utilizing a heat dynamic model of the building. The results show that the proposed EMPC can save the energy cost by load...

  20. Model-based verification method for solving the parameter uncertainty in the train control system

    International Nuclear Information System (INIS)

    Cheng, Ruijun; Zhou, Jin; Chen, Dewang; Song, Yongduan

    2016-01-01

    This paper presents a parameter analysis method to solve the parameter uncertainty problem for hybrid system and explore the correlation of key parameters for distributed control system. For improving the reusability of control model, the proposed approach provides the support for obtaining the constraint sets of all uncertain parameters in the abstract linear hybrid automata (LHA) model when satisfying the safety requirements of the train control system. Then, in order to solve the state space explosion problem, the online verification method is proposed to monitor the operating status of high-speed trains online because of the real-time property of the train control system. Furthermore, we construct the LHA formal models of train tracking model and movement authority (MA) generation process as cases to illustrate the effectiveness and efficiency of the proposed method. In the first case, we obtain the constraint sets of uncertain parameters to avoid collision between trains. In the second case, the correlation of position report cycle and MA generation cycle is analyzed under both the normal and the abnormal condition influenced by packet-loss factor. Finally, considering stochastic characterization of time distributions and real-time feature of moving block control system, the transient probabilities of wireless communication process are obtained by stochastic time petri nets. - Highlights: • We solve the parameters uncertainty problem by using model-based method. • We acquire the parameter constraint sets by verifying linear hybrid automata models. • Online verification algorithms are designed to monitor the high-speed trains. • We analyze the correlation of key parameters and uncritical parameters. • The transient probabilities are obtained by using reliability analysis.

  1. Model-based adaptive sliding mode control of the subcritical boiler-turbine system with uncertainties.

    Science.gov (United States)

    Tian, Zhen; Yuan, Jingqi; Xu, Liang; Zhang, Xiang; Wang, Jingcheng

    2018-05-25

    As higher requirements are proposed for the load regulation and efficiency enhancement, the control performance of boiler-turbine systems has become much more important. In this paper, a novel robust control approach is proposed to improve the coordinated control performance for subcritical boiler-turbine units. To capture the key features of the boiler-turbine system, a nonlinear control-oriented model is established and validated with the history operation data of a 300 MW unit. To achieve system linearization and decoupling, an adaptive feedback linearization strategy is proposed, which could asymptotically eliminate the linearization error caused by the model uncertainties. Based on the linearized boiler-turbine system, a second-order sliding mode controller is designed with the super-twisting algorithm. Moreover, the closed-loop system is proved robustly stable with respect to uncertainties and disturbances. Simulation results are presented to illustrate the effectiveness of the proposed control scheme, which achieves excellent tracking performance, strong robustness and chattering reduction. Copyright © 2018. Published by Elsevier Ltd.

  2. Illuminance-based slat angle selection model for automated control of split blinds

    Energy Technology Data Exchange (ETDEWEB)

    Hu, Jia; Olbina, Svetlana [Rinker School of Building Construction, University of Florida, Gainesville, FL 32611-5703 (United States)

    2011-03-15

    Venetian blinds play an important role in controlling daylight in buildings. Automated blinds overcome some limitations of manual blinds; however, the existing automated systems mainly control the direct solar radiation and glare and cannot be used for controlling innovative blind systems such as split blinds. This research developed an Illuminance-based Slat Angle Selection (ISAS) model that predicts the optimum slat angles of split blinds to achieve the designed indoor illuminance. The model was constructed based on a series of multi-layer feed-forward artificial neural networks (ANNs). The illuminance values at the sensor points used to develop the ANNs were obtained by the software EnergyPlus trademark. The weather determinants (such as horizontal illuminance and sun angles) were used as the input variables for the ANNs. The illuminance level at a sensor point was the output variable for the ANNs. The ISAS model was validated by evaluating the errors in the calculation of the: 1) illuminance and 2) optimum slat angles. The validation results showed that the power of the ISAS model to predict illuminance was 94.7% while its power to calculate the optimum slat angles was 98.5%. For about 90% of time in the year, the illuminance percentage errors were less than 10%, and the percentage errors in calculating the optimum slat angles were less than 5%. This research offers a new approach for the automated control of split blinds and a guide for future research to utilize the adaptive nature of ANNs to develop a more practical and applicable blind control system. (author)

  3. Model-Free Coordinated Control for MHTGR-Based Nuclear Steam Supply Systems

    Directory of Open Access Journals (Sweden)

    Zhe Dong

    2016-01-01

    Full Text Available The modular high temperature gas-cooled reactor (MHTGR is a typical small modular reactor (SMR that offers simpler, standardized and safer modular design by being factory built, requiring smaller initial capital investment, and having a shorter construction period. Thanks to its small size, the MHTGRs could be beneficial in providing electric power to remote areas that are deficient in transmission or distribution and in generating local power for large population centers. Based on the multi-modular operation scheme, the inherent safety feature of the MHTGRs can be applicable to large nuclear plants of any desired power rating. The MHTGR-based nuclear steam supplying system (NSSS is constituted by an MHTGR, a side-by-side arranged helical-coil once-through steam generator (OTSG and some connecting pipes. Due to the side-by-side arrangement, there is a tight coupling effect between the MHTGR and OTSG. Moreover, there always exists the parameter perturbation of the NSSSs. Thus, it is meaningful to study the model-free coordinated control of MHTGR-based NSSSs for safe, stable, robust and efficient operation. In this paper, a new model-free coordinated control strategy that regulates the nuclear power, MHTGR outlet helium temperature and OTSG outlet overheated steam temperature by properly adjusting the control rod position, helium flowrate and feed-water flowrate is established for the MHTGR-based NSSSs. Sufficient conditions for the globally asymptotic closed-loop stability is given. Finally, numerical simulation results in the cases of large range power decrease and increase illustrate the satisfactory performance of this newly-developed model-free coordinated NSSS control law.

  4. A control method for agricultural greenhouses heating based on computational fluid dynamics and energy prediction model

    International Nuclear Information System (INIS)

    Chen, Jiaoliao; Xu, Fang; Tan, Dapeng; Shen, Zheng; Zhang, Libin; Ai, Qinglin

    2015-01-01

    Highlights: • A novel control method for the heating greenhouse with SWSHPS is proposed. • CFD is employed to predict the priorities of FCU loops for thermal performance. • EPM is act as an on-line tool to predict the total energy demand of greenhouse. • The CFD–EPM-based method can save energy and improve control accuracy. • The energy savings potential is between 8.7% and 15.1%. - Abstract: As energy heating is one of the main production costs, many efforts have been made to reduce the energy consumption of agricultural greenhouses. Herein, a novel control method of greenhouse heating using computational fluid dynamics (CFD) and energy prediction model (EPM) is proposed for energy savings and system performance. Based on the low-Reynolds number k–ε turbulence principle, a CFD model of heating greenhouse is developed, applying the discrete ordinates model for the radiative heat transfers and porous medium approach for plants considering plants sensible and latent heat exchanges. The CFD simulations have been validated, and used to analyze the greenhouse thermal performance and the priority of fan coil units (FCU) loops under the various heating conditions. According to the heating efficiency and temperature uniformity, the priorities of each FCU loop can be predicted to generate a database with priorities for control system. EPM is built up based on the thermal balance, and used to predict and optimize the energy demand of the greenhouse online. Combined with the priorities of FCU loops from CFD simulations offline, we have developed the CFD–EPM-based heating control system of greenhouse with surface water source heat pumps system (SWSHPS). Compared with conventional multi-zone independent control (CMIC) method, the energy savings potential is between 8.7% and 15.1%, and the control temperature deviation is decreased to between 0.1 °C and 0.6 °C in the investigated greenhouse. These results show the CFD–EPM-based method can improve system

  5. CystiSim - an agent-based model for Taenia solium transmission and control

    DEFF Research Database (Denmark)

    Braae, Uffe Christian; Devleesschauwer, Brecht; Gabriël, Sarah

    2016-01-01

    Taenia solium taeniosis/cysticercosis was declared eradicable by the International Task Force for Disease Eradication in 1993, but remains a neglected zoonosis. To assist in the attempt to regionally eliminate this parasite, we developed cystiSim, an agent-based model for T. solium transmission...... interventions in both hosts, mass drug administration to humans, and vaccination and treatment of pigs, have a high probability of success if coverage of 75% can be maintained over at least a four year period. In comparison with an existing mathematical model for T. solium transmission, cystiSim also includes...... and control. The model was developed in R and available as an R package (http://cran.r-project.org/package=cystiSim). cystiSim was adapted to an observed setting using field data from Tanzania, but adaptable to other settings if necessary. The model description adheres to the Overview, Design concepts...

  6. Stability Analysis of Positive Polynomial Fuzzy-Model-Based Control Systems with Time Delay under Imperfect Premise Matching

    OpenAIRE

    Li, Xiaomiao; Lam, Hak Keung; Song, Ge; Liu, Fucai

    2017-01-01

    This paper deals with the stability and positivity analysis of polynomial-fuzzy-model-based ({PFMB}) control systems with time delay, which is formed by a polynomial fuzzy model and a polynomial fuzzy controller connected in a closed loop, under imperfect premise matching. To improve the design and realization flexibility, the polynomial fuzzy model and the polynomial fuzzy controller are allowed to have their own set of premise membership functions. A sum-of-squares (SOS)-based stability ana...

  7. LMI-based stability analysis of fuzzy-model-based control systems using approximated polynomial membership functions.

    Science.gov (United States)

    Narimani, Mohammand; Lam, H K; Dilmaghani, R; Wolfe, Charles

    2011-06-01

    Relaxed linear-matrix-inequality-based stability conditions for fuzzy-model-based control systems with imperfect premise matching are proposed. First, the derivative of the Lyapunov function, containing the product terms of the fuzzy model and fuzzy controller membership functions, is derived. Then, in the partitioned operating domain of the membership functions, the relations between the state variables and the mentioned product terms are represented by approximated polynomials in each subregion. Next, the stability conditions containing the information of all subsystems and the approximated polynomials are derived. In addition, the concept of the S-procedure is utilized to release the conservativeness caused by considering the whole operating region for approximated polynomials. It is shown that the well-known stability conditions can be special cases of the proposed stability conditions. Simulation examples are given to illustrate the validity of the proposed approach.

  8. A Model-based B2B (Batch to Batch) Control for An Industrial Batch Polymerization Process

    Science.gov (United States)

    Ogawa, Morimasa

    This paper describes overview of a model-based B2B (batch to batch) control for an industrial batch polymerization process. In order to control the reaction temperature precisely, several methods based on the rigorous process dynamics model are employed at all design stage of the B2B control, such as modeling and parameter estimation of the reaction kinetics which is one of the important part of the process dynamics model. The designed B2B control consists of the gain scheduled I-PD/II2-PD control (I-PD with double integral control), the feed-forward compensation at the batch start time, and the model adaptation utilizing the results of the last batch operation. Throughout the actual batch operations, the B2B control provides superior control performance compared with that of conventional control methods.

  9. Computer-Aided Design Methods for Model-Based Nonlinear Engine Control Systems, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — Traditional design methods for aircraft turbine engine control systems have relied on the use of linearized models and linear control theory. While these controllers...

  10. Modeling and Sensitivity Study of Consensus Algorithm-Based Distributed Hierarchical Control for DC Microgrids

    DEFF Research Database (Denmark)

    Meng, Lexuan; Dragicevic, Tomislav; Roldan Perez, Javier

    2016-01-01

    Distributed control methods based on consensus algorithms have become popular in recent years for microgrid (MG) systems. These kinds of algorithms can be applied to share information in order to coordinate multiple distributed generators within a MG. However, stability analysis becomes a challen......Distributed control methods based on consensus algorithms have become popular in recent years for microgrid (MG) systems. These kinds of algorithms can be applied to share information in order to coordinate multiple distributed generators within a MG. However, stability analysis becomes...... in the communication network, continuous-time methods can be inaccurate for this kind of dynamic study. Therefore, this paper aims at modeling a complete DC MG using a discrete-time approach in order to perform a sensitivity analysis taking into account the effects of the consensus algorithm. To this end......, a generalized modeling method is proposed and the influence of key control parameters, the communication topology and the communication speed are studied in detail. The theoretical results obtained with the proposed model are verified by comparing them with the results obtained with a detailed switching...

  11. A Model-based Framework for Risk Assessment in Human-Computer Controlled Systems

    Science.gov (United States)

    Hatanaka, Iwao

    2000-01-01

    The rapid growth of computer technology and innovation has played a significant role in the rise of computer automation of human tasks in modem production systems across all industries. Although the rationale for automation has been to eliminate "human error" or to relieve humans from manual repetitive tasks, various computer-related hazards and accidents have emerged as a direct result of increased system complexity attributed to computer automation. The risk assessment techniques utilized for electromechanical systems are not suitable for today's software-intensive systems or complex human-computer controlled systems. This thesis will propose a new systemic model-based framework for analyzing risk in safety-critical systems where both computers and humans are controlling safety-critical functions. A new systems accident model will be developed based upon modem systems theory and human cognitive processes to better characterize system accidents, the role of human operators, and the influence of software in its direct control of significant system functions. Better risk assessments will then be achievable through the application of this new framework to complex human-computer controlled systems.

  12. Cylinder pressure sensing and model-based control in engine management systems

    Energy Technology Data Exchange (ETDEWEB)

    Truscott, A.; Noble, A.; Akoachere, A.; Beaumont, A. [Ricardo Consulting Engineers Ltd., Bridge Works (United Kingdom); Mueller, R.; Hart, M. [FT2/EA, HPC T721, DaimlerChrysler AG, Stuttgart (Germany); Kroetz, G. [FT2/M, DaimlerChrysler AG, Muenchen (Germany); Cavalloni, C.; Gnielka, M. [Kistler Instrumente AG, Winterthur (Switzerland)

    2000-07-01

    Global demands on fuel economy and lower emissions from automotive vehicles have had a large impact on the development of engine management systems (EMS) in recent years. However, despite the advances in system hardware, the software programmed into these systems has yet to utilise the full potential of modern control methodologies. Model based control and diagnostics is the next step forward in the development of EMS software with the potential of providing improvements in cost, efficiency, emissions and comfort. However, the full utilisation of such techniques requires very close monitoring of engine conditions. This is made possible with the advent of new inexpensive sensor technology that can withstand the harsh environment of the combustion chamber. To exploit the above advances, the AENEAS collaborative project is being carried out by Ricardo, DaimlerChrysler and Kistler, with financial support from the European Commission and Swiss government, and has the objective of realising the benefits of cylinder pressure based engine management system (CPEMS) technology. This paper describes the application of CPEMS technology to a spark ignition (SI) engine. It describes how the combination of model based algorithms, incorporating physical principles, and cylinder pressure sensing can provide an effective means of engine control and diagnostics. (orig.)

  13. MODELING OF OPERATION MODES OF SHIP POWER PLANT OF COMBINED PROPULSION COMPLEX WITH CONTROL SYSTEM BASED ON ELECTRONIC CONTROLLERS

    Directory of Open Access Journals (Sweden)

    E. A. Yushkov

    2016-12-01

    Full Text Available Purpose. Designing of diagrams to optimize mathematic model of the ship power plant (SPP combined propulsion complexes (CPC for decreasing operational loss and increasing fuel efficiency with simultaneous load limiting on medium revolutions diesel generator (MRDG by criterion reducing of wear and increasing operation time between repairs. Methodology. After analyzing of ship power plant modes of CPC proposed diagrams to optimize mathematic model of the above mentioned complex. The model based on using of electronic controllers in automatic regulation and control systems for diesel and thruster which allow to actualize more complicated control algorithm with viewpoint of increasing working efficiency of ship power plant at normal and emergency modes. Results. Determined suitability of comparative computer modeling in MatLab Simulink for building of imitation model objects based on it block diagrams and mathematic descriptions. Actualized diagrams to optimize mathematic model of the ship’s power plant (SPP combined propulsion complexes (CPC with Azipod system in MatLab Simulink software package Ships_CPC for decreasing operational loss and increasing fuel efficiency with simultaneous load limiting on medium revolutions diesel generator (MRDG by criterion reducing of wear and increasing operation time between repairs. The function blocks of proposed complex are the main structural units which allow to investigate it normal and emergency modes. Originality. This model represents a set of functional blocks of the components SPP CPC, built on the principle of «input-output». For example, the function boxes outputs of PID-regulators of MRDG depends from set excitation voltage and rotating frequency that in turn depends from power-station load and respond that is a ship moving or dynamically positioning, and come on input (inputs of thruster rotating frequency PID-regulator models. Practical value. The results of researches planned to use in

  14. Model-based iterative learning control of Parkinsonian state in thalamic relay neuron

    Science.gov (United States)

    Liu, Chen; Wang, Jiang; Li, Huiyan; Xue, Zhiqin; Deng, Bin; Wei, Xile

    2014-09-01

    Although the beneficial effects of chronic deep brain stimulation on Parkinson's disease motor symptoms are now largely confirmed, the underlying mechanisms behind deep brain stimulation remain unclear and under debate. Hence, the selection of stimulation parameters is full of challenges. Additionally, due to the complexity of neural system, together with omnipresent noises, the accurate model of thalamic relay neuron is unknown. Thus, the iterative learning control of the thalamic relay neuron's Parkinsonian state based on various variables is presented. Combining the iterative learning control with typical proportional-integral control algorithm, a novel and efficient control strategy is proposed, which does not require any particular knowledge on the detailed physiological characteristics of cortico-basal ganglia-thalamocortical loop and can automatically adjust the stimulation parameters. Simulation results demonstrate the feasibility of the proposed control strategy to restore the fidelity of thalamic relay in the Parkinsonian condition. Furthermore, through changing the important parameter—the maximum ionic conductance densities of low-threshold calcium current, the dominant characteristic of the proposed method which is independent of the accurate model can be further verified.

  15. Multi-agent control system with information fusion based comfort model for smart buildings

    International Nuclear Information System (INIS)

    Wang, Zhu; Wang, Lingfeng; Dounis, Anastasios I.; Yang, Rui

    2012-01-01

    Highlights: ► Proposed a model to manage indoor energy and comfort for smart buildings. ► Developed a control system to maximize comfort with minimum energy consumption. ► Information fusion with ordered weighted averaging aggregation is used. ► Multi-agent technology and heuristic intelligent optimization are deployed in developing the control system. -- Abstract: From the perspective of system control, a smart and green building is a large-scale dynamic system with high complexity and a huge amount of information. Proper combination of the available information and effective control of the overall building system turns out to be a big challenge. In this study, we proposed a building indoor energy and comfort management model based on information fusion using ordered weighted averaging (OWA) aggregation. A multi-agent control system with heuristic intelligent optimization is developed to achieve a high level of comfort with the minimum power consumption. Case studies and simulation results are presented and discussed in this paper.

  16. Trust-Based Access Control Model from Sociological Approach in Dynamic Online Social Network Environment

    Science.gov (United States)

    Kim, Seungjoo

    2014-01-01

    There has been an explosive increase in the population of the OSN (online social network) in recent years. The OSN provides users with many opportunities to communicate among friends and family. Further, it facilitates developing new relationships with previously unknown people having similar beliefs or interests. However, the OSN can expose users to adverse effects such as privacy breaches, the disclosing of uncontrolled material, and the disseminating of false information. Traditional access control models such as MAC, DAC, and RBAC are applied to the OSN to address these problems. However, these models are not suitable for the dynamic OSN environment because user behavior in the OSN is unpredictable and static access control imposes a burden on the users to change the access control rules individually. We propose a dynamic trust-based access control for the OSN to address the problems of the traditional static access control. Moreover, we provide novel criteria to evaluate trust factors such as sociological approach and evaluate a method to calculate the dynamic trust values. The proposed method can monitor negative behavior and modify access permission levels dynamically to prevent the indiscriminate disclosure of information. PMID:25374943

  17. Trust-Based Access Control Model from Sociological Approach in Dynamic Online Social Network Environment

    Directory of Open Access Journals (Sweden)

    Seungsoo Baek

    2014-01-01

    Full Text Available There has been an explosive increase in the population of the OSN (online social network in recent years. The OSN provides users with many opportunities to communicate among friends and family. Further, it facilitates developing new relationships with previously unknown people having similar beliefs or interests. However, the OSN can expose users to adverse effects such as privacy breaches, the disclosing of uncontrolled material, and the disseminating of false information. Traditional access control models such as MAC, DAC, and RBAC are applied to the OSN to address these problems. However, these models are not suitable for the dynamic OSN environment because user behavior in the OSN is unpredictable and static access control imposes a burden on the users to change the access control rules individually. We propose a dynamic trust-based access control for the OSN to address the problems of the traditional static access control. Moreover, we provide novel criteria to evaluate trust factors such as sociological approach and evaluate a method to calculate the dynamic trust values. The proposed method can monitor negative behavior and modify access permission levels dynamically to prevent the indiscriminate disclosure of information.

  18. Robust entry guidance using linear covariance-based model predictive control

    Directory of Open Access Journals (Sweden)

    Jianjun Luo

    2017-02-01

    Full Text Available For atmospheric entry vehicles, guidance design can be accomplished by solving an optimal issue using optimal control theories. However, traditional design methods generally focus on the nominal performance and do not include considerations of the robustness in the design process. This paper proposes a linear covariance-based model predictive control method for robust entry guidance design. Firstly, linear covariance analysis is employed to directly incorporate the robustness into the guidance design. The closed-loop covariance with the feedback updated control command is initially formulated to provide the expected errors of the nominal state variables in the presence of uncertainties. Then, the closed-loop covariance is innovatively used as a component of the cost function to guarantee the robustness to reduce its sensitivity to uncertainties. After that, the models predictive control is used to solve the optimal problem, and the control commands (bank angles are calculated. Finally, a series of simulations for different missions have been completed to demonstrate the high performance in precision and the robustness with respect to initial perturbations as well as uncertainties in the entry process. The 3σ confidence region results in the presence of uncertainties which show that the robustness of the guidance has been improved, and the errors of the state variables are decreased by approximately 35%.

  19. Energy efficient model based algorithm for control of building HVAC systems.

    Science.gov (United States)

    Kirubakaran, V; Sahu, Chinmay; Radhakrishnan, T K; Sivakumaran, N

    2015-11-01

    Energy efficient designs are receiving increasing attention in various fields of engineering. Heating ventilation and air conditioning (HVAC) control system designs involve improved energy usage with an acceptable relaxation in thermal comfort. In this paper, real time data from a building HVAC system provided by BuildingLAB is considered. A resistor-capacitor (RC) framework for representing thermal dynamics of the building is estimated using particle swarm optimization (PSO) algorithm. With objective costs as thermal comfort (deviation of room temperature from required temperature) and energy measure (Ecm) explicit MPC design for this building model is executed based on its state space representation of the supply water temperature (input)/room temperature (output) dynamics. The controllers are subjected to servo tracking and external disturbance (ambient temperature) is provided from the real time data during closed loop control. The control strategies are ported on a PIC32mx series microcontroller platform. The building model is implemented in MATLAB and hardware in loop (HIL) testing of the strategies is executed over a USB port. Results indicate that compared to traditional proportional integral (PI) controllers, the explicit MPC's improve both energy efficiency and thermal comfort significantly. Copyright © 2015 Elsevier Inc. All rights reserved.

  20. Enhanced Engine Performance During Emergency Operation Using a Model-Based Engine Control Architecture

    Science.gov (United States)

    Csank, Jeffrey T.; Connolly, Joseph W.

    2016-01-01

    This paper discusses the design and application of model-based engine control (MBEC) for use during emergency operation of the aircraft. The MBEC methodology is applied to the Commercial Modular Aero-Propulsion System Simulation 40k (CMAPSS40k) and features an optimal tuner Kalman Filter (OTKF) to estimate unmeasured engine parameters, which can then be used for control. During an emergency scenario, normally-conservative engine operating limits may be relaxed to increase the performance of the engine and overall survivability of the aircraft; this comes at the cost of additional risk of an engine failure. The MBEC architecture offers the advantage of estimating key engine parameters that are not directly measureable. Estimating the unknown parameters allows for tighter control over these parameters, and on the level of risk the engine will operate at. This will allow the engine to achieve better performance than possible when operating to more conservative limits on a related, measurable parameter.

  1. Tuning rules for robust FOPID controllers based on multi-objective optimization with FOPDT models.

    Science.gov (United States)

    Sánchez, Helem Sabina; Padula, Fabrizio; Visioli, Antonio; Vilanova, Ramon

    2017-01-01

    In this paper a set of optimally balanced tuning rules for fractional-order proportional-integral-derivative controllers is proposed. The control problem of minimizing at once the integrated absolute error for both the set-point and the load disturbance responses is addressed. The control problem is stated as a multi-objective optimization problem where a first-order-plus-dead-time process model subject to a robustness, maximum sensitivity based, constraint has been considered. A set of Pareto optimal solutions is obtained for different normalized dead times and then the optimal balance between the competing objectives is obtained by choosing the Nash solution among the Pareto-optimal ones. A curve fitting procedure has then been applied in order to generate suitable tuning rules. Several simulation results show the effectiveness of the proposed approach. Copyright © 2016. Published by Elsevier Ltd.

  2. 3D force control for robotic-assisted beating heart surgery based on viscoelastic tissue model.

    Science.gov (United States)

    Liu, Chao; Moreira, Pedro; Zemiti, Nabil; Poignet, Philippe

    2011-01-01

    Current cardiac surgery faces the challenging problem of heart beating motion even with the help of mechanical stabilizer which makes delicate operation on the heart surface difficult. Motion compensation methods for robotic-assisted beating heart surgery have been proposed recently in literature, but research on force control for such kind of surgery has hardly been reported. Moreover, the viscoelasticity property of the interaction between organ tissue and robotic instrument further complicates the force control design which is much easier in other applications by assuming the interaction model to be elastic (industry, stiff object manipulation, etc.). In this work, we present a three-dimensional force control method for robotic-assisted beating heart surgery taking into consideration of the viscoelastic interaction property. Performance studies based on our D2M2 robot and 3D heart beating motion information obtained through Da Vinci™ system are provided.

  3. Economic Model Predictive Control of Bihormonal Artificial Pancreas System Based on Switching Control and Dynamic R-parameter.

    Science.gov (United States)

    Tang, Fengna; Wang, Youqing

    2017-11-01

    Blood glucose (BG) regulation is a long-term task for people with diabetes. In recent years, more and more researchers have attempted to achieve automated regulation of BG using automatic control algorithms, called the artificial pancreas (AP) system. In clinical practice, it is equally important to guarantee the treatment effect and reduce the treatment costs. The main motivation of this study is to reduce the cure burden. The dynamic R-parameter economic model predictive control (R-EMPC) is chosen to regulate the delivery rates of exogenous hormones (insulin and glucagon). It uses particle swarm optimization (PSO) to optimize the economic cost function and the switching logic between insulin delivery and glucagon delivery is designed based on switching control theory. The proposed method is first tested on the standard subject; the result is compared with the switching PID and the switching MPC. The effect of the dynamic R-parameter on improving the control performance is illustrated by comparing the results of the EMPC and the R-EMPC. Finally, the robustness tests on meal change (size and timing), hormone sensitivity (insulin and glucagon), and subject variability are performed. All results show that the proposed method can improve the control performance and reduce the economic costs. The simulation results verify the effectiveness of the proposed algorithm on improving the tracking performance, enhancing robustness, and reducing economic costs. The method proposed in this study owns great worth in practical application.

  4. CystiSim - An Agent-Based Model for Taenia solium Transmission and Control.

    Science.gov (United States)

    Braae, Uffe Christian; Devleesschauwer, Brecht; Gabriël, Sarah; Dorny, Pierre; Speybroeck, Niko; Magnussen, Pascal; Torgerson, Paul; Johansen, Maria Vang

    2016-12-01

    Taenia solium taeniosis/cysticercosis was declared eradicable by the International Task Force for Disease Eradication in 1993, but remains a neglected zoonosis. To assist in the attempt to regionally eliminate this parasite, we developed cystiSim, an agent-based model for T. solium transmission and control. The model was developed in R and available as an R package (http://cran.r-project.org/package=cystiSim). cystiSim was adapted to an observed setting using field data from Tanzania, but adaptable to other settings if necessary. The model description adheres to the Overview, Design concepts, and Details (ODD) protocol and consists of two entities-pigs and humans. Pigs acquire cysticercosis through the environment or by direct contact with a tapeworm carrier's faeces. Humans acquire taeniosis from slaughtered pigs proportional to their infection intensity. The model allows for evaluation of three interventions measures or combinations hereof: treatment of humans, treatment of pigs, and pig vaccination, and allows for customary coverage and efficacy settings. cystiSim is the first agent-based transmission model for T. solium and suggests that control using a strategy consisting of an intervention only targeting the porcine host is possible, but that coverage and efficacy must be high if elimination is the ultimate goal. Good coverage of the intervention is important, but can be compensated for by including an additional intervention targeting the human host. cystiSim shows that the scenarios combining interventions in both hosts, mass drug administration to humans, and vaccination and treatment of pigs, have a high probability of success if coverage of 75% can be maintained over at least a four year period. In comparison with an existing mathematical model for T. solium transmission, cystiSim also includes parasite maturation, host immunity, and environmental contamination. Adding these biological parameters to the model resulted in new insights in the potential

  5. CystiSim – An Agent-Based Model for Taenia solium Transmission and Control

    Science.gov (United States)

    Gabriël, Sarah; Dorny, Pierre; Speybroeck, Niko; Magnussen, Pascal; Torgerson, Paul; Johansen, Maria Vang

    2016-01-01

    Taenia solium taeniosis/cysticercosis was declared eradicable by the International Task Force for Disease Eradication in 1993, but remains a neglected zoonosis. To assist in the attempt to regionally eliminate this parasite, we developed cystiSim, an agent-based model for T. solium transmission and control. The model was developed in R and available as an R package (http://cran.r-project.org/package=cystiSim). cystiSim was adapted to an observed setting using field data from Tanzania, but adaptable to other settings if necessary. The model description adheres to the Overview, Design concepts, and Details (ODD) protocol and consists of two entities—pigs and humans. Pigs acquire cysticercosis through the environment or by direct contact with a tapeworm carrier's faeces. Humans acquire taeniosis from slaughtered pigs proportional to their infection intensity. The model allows for evaluation of three interventions measures or combinations hereof: treatment of humans, treatment of pigs, and pig vaccination, and allows for customary coverage and efficacy settings. cystiSim is the first agent-based transmission model for T. solium and suggests that control using a strategy consisting of an intervention only targeting the porcine host is possible, but that coverage and efficacy must be high if elimination is the ultimate goal. Good coverage of the intervention is important, but can be compensated for by including an additional intervention targeting the human host. cystiSim shows that the scenarios combining interventions in both hosts, mass drug administration to humans, and vaccination and treatment of pigs, have a high probability of success if coverage of 75% can be maintained over at least a four year period. In comparison with an existing mathematical model for T. solium transmission, cystiSim also includes parasite maturation, host immunity, and environmental contamination. Adding these biological parameters to the model resulted in new insights in the potential

  6. Design of current controller of grid-connected voltage source converter based internal model control in wind power

    Energy Technology Data Exchange (ETDEWEB)

    Zhang Xianping; Guo Jindong; Xu Honghua [Inst. of Electrical Engineering, Chinese Academy of Sciences, BJ (China)

    2008-07-01

    Grid-connected voltage source converter (VSC) is important for variable speed turbines with doubly fed induction generator (DFIG), and bad performance of current loop of VSC may cause VSC inject much low and high order harmonics into grid. Therefore, design of current controller of VSC is very important. PI regulator is often used to regulate current error in dq rotating coordinate to obtain zero steady error. However, it is complex to design PI parameters, and researchers need many trial-and-error steps. Therefore, a novel and simple design method of PI regulator for grid-connected VSC, which is based internal model control (IMC), has been presented in this paper. The parameters of PI regulator can be expressed directly with certain L-type line filter parameters and the desired closed-loop bandwidth. At last, The simulation has been done and result shows that the method in this paper is easy and useful to regulate PI parameters. (orig.)

  7. Model Based Optimal Control, Estimation, and Validation of Lithium-Ion Batteries

    Science.gov (United States)

    Perez, Hector Eduardo

    This dissertation focuses on developing and experimentally validating model based control techniques to enhance the operation of lithium ion batteries, safely. An overview of the contributions to address the challenges that arise are provided below. Chapter 1: This chapter provides an introduction to battery fundamentals, models, and control and estimation techniques. Additionally, it provides motivation for the contributions of this dissertation. Chapter 2: This chapter examines reference governor (RG) methods for satisfying state constraints in Li-ion batteries. Mathematically, these constraints are formulated from a first principles electrochemical model. Consequently, the constraints explicitly model specific degradation mechanisms, such as lithium plating, lithium depletion, and overheating. This contrasts with the present paradigm of limiting measured voltage, current, and/or temperature. The critical challenges, however, are that (i) the electrochemical states evolve according to a system of nonlinear partial differential equations, and (ii) the states are not physically measurable. Assuming available state and parameter estimates, this chapter develops RGs for electrochemical battery models. The results demonstrate how electrochemical model state information can be utilized to ensure safe operation, while simultaneously enhancing energy capacity, power, and charge speeds in Li-ion batteries. Chapter 3: Complex multi-partial differential equation (PDE) electrochemical battery models are characterized by parameters that are often difficult to measure or identify. This parametric uncertainty influences the state estimates of electrochemical model-based observers for applications such as state-of-charge (SOC) estimation. This chapter develops two sensitivity-based interval observers that map bounded parameter uncertainty to state estimation intervals, within the context of electrochemical PDE models and SOC estimation. Theoretically, this chapter extends the

  8. Method of controlling illumination device based on current-voltage model

    DEFF Research Database (Denmark)

    2013-01-01

    The present invention relates to an illumination device comprising a number of LEDs, means for receiving an input signal, means for generating an activation signal for at least one of the LEDs based on the input signal. The illumination device comprises further means for obtaining the voltage...... and the colorimetric properties of said light emitted by LED. The present invention relates also to a method of controlling and a meted of calibrating such illumination device....... across and current through the LED and the means for generating the activation signal is adapted to generate the activating signal based on the voltage, the current and a current- voltage model related to LED. The current-voltage model defines a relationship between the current, the voltage...

  9. Discrete Second-Order Sliding Mode Adaptive Controller Based on Characteristic Model for Servo Systems

    Directory of Open Access Journals (Sweden)

    Zhihong Wang

    2015-01-01

    Full Text Available Considering the varying inertia and load torque in high speed and high accuracy servo systems, a novel discrete second-order sliding mode adaptive controller (DSSMAC based on characteristic model is proposed, and a command observer is also designed. Firstly, the discrete characteristic model of servo systems is established. Secondly, the recursive least square algorithm is adopted to identify time-varying parameters in characteristic model, and the observer is applied to predict the command value of next sample time. Furthermore, the stability of the closed-loop system and the convergence of the observer are analyzed. The experimental results show that the proposed method not only can adapt to varying inertia and load torque, but also has good disturbance rejection ability and robustness to uncertainties.

  10. A study on model fidelity for model predictive control-based obstacle avoidance in high-speed autonomous ground vehicles

    Science.gov (United States)

    Liu, Jiechao; Jayakumar, Paramsothy; Stein, Jeffrey L.; Ersal, Tulga

    2016-11-01

    This paper investigates the level of model fidelity needed in order for a model predictive control (MPC)-based obstacle avoidance algorithm to be able to safely and quickly avoid obstacles even when the vehicle is close to its dynamic limits. The context of this work is large autonomous ground vehicles that manoeuvre at high speed within unknown, unstructured, flat environments and have significant vehicle dynamics-related constraints. Five different representations of vehicle dynamics models are considered: four variations of the two degrees-of-freedom (DoF) representation as lower fidelity models and a fourteen DoF representation with combined-slip Magic Formula tyre model as a higher fidelity model. It is concluded that the two DoF representation that accounts for tyre nonlinearities and longitudinal load transfer is necessary for the MPC-based obstacle avoidance algorithm in order to operate the vehicle at its limits within an environment that includes large obstacles. For less challenging environments, however, the two DoF representation with linear tyre model and constant axle loads is sufficient.

  11. Research on Robot Pose Control Technology Based on Kinematics Analysis Model

    Science.gov (United States)

    Liu, Dalong; Xu, Lijuan

    2018-01-01

    In order to improve the attitude stability of the robot, proposes an attitude control method of robot based on kinematics analysis model, solve the robot walking posture transformation, grasping and controlling the motion planning problem of robot kinematics. In Cartesian space analytical model, using three axis accelerometer, magnetometer and the three axis gyroscope for the combination of attitude measurement, the gyroscope data from Calman filter, using the four element method for robot attitude angle, according to the centroid of the moving parts of the robot corresponding to obtain stability inertia parameters, using random sampling RRT motion planning method, accurate operation to any position control of space robot, to ensure the end effector along a prescribed trajectory the implementation of attitude control. The accurate positioning of the experiment is taken using MT-R robot as the research object, the test robot. The simulation results show that the proposed method has better robustness, and higher positioning accuracy, and it improves the reliability and safety of robot operation.

  12. Passivity-based model predictive control for mobile vehicle motion planning

    CERN Document Server

    Tahirovic, Adnan

    2013-01-01

    Passivity-based Model Predictive Control for Mobile Vehicle Navigation represents a complete theoretical approach to the adoption of passivity-based model predictive control (MPC) for autonomous vehicle navigation in both indoor and outdoor environments. The brief also introduces analysis of the worst-case scenario that might occur during the task execution. Some of the questions answered in the text include: • how to use an MPC optimization framework for the mobile vehicle navigation approach; • how to guarantee safe task completion even in complex environments including obstacle avoidance and sideslip and rollover avoidance; and  • what to expect in the worst-case scenario in which the roughness of the terrain leads the algorithm to generate the longest possible path to the goal. The passivity-based MPC approach provides a framework in which a wide range of complex vehicles can be accommodated to obtain a safer and more realizable tool during the path-planning stage. During task execution, the optimi...

  13. Front tracking based modeling of the solid grain growth on the adaptive control volume grid

    Science.gov (United States)

    Seredyński, Mirosław; Łapka, Piotr

    2017-07-01

    The paper presents the micro-scale model of unconstrained solidification of the grain immersed in under-cooled liquid, based on the front tracking approach. For this length scale, the interface tracked through the domain is meant as the solid-liquid boundary. To prevent generation of huge meshes the energy transport equation is discretized on the adaptive control volume (c.v.) mesh. The coupling of dynamically changing mesh and moving front position is addressed. Preliminary results of simulation of a test case, the growth of single grain, are presented and discussed.

  14. Model-Based, Closed-Loop Control of PZT Creep for Cavity Ring-Down Spectroscopy.

    Science.gov (United States)

    McCartt, A D; Ognibene, T J; Bench, G; Turteltaub, K W

    2014-09-01

    Cavity ring-down spectrometers typically employ a PZT stack to modulate the cavity transmission spectrum. While PZTs ease instrument complexity and aid measurement sensitivity, PZT hysteresis hinders the implementation of cavity-length-stabilized, data-acquisition routines. Once the cavity length is stabilized, the cavity's free spectral range imparts extreme linearity and precision to the measured spectrum's wavelength axis. Methods such as frequency-stabilized cavity ring-down spectroscopy have successfully mitigated PZT hysteresis, but their complexity limits commercial applications. Described herein is a single-laser, model-based, closed-loop method for cavity length control.

  15. Toward Model-Based Control of Non-linear Hydraulic Networks

    DEFF Research Database (Denmark)

    Tahavori, Maryamsadat; Jensen, Tom Nørgaard; Kallesøe, Carsten

    2013-01-01

    Water leakage is an important component of water loss. Many methods have emerged from urban water supply systems (WSSs) for leakage control, but it still remains a challenge in many countries. Pressure management is an effective way to reduce the leakage in a system. It can also reduce the power....... Following an analogy to electric circuits, first the mathematical expression for pressure drop over each component of the pipe network (WSS) such as pipes, pumps, valves and water towers is presented. Then the network model is derived based on the circuit theory and subsequently used for pressure management...

  16. Comparative investigation of ELM control based on toroidal modelling of plasma response to RMP fields

    Science.gov (United States)

    Liu, Yueqiang

    2016-10-01

    The type-I edge localized mode (ELM), bursting at low frequency and with large amplitude, can channel a substantial amount of the plasma thermal energy into the surrounding plasma-facing components in tokamak devices operating at the high-confinement mode, potentially causing severe material damages. Learning effective ways of controlling this instability is thus an urgent issue in fusion research, in particular in view of the next generation large devices such as ITER and DEMO. Among other means, externally applied, three-dimensional resonant magnetic perturbation (RMP) fields have been experimentally demonstrated to be successful in mitigating or suppressing the type-I ELM, in multiple existing devices. In this work, we shall report results of a comparative study of ELM control using RMPs. Comparison is made between the modelled plasma response to the 3D external fields and the observed change of the ELM behaviour on multiple devices, including MAST, ASDEX Upgrade, EAST, DIII-D, JET, and KSTAR. We show that toroidal modelling of the plasma response, based on linear and quasi-linear magnetohydrodynamic (MHD) models, provides essential insights that are useful in interpreting and guiding the ELM control experiments. In particular, linear toroidal modelling results, using the MARS-F code, reveal the crucial role of the edge localized peeling-tearing mode response during ELM mitigation/suppression on all these devices. Such response often leads to strong peaking of the plasma surface displacement near the region of weak equilibrium poloidal field (e.g. the X-point), and this provides an alternative practical criterion for ELM control, as opposed to the vacuum field based Chirikov criteria. Quasi-linear modelling using MARS-Q provides quantitative interpretation of the side effects due to the ELM control coils, on the plasma toroidal momentum and particle confinements. The particular role of the momentum and particle fluxes, associated with the neoclassical toroidal

  17. Beyond the CP-curve in Model-based Control of Wind Turbines

    DEFF Research Database (Denmark)

    Henriksen, Lars Christian; Hansen, Morten Hartvig; Poulsen, Niels Kjølstad

    2012-01-01

    The importance of including dynamic inflow in the model used by the control algorithm is investigated in this contribution. A control setup consisting of a model predictive controller and an extended Kalman filter in conjunction with mechanisms to switch smoothly between partial and full load ope...

  18. An agent-based simulation model for Clostridium difficile infection control.

    Science.gov (United States)

    Codella, James; Safdar, Nasia; Heffernan, Rick; Alagoz, Oguzhan

    2015-02-01

    Control of Clostridium difficile infection (CDI) is an increasingly difficult problem for health care institutions. There are commonly recommended strategies to combat CDI transmission, such as oral vancomycin for CDI treatment, increased hand hygiene with soap and water for health care workers, daily environmental disinfection of infected patient rooms, and contact isolation of diseased patients. However, the efficacy of these strategies, particularly for endemic CDI, has not been well studied. The objective of this research is to develop a valid, agent-based simulation model (ABM) to study C. difficile transmission and control in a midsized hospital. We develop an ABM of a midsized hospital with agents such as patients, health care workers, and visitors. We model the natural progression of CDI in a patient using a Markov chain and the transmission of CDI through agent and environmental interactions. We derive input parameters from aggregate patient data from the 2007-2010 Wisconsin Hospital Association and published medical literature. We define a calibration process, which we use to estimate transition probabilities of the Markov model by comparing simulation results to benchmark values found in published literature. In a comparison of CDI control strategies implemented individually, routine bleach disinfection of CDI-positive patient rooms provides the largest reduction in nosocomial asymptomatic colonization (21.8%) and nosocomial CDIs (42.8%). Additionally, vancomycin treatment provides the largest reduction in relapse CDIs (41.9%), CDI-related mortalities (68.5%), and total patient length of stay (21.6%). We develop a generalized ABM for CDI control that can be customized and further expanded to specific institutions and/or scenarios. Additionally, we estimate transition probabilities for a Markov model of natural CDI progression in a patient through calibration. © The Author(s) 2014.

  19. Modelling and Simulation of SVPWM Based Vector Controlled HVDC Light Systems

    Directory of Open Access Journals (Sweden)

    Ajay Kumar MOODADLA

    2012-11-01

    Full Text Available Recent upgrades in power electronics technology have lead to the improvements of insulated gate bipolar transistor (IGBT based Voltage source converter High voltage direct current (VSC HVDC transmission systems. These are also commercially known as HVDC Light systems, which are popular in renewable, micro grid, and electric power systems. Out of different pulse width modulation (PWM schemes, Space vector PWM (SVPWM control scheme finds growing importance in power system applications because of its better dc bus utilization. In this paper, modelling of the converter is described, and SVPWM scheme is utilized to control the HVDC Light system in order to achieve better DC bus utilization, harmonic reduction, and for reduced power fluctuations. The simulations are carried out in the MATLAB/SIMULINK environment and the results are provided for steady state and dynamic conditions. Finally, the performance of SVPWM based vector controlled HVDC Light transmission system is compared with sinusoidal pulse width modulation (SPWM based HVDC Light system in terms of output voltage and total harmonic distortion (THD.

  20. Cluster-based adaptive power control protocol using Hidden Markov Model for Wireless Sensor Networks

    Science.gov (United States)

    Vinutha, C. B.; Nalini, N.; Nagaraja, M.

    2017-06-01

    This paper presents strategies for an efficient and dynamic transmission power control technique, in order to reduce packet drop and hence energy consumption of power-hungry sensor nodes operated in highly non-linear channel conditions of Wireless Sensor Networks. Besides, we also focus to prolong network lifetime and scalability by designing cluster-based network structure. Specifically we consider weight-based clustering approach wherein, minimum significant node is chosen as Cluster Head (CH) which is computed stemmed from the factors distance, remaining residual battery power and received signal strength (RSS). Further, transmission power control schemes to fit into dynamic channel conditions are meticulously implemented using Hidden Markov Model (HMM) where probability transition matrix is formulated based on the observed RSS measurements. Typically, CH estimates initial transmission power of its cluster members (CMs) from RSS using HMM and broadcast this value to its CMs for initialising their power value. Further, if CH finds that there are variations in link quality and RSS of the CMs, it again re-computes and optimises the transmission power level of the nodes using HMM to avoid packet loss due noise interference. We have demonstrated our simulation results to prove that our technique efficiently controls the power levels of sensing nodes to save significant quantity of energy for different sized network.

  1. Model-Based Closed-Loop Glucose Control in Type 1 Diabetes: The DiaCon Experience

    DEFF Research Database (Denmark)

    Schmidt, Signe; Boiroux, Dimitri; Duun-Henriksen, Anne Katrine

    2013-01-01

    Background: To improve type 1 diabetes mellitus (T1DM) management, we developed a model predictive control (MPC) algorithm for closed-loop (CL) glucose control based on a linear second-order deterministic-stochastic model. The deterministic part of the model is specified by three patient-specific......Background: To improve type 1 diabetes mellitus (T1DM) management, we developed a model predictive control (MPC) algorithm for closed-loop (CL) glucose control based on a linear second-order deterministic-stochastic model. The deterministic part of the model is specified by three patient...... crossover studies. Study 1 compared CL with open-loop (OL) control. Study 2 compared glucose control after CL initiation in the euglycemic (CL-Eu) and hyperglycemic (CL-Hyper) ranges, respectively. Patients were studied from 22:00–07:00 on two separate nights. Results: Each study included six T1DM patients...

  2. Stochastic Control - External Models

    DEFF Research Database (Denmark)

    Poulsen, Niels Kjølstad

    2005-01-01

    This note is devoted to control of stochastic systems described in discrete time. We are concerned with external descriptions or transfer function model, where we have a dynamic model for the input output relation only (i.e.. no direct internal information). The methods are based on LTI systems...

  3. Model-Based Engine Control Architecture with an Extended Kalman Filter

    Science.gov (United States)

    Csank, Jeffrey T.; Connolly, Joseph W.

    2016-01-01

    This paper discusses the design and implementation of an extended Kalman filter (EKF) for model-based engine control (MBEC). Previously proposed MBEC architectures feature an optimal tuner Kalman Filter (OTKF) to produce estimates of both unmeasured engine parameters and estimates for the health of the engine. The success of this approach relies on the accuracy of the linear model and the ability of the optimal tuner to update its tuner estimates based on only a few sensors. Advances in computer processing are making it possible to replace the piece-wise linear model, developed off-line, with an on-board nonlinear model running in real-time. This will reduce the estimation errors associated with the linearization process, and is typically referred to as an extended Kalman filter. The nonlinear extended Kalman filter approach is applied to the Commercial Modular Aero-Propulsion System Simulation 40,000 (C-MAPSS40k) and compared to the previously proposed MBEC architecture. The results show that the EKF reduces the estimation error, especially during transient operation.

  4. Iterated non-linear model predictive control based on tubes and contractive constraints.

    Science.gov (United States)

    Murillo, M; Sánchez, G; Giovanini, L

    2016-05-01

    This paper presents a predictive control algorithm for non-linear systems based on successive linearizations of the non-linear dynamic around a given trajectory. A linear time varying model is obtained and the non-convex constrained optimization problem is transformed into a sequence of locally convex ones. The robustness of the proposed algorithm is addressed adding a convex contractive constraint. To account for linearization errors and to obtain more accurate results an inner iteration loop is added to the algorithm. A simple methodology to obtain an outer bounding-tube for state trajectories is also presented. The convergence of the iterative process and the stability of the closed-loop system are analyzed. The simulation results show the effectiveness of the proposed algorithm in controlling a quadcopter type unmanned aerial vehicle. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

  5. Agent-Based Modeling for Testing and Designing Novel Decentralized Command and Control System Paradigms

    National Research Council Canada - National Science Library

    Bonabeau, Eric; Hunt, Carl W; Gaudiano, Paolo

    2003-01-01

    Agent-based modeling (ABM) is a recent simulation modeling technique that consists of modeling a system from the bottom up, capturing the interactions taking place between the system's constituent units...

  6. Model-Based Design of Brushless DC Motor Control and Motion Control Modelling for RoboCup SSL Robots

    OpenAIRE

    Li, Xiaotian

    2015-01-01

    Over the recent years, the RoboCup competition has grown popular and attracted more and more domestic and international universities, and the levels of the teams increase every year. In Small Size League (SSL) competition, besides a good strategy system, the precision of the robots’ actions is also of vital importance in order to achieve high performance. Thus, a highly accurate and stable motion control system is needed to drive the robots to move in accordance with the planned trajectory. C...

  7. The optimal dynamic immunization under a controlled heterogeneous node-based SIRS model

    Science.gov (United States)

    Yang, Lu-Xing; Draief, Moez; Yang, Xiaofan

    2016-05-01

    Dynamic immunizations, under which the state of the propagation network of electronic viruses can be changed by adjusting the control measures, are regarded as an alternative to static immunizations. This paper addresses the optimal dynamical immunization under the widely accepted SIRS assumption. First, based on a controlled heterogeneous node-based SIRS model, an optimal control problem capturing the optimal dynamical immunization is formulated. Second, the existence of an optimal dynamical immunization scheme is shown, and the corresponding optimality system is derived. Next, some numerical examples are given to show that an optimal immunization strategy can be worked out by numerically solving the optimality system, from which it is found that the network topology has a complex impact on the optimal immunization strategy. Finally, the difference between a payoff and the minimum payoff is estimated in terms of the deviation of the corresponding immunization strategy from the optimal immunization strategy. The proposed optimal immunization scheme is justified, because it can achieve a low level of infections at a low cost.

  8. Simulation model of ANN based maximum power point tracking controller for solar PV system

    Energy Technology Data Exchange (ETDEWEB)

    Rai, Anil K.; Singh, Bhupal [Department of Electrical and Electronics Engineering, Ajay Kumar Garg Engineering College, Ghaziabad 201009 (India); Kaushika, N.D.; Agarwal, Niti [School of Research and Development, Bharati Vidyapeeth College of Engineering, A-4 Paschim Vihar, New Delhi 110063 (India)

    2011-02-15

    In this paper the simulation model of an artificial neural network (ANN) based maximum power point tracking controller has been developed. The controller consists of an ANN tracker and the optimal control unit. The ANN tracker estimates the voltages and currents corresponding to a maximum power delivered by solar PV (photovoltaic) array for variable cell temperature and solar radiation. The cell temperature is considered as a function of ambient air temperature, wind speed and solar radiation. The tracker is trained employing a set of 124 patterns using the back propagation algorithm. The mean square error of tracker output and target values is set to be of the order of 10{sup -5} and the successful convergent of learning process takes 1281 epochs. The accuracy of the ANN tracker has been validated by employing different test data sets. The control unit uses the estimates of the ANN tracker to adjust the duty cycle of the chopper to optimum value needed for maximum power transfer to the specified load. (author)

  9. Learning-based Nonlinear Model Predictive Control to Improve Vision-based Mobile Robot Path Tracking

    Science.gov (United States)

    2015-07-01

    corresponding cost function to be J(u) = ( xd − x)TQx ( xd − x) + uTRu, (20) where Qx ∈ RKnx×Knx is positive semi-definite, R and u are as in (3), xd is a...sequence of desired states, xd = ( xd ,k+1, . . . , xd ,k+K), x is a sequence of predicted states, x = (xk+1, . . . ,xk+K), and K is the given prediction...vact,k−1+b, ωact,k−1+b), based ωk θk vk xd ,i−1 xd ,i xd ,i+1 xk yk Figure 5: Definition of the robot velocities, vk and ωk, and three pose variables

  10. Adjoint-based model predictive control of wind farms : Beyond the quasi steady-state power maximization

    NARCIS (Netherlands)

    Vali, M.; Petrović, Vlaho; Boersma, S.; van Wingerden, J.W.; Kuhn, Martin; Dochain, Denis; Henrion, Didier; Peaucelle, Dimitri

    2017-01-01

    In this paper, we extend our closed-loop optimal control framework for wind farms to minimize wake-induced power losses. We develop an adjoint-based model predictive controller which employs a medium-fidelity 2D dynamic wind farm model. The wind turbine axial induction factors are considered here

  11. Robust self-triggered model predictive control for constrained discrete-time LTI systems based on homothetic tubes

    NARCIS (Netherlands)

    Aydiner, E.; Brunner, F.D.; Heemels, W.P.M.H.; Allgower, F.

    2015-01-01

    In this paper we present a robust self-triggered model predictive control (MPC) scheme for discrete-time linear time-invariant systems subject to input and state constraints and additive disturbances. In self-triggered model predictive control, at every sampling instant an optimization problem based

  12. A novel model-based control strategy for aerobic filamentous fungal fed-batch fermentation processes.

    Science.gov (United States)

    Mears, Lisa; Stocks, Stuart M; Albaek, Mads O; Cassells, Benny; Sin, Gürkan; Gernaey, Krist V

    2017-07-01

    A novel model-based control strategy has been developed for filamentous fungal fed-batch fermentation processes. The system of interest is a pilot scale (550 L) filamentous fungus process operating at Novozymes A/S. In such processes, it is desirable to maximize the total product achieved in a batch in a defined process time. In order to achieve this goal, it is important to maximize both the product concentration, and also the total final mass in the fed-batch system. To this end, we describe the development of a control strategy which aims to achieve maximum tank fill, while avoiding oxygen limited conditions. This requires a two stage approach: (i) calculation of the tank start fill; and (ii) on-line control in order to maximize fill subject to oxygen transfer limitations. First, a mechanistic model was applied off-line in order to determine the appropriate start fill for processes with four different sets of process operating conditions for the stirrer speed, headspace pressure, and aeration rate. The start fills were tested with eight pilot scale experiments using a reference process operation. An on-line control strategy was then developed, utilizing the mechanistic model which is recursively updated using on-line measurements. The model was applied in order to predict the current system states, including the biomass concentration, and to simulate the expected future trajectory of the system until a specified end time. In this way, the desired feed rate is updated along the progress of the batch taking into account the oxygen mass transfer conditions and the expected future trajectory of the mass. The final results show that the target fill was achieved to within 5% under the maximum fill when tested using eight pilot scale batches, and over filling was avoided. The results were reproducible, unlike the reference experiments which show over 10% variation in the final tank fill, and this also includes over filling. The variance of the final tank fill is

  13. TRBAC:基于信任的访问控制模型%TRBAC: Trust Based Access Control Model

    Institute of Scientific and Technical Information of China (English)

    刘武; 段海新; 张洪; 任萍; 吴建平

    2011-01-01

    访问控制是根据网络用户的身份或属性,对该用户执行某些操作或访问某些网络资源进行控制的过程.对现有访问控制模型进行分析,并针对其不足对RBAC模型进行了扩展,提出了基于信任的访问控制模型TRBAC(trust based access control model).该模型可以提供更加安全、灵活以及细粒度的动态访问授权机制,从而提高授权机制的安全性与可靠性.%Access control is a process which controls users to execute some operations or access some network resources according to the users' identity or attribution. The discretionary access control and mandatory access control are two main access control modes which are broadly used in secure operating systems. Discretionary access control is based on user identity and/or groups and mandatory access control is usually based on sensitivity labels. Neither of these two modes can completely satisfy the requirements of all access control. Discretionary access control is too loose to restrict the propagation of privileges while mandatory access control is too rigid to use flexibly. This paper analyzes current access control models, and extends the RBAC (role based access control) model aiming at its deficiency, and based on which we propose a trust based access control model (TRBAC). The TRBAC model can provide more security, flexible and fine-grained dynamic access control mechanism, and therefore improve both the security and the reliability of authorization mechanism.

  14. Modeling T cell antigen discrimination based on feedback control of digital ERK responses.

    Directory of Open Access Journals (Sweden)

    2005-11-01

    Full Text Available T-lymphocyte activation displays a remarkable combination of speed, sensitivity, and discrimination in response to peptide-major histocompatibility complex (pMHC ligand engagement of clonally distributed antigen receptors (T cell receptors or TCRs. Even a few foreign pMHCs on the surface of an antigen-presenting cell trigger effective signaling within seconds, whereas 1 x 10(5-1 x 10(6 self-pMHC ligands that may differ from the foreign stimulus by only a single amino acid fail to elicit this response. No existing model accounts for this nearly absolute distinction between closely related TCR ligands while also preserving the other canonical features of T-cell responses. Here we document the unexpected highly amplified and digital nature of extracellular signal-regulated kinase (ERK activation in T cells. Based on this observation and evidence that competing positive- and negative-feedback loops contribute to TCR ligand discrimination, we constructed a new mathematical model of proximal TCR-dependent signaling. The model made clear that competition between a digital positive feedback based on ERK activity and an analog negative feedback involving SH2 domain-containing tyrosine phosphatase (SHP-1 was critical for defining a sharp ligand-discrimination threshold while preserving a rapid and sensitive response. Several nontrivial predictions of this model, including the notion that this threshold is highly sensitive to small changes in SHP-1 expression levels during cellular differentiation, were confirmed by experiment. These results combining computation and experiment reveal that ligand discrimination by T cells is controlled by the dynamics of competing feedback loops that regulate a high-gain digital amplifier, which is itself modulated during differentiation by alterations in the intracellular concentrations of key enzymes. The organization of the signaling network that we model here may be a prototypic solution to the problem of achieving

  15. Design and implementation of fuzzy-PD controller based on relation models: A cross-entropy optimization approach

    Science.gov (United States)

    Anisimov, D. N.; Dang, Thai Son; Banerjee, Santo; Mai, The Anh

    2017-07-01

    In this paper, an intelligent system use fuzzy-PD controller based on relation models is developed for a two-wheeled self-balancing robot. Scaling factors of the fuzzy-PD controller are optimized by a Cross-Entropy optimization method. A linear Quadratic Regulator is designed to bring a comparison with the fuzzy-PD controller by control quality parameters. The controllers are ported and run on STM32F4 Discovery Kit based on the real-time operating system. The experimental results indicate that the proposed fuzzy-PD controller runs exactly on embedded system and has desired performance in term of fast response, good balance and stabilize.

  16. A Multi-Agent Traffic Control Model Based on Distributed System

    Directory of Open Access Journals (Sweden)

    Qian WU

    2014-06-01

    Full Text Available With the development of urbanization construction, urban travel has become a quite thorny and imminent problem. Some previous researches on the large urban traffic systems easily change into NPC problems. We purpose a multi-agent inductive control model based on the distributed approach. To describe the real traffic scene, this model designs four different types of intelligent agents, i.e. we regard each lane, route, intersection and traffic region as different types of intelligent agents. Each agent can achieve the real-time traffic data from its neighbor agents, and decision-making agents establish real-time traffic signal plans through the communication between local agents and their neighbor agents. To evaluate the traffic system, this paper takes the average delay, the stopped time and the average speed as performance parameters. Finally, the distributed multi-agent is simulated on the VISSIM simulation platform, the simulation results show that the multi-agent system is more effective than the adaptive control system in solving the traffic congestion.

  17. Poly lactic acid based injectable delivery systems for controlled release of a model protein, lysozyme.

    Science.gov (United States)

    Al-Tahami, Khaled; Meyer, Amanda; Singh, Jagdish

    2006-02-01

    The objective of this study was to evaluate the critical formulation parameters (i.e., polymer concentration, polymer molecular weight, and solvent nature) affecting the controlled delivery of a model protein, lysozyme, from injectable polymeric implants. The conformational stability and biological activity of the released lysozyme were also investigated. Three formulations containing 10%, 20%, and 30% (w/v) poly lactic acid (PLA) in triacetin were investigated. It was found that increasing polymer concentration in the formulations led to a lower burst effect and a slower release rate. Formulation with a high molecular weight polymer showed a greater burst effect as compared to those containing low molecular weight. Conformational stability and biological activity of released samples were studied by differential scanning calorimeter and enzyme activity assay, respectively. The released samples had significantly (P solution kept at same conditions). Increasing polymer concentration increased both the conformational stability and the biological activity of released lysozyme. In conclusion, phase sensitive polymer-based delivery systems were able to deliver a model protein, lysozyme, in a conformationally stable and biologically active form at a controlled rate over an extended period.

  18. A population-feedback control based algorithm for well trajectory optimization using proxy model

    Directory of Open Access Journals (Sweden)

    Javad Kasravi

    2017-04-01

    Full Text Available Wellbore instability is one of the concerns in the field of drilling engineering. This phenomenon is affected by several factors such as azimuth, inclination angle, in-situ stress, mud weight, and rock strength parameters. Among these factors, azimuth, inclination angle, and mud weight are controllable. The objective of this paper is to introduce a new procedure based on elastoplastic theory in wellbore stability solution to determine the optimum well trajectory and global minimum mud pressure required (GMMPR. Genetic algorithm (GA was applied as a main optimization engine that employs proportional feedback controller to obtain the minimum mud pressure required (MMPR. The feedback function repeatedly calculated and updated the error between the simulated and set point of normalized yielded zone area (NYZA. To reduce computation expenses, an artificial neural network (ANN was used as a proxy (surrogate model to approximate the behavior of the actual wellbore model. The methodology was applied to a directional well in southwestern Iranian oilfield. The results demonstrated that the error between the predicted GMMPR and practical safe mud pressure was 4% for elastoplastic method, and 22% for conventional elastic solution.

  19. Face Recognition for Access Control Systems Combining Image-Difference Features Based on a Probabilistic Model

    Science.gov (United States)

    Miwa, Shotaro; Kage, Hiroshi; Hirai, Takashi; Sumi, Kazuhiko

    We propose a probabilistic face recognition algorithm for Access Control System(ACS)s. Comparing with existing ACSs using low cost IC-cards, face recognition has advantages in usability and security that it doesn't require people to hold cards over scanners and doesn't accept imposters with authorized cards. Therefore face recognition attracts more interests in security markets than IC-cards. But in security markets where low cost ACSs exist, price competition is important, and there is a limitation on the quality of available cameras and image control. Therefore ACSs using face recognition are required to handle much lower quality images, such as defocused and poor gain-controlled images than high security systems, such as immigration control. To tackle with such image quality problems we developed a face recognition algorithm based on a probabilistic model which combines a variety of image-difference features trained by Real AdaBoost with their prior probability distributions. It enables to evaluate and utilize only reliable features among trained ones during each authentication, and achieve high recognition performance rates. The field evaluation using a pseudo Access Control System installed in our office shows that the proposed system achieves a constant high recognition performance rate independent on face image qualities, that is about four times lower EER (Equal Error Rate) under a variety of image conditions than one without any prior probability distributions. On the other hand using image difference features without any prior probabilities are sensitive to image qualities. We also evaluated PCA, and it has worse, but constant performance rates because of its general optimization on overall data. Comparing with PCA, Real AdaBoost without any prior distribution performs twice better under good image conditions, but degrades to a performance as good as PCA under poor image conditions.

  20. Model predictive control-based scheduler for repetitive discrete event systems with capacity constraints

    Directory of Open Access Journals (Sweden)

    Hiroyuki Goto

    2013-07-01

    Full Text Available A model predictive control-based scheduler for a class of discrete event systems is designed and developed. We focus on repetitive, multiple-input, multiple-output, and directed acyclic graph structured systems on which capacity constraints can be imposed. The target system’s behaviour is described by linear equations in max-plus algebra, referred to as state-space representation. Assuming that the system’s performance can be improved by paying additional cost, we adjust the system parameters and determine control inputs for which the reference output signals can be observed. The main contribution of this research is twofold, 1: For systems with capacity constraints, we derived an output prediction equation as functions of adjustable variables in a recursive form, 2: Regarding the construct for the system’s representation, we improved the structure to accomplish general operations which are essential for adjusting the system parameters. The result of numerical simulation in a later section demonstrates the effectiveness of the developed controller.

  1. Model-based rational feedback controller design for closed-loop deep brain stimulation of Parkinson's disease

    Science.gov (United States)

    Gorzelic, P.; Schiff, S. J.; Sinha, A.

    2013-04-01

    Objective. To explore the use of classical feedback control methods to achieve an improved deep brain stimulation (DBS) algorithm for application to Parkinson's disease (PD). Approach. A computational model of PD dynamics was employed to develop model-based rational feedback controller design. The restoration of thalamocortical relay capabilities to patients suffering from PD is formulated as a feedback control problem with the DBS waveform serving as the control input. Two high-level control strategies are tested: one that is driven by an online estimate of thalamic reliability, and another that acts to eliminate substantial decreases in the inhibition from the globus pallidus interna (GPi) to the thalamus. Control laws inspired by traditional proportional-integral-derivative (PID) methodology are prescribed for each strategy and simulated on this computational model of the basal ganglia network. Main Results. For control based upon thalamic reliability, a strategy of frequency proportional control with proportional bias delivered the optimal control achieved for a given energy expenditure. In comparison, control based upon synaptic inhibitory output from the GPi performed very well in comparison with those of reliability-based control, with considerable further reduction in energy expenditure relative to that of open-loop DBS. The best controller performance was amplitude proportional with derivative control and integral bias, which is full PID control. We demonstrated how optimizing the three components of PID control is feasible in this setting, although the complexity of these optimization functions argues for adaptive methods in implementation. Significance. Our findings point to the potential value of model-based rational design of feedback controllers for Parkinson's disease.

  2. Modeling disturbance-based native invasive species control and its implications for management.

    Science.gov (United States)

    Shackelford, Nancy; Renton, Michael; Perring, Michael P; Hobbs, Richard J

    2013-09-01

    Shifts in disturbance regime have often been linked to invasion in systems by native and nonnative species. This process can have negative effects on biodiversity and ecosystem function. Degradation may be ameliorated by the reinstatement of the disturbance regimes, such as the reintroduction of fire in pyrogenic systems. Modeling is one method through which potential outcomes of different regimes can be investigated. We created a population model to examine the control of a native invasive that is expanding and increasing in abundance due to suppressed fire. Our model, parameterized with field data from a case study of the tree Allocasuarina huegeliana in Australian sandplain heath, simulated different fire return intervals with and without the additional management effort of mechanical removal of the native invader. Population behavior under the different management options was assessed, and general estimates of potential biodiversity impacts were compared. We found that changes in fire return intervals made no significant difference in the increase and spread of the population. However, decreased fire return intervals did lower densities reached in the simulated heath patch as well as the estimated maximum biodiversity impacts. When simulating both mechanical removal and fire, we found that the effects of removal depended on the return intervals and the strategy used. Increase rates were not significantly affected by any removal strategy. However, we found that removal, particularly over the whole patch rather than focusing on satellite populations, could decrease average and maximum densities reached and thus decrease the predicted biodiversity impacts. Our simulation model shows that disturbance-based management has the potential to control native invasion in cases where shifted disturbance is the likely driver of the invasion. The increased knowledge gained through the modeling methods outlined can inform management decisions in fire regime planning that

  3. Nonlinear model predictive control of a wave energy converter based on differential flatness parameterisation

    Science.gov (United States)

    Li, Guang

    2017-01-01

    This paper presents a fast constrained optimization approach, which is tailored for nonlinear model predictive control of wave energy converters (WEC). The advantage of this approach relies on its exploitation of the differential flatness of the WEC model. This can reduce the dimension of the resulting nonlinear programming problem (NLP) derived from the continuous constrained optimal control of WEC using pseudospectral method. The alleviation of computational burden using this approach helps to promote an economic implementation of nonlinear model predictive control strategy for WEC control problems. The method is applicable to nonlinear WEC models, nonconvex objective functions and nonlinear constraints, which are commonly encountered in WEC control problems. Numerical simulations demonstrate the efficacy of this approach.

  4. Assess and Predict Automatic Generation Control Performances for Thermal Power Generation Units Based on Modeling Techniques

    Science.gov (United States)

    Zhao, Yan; Yang, Zijiang; Gao, Song; Liu, Jinbiao

    2018-02-01

    Automatic generation control(AGC) is a key technology to maintain real time power generation and load balance, and to ensure the quality of power supply. Power grids require each power generation unit to have a satisfactory AGC performance, being specified in two detailed rules. The two rules provide a set of indices to measure the AGC performance of power generation unit. However, the commonly-used method to calculate these indices is based on particular data samples from AGC responses and will lead to incorrect results in practice. This paper proposes a new method to estimate the AGC performance indices via system identification techniques. In addition, a nonlinear regression model between performance indices and load command is built in order to predict the AGC performance indices. The effectiveness of the proposed method is validated through industrial case studies.

  5. Optimal control of transverse mode coupling instability based on the two particle model

    International Nuclear Information System (INIS)

    Ogata, Atsushi

    1985-01-01

    The optimal regulator design technique is applied to asymptotically stabilize the transverse mode coupling instability of a storage ring. The state equations are based on the two particle model. These are a pair of equation sets, one for the first and one for the second half of the synchrotron phase. Each set consists of first-order difference equations in vector-matrix form, with time step equal to the revolution time of the ring. Solution of the discrete Riccati equation gives the optimal gain matrix of the transverse feedback. Computer simulations are carried out to verify its effectiveness. Some modifications necessary to apply it to the real accelerator operation are made. The old methods, the classical output feedback and the reactive feedback, are interpreted from the viewpoint of the optimal control. (orig.)

  6. Control Theory Perspective of Effects-Based Thinking and Operations: Modelling "Operations" as a Feedback Control System

    National Research Council Canada - National Science Library

    Farrell, Philip S

    2007-01-01

    This paper explores operations that involve effects-based thinking (EBT) using Control Theory techniques in order to highlight the concept's fundamental characteristics in a simple and straightforward manner...

  7. Interface design and human factors considerations for model-based tight glycemic control in critical care.

    Science.gov (United States)

    Ward, Logan; Steel, James; Le Compte, Aaron; Evans, Alicia; Tan, Chia-Siong; Penning, Sophie; Shaw, Geoffrey M; Desaive, Thomas; Chase, J Geoffrey

    2012-01-01

    Tight glycemic control (TGC) has shown benefits but has been difficult to implement. Model-based methods and computerized protocols offer the opportunity to improve TGC quality and compliance. This research presents an interface design to maximize compliance, minimize real and perceived clinical effort, and minimize error based on simple human factors and end user input. The graphical user interface (GUI) design is presented by construction based on a series of simple, short design criteria based on fundamental human factors engineering and includes the use of user feedback and focus groups comprising nursing staff at Christchurch Hospital. The overall design maximizes ease of use and minimizes (unnecessary) interaction and use. It is coupled to a protocol that allows nurse staff to select measurement intervals and thus self-manage workload. The overall GUI design is presented and requires only one data entry point per intervention cycle. The design and main interface are heavily focused on the nurse end users who are the predominant users, while additional detailed and longitudinal data, which are of interest to doctors guiding overall patient care, are available via tabs. This dichotomy of needs and interests based on the end user's immediate focus and goals shows how interfaces must adapt to offer different information to multiple types of users. The interface is designed to minimize real and perceived clinical effort, and ongoing pilot trials have reported high levels of acceptance. The overall design principles, approach, and testing methods are based on fundamental human factors principles designed to reduce user effort and error and are readily generalizable. © 2012 Diabetes Technology Society.

  8. A Model-driven Role-based Access Control for SQL Databases

    Directory of Open Access Journals (Sweden)

    Raimundas Matulevičius

    2015-07-01

    Full Text Available Nowadays security has become an important aspect in information systems engineering. A mainstream method for information system security is Role-based Access Control (RBAC, which restricts system access to authorised users. While the benefits of RBAC are widely acknowledged, the implementation and administration of RBAC policies remains a human intensive activity, typically postponed until the implementation and maintenance phases of system development. This deferred security engineering approach makes it difficult for security requirements to be accurately captured and for the system’s implementation to be kept aligned with these requirements as the system evolves. In this paper we propose a model-driven approach to manage SQL database access under the RBAC paradigm. The starting point of the approach is an RBAC model captured in SecureUML. This model is automatically translated to Oracle Database views and instead-of triggers code, which implements the security constraints. The approach has been fully instrumented as a prototype and its effectiveness has been validated by means of a case study.

  9. Nonrigid, Linear Plasma Response Model Based on Perturbed Equilibria for Axisymmetric Tokamak Control Design

    International Nuclear Information System (INIS)

    Welander, A.S.; Deranian, R.D.; Humphreys, D.A.; Leuer, J.A.; Walker, M.L.

    2005-01-01

    Tokamak control design relies on an accurate linear model of the plasma response, which can often dominate the local field variations in regions under active feedback control. For example, when fluxes at selected points on the plasma boundary are regulated in DIII-D, the plasma response to a change in a coil current gives rise to a flux change which can be larger than and opposite to the flux change caused by the coil alone.In the past, rigid plasma models have been used for linear stability and shape control design. In a rigid model, the plasma current profile is considered fixed and moves rigidly in response to control coils to maintain radial and vertical force balance. In a nonrigid model, however, changes in the plasma shape and current profile are taken into account. Such models are expected to be important for future advanced tokamak control design. The present work describes development of a nonrigid plasma response model for high-accuracy multivariable control design and provides comparisons of model predictions against DIII-D experimental data. The linear perturbed plasma response model is calculated rapidly from an existing equilibrium solution

  10. Model predictive control of the solid oxide fuel cell stack temperature with models based on experimental data

    Science.gov (United States)

    Pohjoranta, Antti; Halinen, Matias; Pennanen, Jari; Kiviaho, Jari

    2015-03-01

    Generalized predictive control (GPC) is applied to control the maximum temperature in a solid oxide fuel cell (SOFC) stack and the temperature difference over the stack. GPC is a model predictive control method and the models utilized in this work are ARX-type (autoregressive with extra input), multiple input-multiple output, polynomial models that were identified from experimental data obtained from experiments with a complete SOFC system. The proposed control is evaluated by simulation with various input-output combinations, with and without constraints. A comparison with conventional proportional-integral-derivative (PID) control is also made. It is shown that if only the stack maximum temperature is controlled, a standard PID controller can be used to obtain output performance comparable to that obtained with the significantly more complex model predictive controller. However, in order to control the temperature difference over the stack, both the stack minimum and the maximum temperature need to be controlled and this cannot be done with a single PID controller. In such a case the model predictive controller provides a feasible and effective solution.

  11. Flow Management to Control Excessive Growth of Macrophytes - An Assessment Based on Habitat Suitability Modeling.

    Science.gov (United States)

    Ochs, Konstantin; Rivaes, Rui P; Ferreira, Teresa; Egger, Gregory

    2018-01-01

    Mediterranean rivers in intensive agricultural watersheds usually display outgrowths of macrophytes - notably alien species - due to a combination of high concentrations of nutrients in the water runoff and low flows resulting from water abstraction for irrigation. Standard mechanical and chemical control is used to mitigate the problems associated with excessive growth of plant biomass: mainly less drainage capacity and higher flood risk. However, such control measures are cost and labor-intensive and do not present long-term efficiency. Although the high sensitivity of aquatic vegetation to instream hydraulic conditions is well known, management approaches based on flow management remain relatively unexplored. The aim of our study was therefore to apply physical habitat simulation techniques promoted by the Instream Flow Incremental Method (IFIM) to aquatic macrophytes - the first time it has been applied in this context - in order to model shifts in habitat suitability under different flow scenarios in the Sorraia river in central Portugal. We used this approach to test whether the risk of invasion and channel encroachment by nuisance species can be controlled by setting minimum annual flows. We used 960 randomly distributed survey points to analyze the habitat suitability for the most important aquatic species (including the invasive Brazilian milfoil Myriophyllum aquaticum , Sparganium erectum , and Potamogeton crispus ) in regard to the physical parameters 'flow velocity,' 'water depth,' and 'substrate size'. We chose the lowest discharge period of the year in order to assess the hydraulic conditions while disturbances were at a low-point, thus allowing aquatic vegetation establishment and subsistence. We then used the two-dimensional hydraulic River2D software to model the potential habitat availability for different flow conditions based on the site-specific habitat suitability index for each physical parameter and species. Our results show that the growth

  12. Flow Management to Control Excessive Growth of Macrophytes – An Assessment Based on Habitat Suitability Modeling

    Science.gov (United States)

    Ochs, Konstantin; Rivaes, Rui P.; Ferreira, Teresa; Egger, Gregory

    2018-01-01

    Mediterranean rivers in intensive agricultural watersheds usually display outgrowths of macrophytes – notably alien species – due to a combination of high concentrations of nutrients in the water runoff and low flows resulting from water abstraction for irrigation. Standard mechanical and chemical control is used to mitigate the problems associated with excessive growth of plant biomass: mainly less drainage capacity and higher flood risk. However, such control measures are cost and labor-intensive and do not present long-term efficiency. Although the high sensitivity of aquatic vegetation to instream hydraulic conditions is well known, management approaches based on flow management remain relatively unexplored. The aim of our study was therefore to apply physical habitat simulation techniques promoted by the Instream Flow Incremental Method (IFIM) to aquatic macrophytes – the first time it has been applied in this context – in order to model shifts in habitat suitability under different flow scenarios in the Sorraia river in central Portugal. We used this approach to test whether the risk of invasion and channel encroachment by nuisance species can be controlled by setting minimum annual flows. We used 960 randomly distributed survey points to analyze the habitat suitability for the most important aquatic species (including the invasive Brazilian milfoil Myriophyllum aquaticum, Sparganium erectum, and Potamogeton crispus) in regard to the physical parameters ‘flow velocity,’ ‘water depth,’ and ‘substrate size’. We chose the lowest discharge period of the year in order to assess the hydraulic conditions while disturbances were at a low-point, thus allowing aquatic vegetation establishment and subsistence. We then used the two-dimensional hydraulic River2D software to model the potential habitat availability for different flow conditions based on the site-specific habitat suitability index for each physical parameter and species. Our results show

  13. A lattice hydrodynamic model based on delayed feedback control considering the effect of flow rate difference

    Science.gov (United States)

    Wang, Yunong; Cheng, Rongjun; Ge, Hongxia

    2017-08-01

    In this paper, a lattice hydrodynamic model is derived considering not only the effect of flow rate difference but also the delayed feedback control signal which including more comprehensive information. The control method is used to analyze the stability of the model. Furthermore, the critical condition for the linear steady traffic flow is deduced and the numerical simulation is carried out to investigate the advantage of the proposed model with and without the effect of flow rate difference and the control signal. The results are consistent with the theoretical analysis correspondingly.

  14. A Reactive Power Based Reference Model for Adaptive Control Strategy in a SEIG

    Directory of Open Access Journals (Sweden)

    M. A. Taghikhani

    2018-02-01

    Full Text Available In this paper, a new control strategy is proposed for a three-phase squirrel-cage self-excited induction generator (SEIG connected to a variable speed wind turbine in autonomous mode. In order to improve the dynamic performance of the mentioned vector control system, a model reference adaptive controller is used for online rotor time constant estimation. Thus, the main drawbacks of this method, which include the effects of the changes in machine parameters on rotor flux estimation, slip speed, the creation of instability problems and the system leaving vector control mode, are resolved. In this control strategy, a PI controller is used to control the dc voltage and three similar hysteresis current controllers (HCC are used to control the switching of IGBTs. The results of the dynamic simulation indicate the desirable performance of the proposed system.

  15. Model-based dynamic resistive wall mode identification and feedback control in the DIII-D tokamak

    International Nuclear Information System (INIS)

    In, Y.; Kim, J.S.; Edgell, D.H.; Strait, E.J.; Humphreys, D.A.; Walker, M.L.; Jackson, G.L.; Chu, M.S.; Johnson, R.; La Haye, R.J.; Okabayashi, M.; Garofalo, A.M.; Reimerdes, H.

    2006-01-01

    A new model-based dynamic resistive wall mode (RWM) identification and feedback control algorithm has been developed. While the overall RWM structure can be detected by a model-based matched filter in a similar manner to a conventional sensor-based scheme, it is significantly influenced by edge-localized-modes (ELMs). A recent study suggested that such ELM noise might cause the RWM control system to respond in an undesirable way. Thus, an advanced algorithm to discriminate ELMs from RWM has been incorporated into this model-based control scheme, dynamic Kalman filter. Specifically, the DIII-D [J. L. Luxon, Nucl. Fusion 42, 614 (2002)] resistive vessel wall was modeled in two ways: picture frame model or eigenmode treatment. Based on the picture frame model, the first real-time, closed-loop test results of the Kalman filter algorithms during DIII-D experimental operation are presented. The Kalman filtering scheme was experimentally confirmed to be effective in discriminating ELMs from RWM. As a result, the actuator coils (I-coils) were rarely excited during ELMs, while retaining the sensitivity to RWM. However, finding an optimized set of operating parameters for the control algorithm requires further analysis and design. Meanwhile, a more advanced Kalman filter based on a more accurate eigenmode model has been developed. According to this eigenmode approach, significant improvement in terms of control performance has been predicted, while maintaining good ELM discrimination

  16. Tip-tilt disturbance model identification based on non-linear least squares fitting for Linear Quadratic Gaussian control

    Science.gov (United States)

    Yang, Kangjian; Yang, Ping; Wang, Shuai; Dong, Lizhi; Xu, Bing

    2018-05-01

    We propose a method to identify tip-tilt disturbance model for Linear Quadratic Gaussian control. This identification method based on Levenberg-Marquardt method conducts with a little prior information and no auxiliary system and it is convenient to identify the tip-tilt disturbance model on-line for real-time control. This identification method makes it easy that Linear Quadratic Gaussian control runs efficiently in different adaptive optics systems for vibration mitigation. The validity of the Linear Quadratic Gaussian control associated with this tip-tilt disturbance model identification method is verified by experimental data, which is conducted in replay mode by simulation.

  17. Control-Oriented First Principles-Based Model of a Diesel Generator

    DEFF Research Database (Denmark)

    Knudsen, Jesper Viese; Bendtsen, Jan Dimon; Andersen, Palle

    2016-01-01

    This paper presents the development of a control-oriented tenth-order nonlinear model of a diesel driven generator set, using first principles modeling. The model provides physical system insight, while keeping the complexity at a level where it can be a tool for future design of improved automatic...... generation control (AGC), by including important nonlinearities of the machine. The nonlinearities are, as would be expected for a generator, primarily of bilinear nature. Validation of the model is done with measurements on a 60 kVA/48 kW diesel driven generator set in island operation during steps...

  18. Stochastic Model Predictive Fault Tolerant Control Based on Conditional Value at Risk for Wind Energy Conversion System

    Directory of Open Access Journals (Sweden)

    Yun-Tao Shi

    2018-01-01

    Full Text Available Wind energy has been drawing considerable attention in recent years. However, due to the random nature of wind and high failure rate of wind energy conversion systems (WECSs, how to implement fault-tolerant WECS control is becoming a significant issue. This paper addresses the fault-tolerant control problem of a WECS with a probable actuator fault. A new stochastic model predictive control (SMPC fault-tolerant controller with the Conditional Value at Risk (CVaR objective function is proposed in this paper. First, the Markov jump linear model is used to describe the WECS dynamics, which are affected by many stochastic factors, like the wind. The Markov jump linear model can precisely model the random WECS properties. Second, the scenario-based SMPC is used as the controller to address the control problem of the WECS. With this controller, all the possible realizations of the disturbance in prediction horizon are enumerated by scenario trees so that an uncertain SMPC problem can be transformed into a deterministic model predictive control (MPC problem. Finally, the CVaR object function is adopted to improve the fault-tolerant control performance of the SMPC controller. CVaR can provide a balance between the performance and random failure risks of the system. The Min-Max performance index is introduced to compare the fault-tolerant control performance with the proposed controller. The comparison results show that the proposed method has better fault-tolerant control performance.

  19. An automotive vehicle dynamics prototyping platform based on a remote control model car

    OpenAIRE

    SOLMAZ, Selim; COŞKUN, Türker

    2013-01-01

    The use of a modified remote control (RC) model car as a vehicle dynamics testing and development platform is detailed. Vehicle dynamics testing is an important aspect of automotive engineering and it plays a key role during the design and tuning of active safety control systems. Considering the fact that such tests are conductedi at great expense, scaled model cars can potentially be used to help with the process to reduce the costs. With this view, we instrument and develop a stand...

  20. Integration of supervisory control synthesis in model-based systems engineering

    NARCIS (Netherlands)

    Baeten, J.C.M.; van de Mortel - Fronczak, J.M.; Rooda, J.E.

    2016-01-01

    Increasing system complexity, time to market and development costs reduction place higher demands on engineering processes. Formal models play an important role here because they enable the use of various model-based analyses and early integration techniques and tools. Engineering processes based on

  1. Integration of supervisory control synthesis in model-based systems engineering

    NARCIS (Netherlands)

    Baeten, J.C.M.; Mortel - Fronczak, van de J.M.; Rooda, J.E.

    2011-01-01

    Due to increasing system complexity, time-to-market and development costs reduction, there are higher demands on engineering processes. Model-based engineering can play a role here because it supports system development by enabling the use of various model-based analysis techniques and tools. As a

  2. Extended Model-Based Feedforward Compensation in L1 Adaptive Control for Mechanical Manipulators: Design and Experiments

    Directory of Open Access Journals (Sweden)

    Moussab eBennehar

    2015-12-01

    Full Text Available This paper deals with a new control scheme for Parallel Kinematic Manipulators (PKMs based on the L1 adaptive control theory. The original L1 adaptive controller is extended by including an adaptive loop based on the dynamics of the PKM. The additional model-based term is in charge of the compensation of the modeled nonlinear dynamics in the aim of improving the tracking performance. Moreover, the proposed controller is enhanced to reduce the internal forces, which may appear in the case of Redundantly Actuated PKMs (RA-PKMs. The generated control inputs are first regulated through a projection mechanism that reduces the antagonistic internal forces, before being applied to the manipulator. To validate the proposed controller and to show its effectiveness, real-time experiments are conducted on a new four degrees-of-freedom (4-DOFs RA-PKM developed in our laboratory.

  3. Wave Disturbance Reduction of a Floating Wind Turbine Using a Reference Model-based Predictive Control

    DEFF Research Database (Denmark)

    Christiansen, Søren; Tabatabaeipour, Seyed Mojtaba; Bak, Thomas

    2013-01-01

    pitch such that the state trajectories of the controlled system tracks the reference trajectories. The framework is demonstrated with a reference model of the desired closed-loop system undisturbed by the incident waves. This allows the wave-induced motion of the platform to be damped significantly...... compared to a baseline floating wind turbine controller at the cost of more pitch action....

  4. Modeling and Inverse Controller Design for an Unmanned Aerial Vehicle Based on the Self-Organizing Map

    Science.gov (United States)

    Cho, Jeongho; Principe, Jose C.; Erdogmus, Deniz; Motter, Mark A.

    2005-01-01

    The next generation of aircraft will have dynamics that vary considerably over the operating regime. A single controller will have difficulty to meet the design specifications. In this paper, a SOM-based local linear modeling scheme of an unmanned aerial vehicle (UAV) is developed to design a set of inverse controllers. The SOM selects the operating regime depending only on the embedded output space information and avoids normalization of the input data. Each local linear model is associated with a linear controller, which is easy to design. Switching of the controllers is done synchronously with the active local linear model that tracks the different operating conditions. The proposed multiple modeling and control strategy has been successfully tested in a simulator that models the LoFLYTE UAV.

  5. Modeling and sensitivity analysis of consensus algorithm based distributed hierarchical control for dc microgrids

    DEFF Research Database (Denmark)

    Meng, Lexuan; Dragicevic, Tomislav; Vasquez, Juan Carlos

    2015-01-01

    of dynamic study. The aim of this paper is to model the complete DC microgrid system in z-domain and perform sensitivity analysis for the complete system. A generalized modeling method is proposed and the system dynamics under different control parameters, communication topologies and communication speed...

  6. Optimal Active Power Control of A Wind Farm Equipped with Energy Storage System based on Distributed Model Predictive Control

    DEFF Research Database (Denmark)

    Zhao, Haoran; Wu, Qiuwei; Guo, Qinglai

    2016-01-01

    This paper presents the Distributed Model Predictive Control (D-MPC) of a wind farm equipped with fast and short-term Energy Storage System (ESS) for optimal active power control using the fast gradient method via dual decomposition. The primary objective of the D-MPC control of the wind farm...... is power reference tracking from system operators. Besides, by optimal distribution of the power references to individual wind turbines and the ESS unit, the wind turbine mechanical loads are alleviated. With the fast gradient method, the convergence rate of the DMPC is significantly improved which leads...

  7. Dynamic Phasors-Based Modeling and Stability Analysis of Droop-Controlled Inverters for Microgrid Applications

    DEFF Research Database (Denmark)

    Guo, Xiaoqiang; Lu, Zhigang; Wang, Baocheng

    2014-01-01

    models fail to predict the system instabilities. In order to solve the problem, a new modeling approach for inverter-dominated microgrids by using dynamic phasors is presented in this paper. Our findings indicate that the proposed dynamic phasor model is able to predict accurately the stability margins...... of the system, while the conventional reduced-order small signal model fails. In addition, the virtual ω-E frame power control method, which deals with the power coupling caused by the line impedance X/R characteristic, has also been chosen as an application example of the proposed modeling technique....

  8. Tracking Control of A Balancing Robot – A Model-Based Approach

    Directory of Open Access Journals (Sweden)

    Zaiczek Tobias

    2014-08-01

    Full Text Available This paper presents a control concept for a single-axle mobile robot moving on the horizontal plane. A mathematical model of the nonholonomic mechanical system is derived using Hamel's equations of motion. Subsequently, a concept for a tracking controller is described in detail. This controller keeps the mobile robot on a given reference trajectory while maintaining it in an upright position. The control objective is reached by a cascade control structure. By an appropriate input transformation, we are able to utilize an input-output linearization of a subsystem. For the remaining dynamics a linear set-point control law is presented. Finally, the performance of the implemented control law is illustrated by simulation results.

  9. Transaction-based building controls framework, Volume 2: Platform descriptive model and requirements

    Energy Technology Data Exchange (ETDEWEB)

    Akyol, Bora A. [Pacific Northwest National Laboratory (PNNL), Richland, WA (United States); Haack, Jereme N. [Pacific Northwest National Laboratory (PNNL), Richland, WA (United States); Carpenter, Brandon J. [Pacific Northwest National Laboratory (PNNL), Richland, WA (United States); Katipamula, Srinivas [Pacific Northwest National Laboratory (PNNL), Richland, WA (United States); Lutes, Robert G. [Pacific Northwest National Laboratory (PNNL), Richland, WA (United States); Hernandez, George [Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)

    2015-07-31

    Transaction-based Building Controls (TBC) offer a control systems platform that provides an agent execution environment that meets the growing requirements for security, resource utilization, and reliability. This report outlines the requirements for a platform to meet these needs and describes an illustrative/exemplary implementation.

  10. Model dynamic behaviour analysis with chaotic noise using fuzzy logic based control

    International Nuclear Information System (INIS)

    Silva, Glauco Antonio Santos da

    2002-01-01

    This work presents an application of fuzzy control on dynamical system models. It has been observed that fuzzy controllers maybe used as a good alternative to the classical PI controller, once it incorporates human line behavior. Three implication relationships were used for the fussy controllers, namely, Mamdani Min, Larsen and Takagi-Sugeno. Performance comparisons were made aiming at achieving the best performance for each model used. The PI controller was used as a minimum standard, once it has been present in the industry for many years, giving acceptable performances and some degree of reliability . Two kinds of perturbations were introduced in the models to test the controllers: a ramp and chaotic perturbations. The first one is a monotonic, standard increase of an input parameter. The second one presents non-periodicity and irregularity in such a way to be quite rough to the controllers. The chaotic signal, as an analysis tool to dynamical systems, is an interesting contribution of this work. As a general conclusion it can be said the best performance, in this work, was achieved by the Takagi-Sugeno fuzzy controller. (author)

  11. A Generic Model Based Tracking Controller for Hydraulic Valve-Cylinder Drives

    DEFF Research Database (Denmark)

    Hansen, Anders Hedegaard; Schmidt, Lasse; Pedersen, Henrik Clemmensen

    2016-01-01

    in the entire range of operation, rather than reducing stationary errors, and may be parameterized from the desired gain margin, as well as linear model parameters. The proposed control design approaches are evaluated in an experimentally validated, nonlinear simulation model of a hydraulic valve-cylinder drive......The control of hydraulic valve-cylinder drives is still an active subject of research, and various linear and particularly nonlinear approaches has been proposed, especially in the last two-three decades. In many cases the proposed controllers appear to produce excellent tracking ability due...... generally has failed to break through in industry. This paper discusses the dominant properties necessary to take into account when considering position tracking control of hydraulic valve-cylinder drives, and presents two generally applicable, generic control design approaches that combines non...

  12. FEM-based neural-network approach to nonlinear modeling with application to longitudinal vehicle dynamics control.

    Science.gov (United States)

    Kalkkuhl, J; Hunt, K J; Fritz, H

    1999-01-01

    An finite-element methods (FEM)-based neural-network approach to Nonlinear AutoRegressive with eXogenous input (NARX) modeling is presented. The method uses multilinear interpolation functions on C0 rectangular elements. The local and global structure of the resulting model is analyzed. It is shown that the model can be interpreted both as a local model network and a single layer feedforward neural network. The main aim is to use the model for nonlinear control design. The proposed FEM NARX description is easily accessible to feedback linearizing control techniques. Its use with a two-degrees of freedom nonlinear internal model controller is discussed. The approach is applied to modeling of the nonlinear longitudinal dynamics of an experimental lorry, using measured data. The modeling results are compared with local model network and multilayer perceptron approaches. A nonlinear speed controller was designed based on the identified FEM model. The controller was implemented in a test vehicle, and several experimental results are presented.

  13. Model-based setting of inspiratory pressure and respiratory rate in pressure-controlled ventilation

    International Nuclear Information System (INIS)

    Schranz, C; Möller, K; Becher, T; Schädler, D; Weiler, N

    2014-01-01

    Mechanical ventilation carries the risk of ventilator-induced-lung-injury (VILI). To minimize the risk of VILI, ventilator settings should be adapted to the individual patient properties. Mathematical models of respiratory mechanics are able to capture the individual physiological condition and can be used to derive personalized ventilator settings. This paper presents model-based calculations of inspiration pressure (p I ), inspiration and expiration time (t I , t E ) in pressure-controlled ventilation (PCV) and a retrospective evaluation of its results in a group of mechanically ventilated patients. Incorporating the identified first order model of respiratory mechanics in the basic equation of alveolar ventilation yielded a nonlinear relation between ventilation parameters during PCV. Given this patient-specific relation, optimized settings in terms of minimal p I and adequate t E can be obtained. We then retrospectively analyzed data from 16 ICU patients with mixed pathologies, whose ventilation had been previously optimized by ICU physicians with the goal of minimization of inspiration pressure, and compared the algorithm's ‘optimized’ settings to the settings that had been chosen by the physicians. The presented algorithm visualizes the patient-specific relations between inspiration pressure and inspiration time. The algorithm's calculated results highly correlate to the physician's ventilation settings with r = 0.975 for the inspiration pressure, and r = 0.902 for the inspiration time. The nonlinear patient-specific relations of ventilation parameters become transparent and support the determination of individualized ventilator settings according to therapeutic goals. Thus, the algorithm is feasible for a variety of ventilated ICU patients and has the potential of improving lung-protective ventilation by minimizing inspiratory pressures and by helping to avoid the build-up of clinically significant intrinsic positive end

  14. Model-based setting of inspiratory pressure and respiratory rate in pressure-controlled ventilation.

    Science.gov (United States)

    Schranz, C; Becher, T; Schädler, D; Weiler, N; Möller, K

    2014-03-01

    Mechanical ventilation carries the risk of ventilator-induced-lung-injury (VILI). To minimize the risk of VILI, ventilator settings should be adapted to the individual patient properties. Mathematical models of respiratory mechanics are able to capture the individual physiological condition and can be used to derive personalized ventilator settings. This paper presents model-based calculations of inspiration pressure (pI), inspiration and expiration time (tI, tE) in pressure-controlled ventilation (PCV) and a retrospective evaluation of its results in a group of mechanically ventilated patients. Incorporating the identified first order model of respiratory mechanics in the basic equation of alveolar ventilation yielded a nonlinear relation between ventilation parameters during PCV. Given this patient-specific relation, optimized settings in terms of minimal pI and adequate tE can be obtained. We then retrospectively analyzed data from 16 ICU patients with mixed pathologies, whose ventilation had been previously optimized by ICU physicians with the goal of minimization of inspiration pressure, and compared the algorithm's 'optimized' settings to the settings that had been chosen by the physicians. The presented algorithm visualizes the patient-specific relations between inspiration pressure and inspiration time. The algorithm's calculated results highly correlate to the physician's ventilation settings with r = 0.975 for the inspiration pressure, and r = 0.902 for the inspiration time. The nonlinear patient-specific relations of ventilation parameters become transparent and support the determination of individualized ventilator settings according to therapeutic goals. Thus, the algorithm is feasible for a variety of ventilated ICU patients and has the potential of improving lung-protective ventilation by minimizing inspiratory pressures and by helping to avoid the build-up of clinically significant intrinsic positive end-expiratory pressure.

  15. Design of methanol Feed control in Pichia pastoris fermentations based upon a growth model.

    Science.gov (United States)

    Zhang, Wenhui; Smith, Leonard A; Plantz, Bradley A; Schlegel, Vicki L; Meagher, Michael M

    2002-01-01

    The methylotrophic yeast Pichia pastoris is an effective system for recombinant protein productions that utilizes methanol as an inducer, and also as carbon and energy source for a Mut(+) (methanol utilization plus) strain. Pichia fermentation is conducted in a fed-batch mode to obtain a high cell density for a high productivity. An accurate methanol control is required in the methanol fed-batch phase (induction phase) in the fermentation. A simple "on-off" control strategy is inadequate for precise control of methanol concentrations in the fermentor. In this paper we employed a PID (proportional, integral and derivative) control system for the methanol concentration control and designed the PID controller settings on the basis of a Pichia growth model. The closed-loop system was built with four components: PID controller, methanol feed pump, fermentation process, and methanol sensor. First, modeling and transfer functions for all components were derived, followed by frequency response analysis, a powerful method for calculating the optimal PID parameters K(c) (controller gain), tau(I) (controller integral time constant), and tau(D) (controller derivative time constant). Bode stability criteria were used to develop the stability diagram for evaluating the designed settings during the entire methanol fed-batch phase. Fermentations were conducted using four Pichia strains, each expressing a different protein, to verify the control performance with optimal PID settings. The results showed that the methanol concentration matched the set point very well with only small overshoot when the set point was switched, which indicated that a very good control performance was achieved. The method developed in this paper is robust and can serve as a framework for the design of other PID feedback control systems in biological processes.

  16. A fuzzy model based adaptive PID controller design for nonlinear and uncertain processes.

    Science.gov (United States)

    Savran, Aydogan; Kahraman, Gokalp

    2014-03-01

    We develop a novel adaptive tuning method for classical proportional-integral-derivative (PID) controller to control nonlinear processes to adjust PID gains, a problem which is very difficult to overcome in the classical PID controllers. By incorporating classical PID control, which is well-known in industry, to the control of nonlinear processes, we introduce a method which can readily be used by the industry. In this method, controller design does not require a first principal model of the process which is usually very difficult to obtain. Instead, it depends on a fuzzy process model which is constructed from the measured input-output data of the process. A soft limiter is used to impose industrial limits on the control input. The performance of the system is successfully tested on the bioreactor, a highly nonlinear process involving instabilities. Several tests showed the method's success in tracking, robustness to noise, and adaptation properties. We as well compared our system's performance to those of a plant with altered parameters with measurement noise, and obtained less ringing and better tracking. To conclude, we present a novel adaptive control method that is built upon the well-known PID architecture that successfully controls highly nonlinear industrial processes, even under conditions such as strong parameter variations, noise, and instabilities. © 2013 Published by ISA on behalf of ISA.

  17. Implementation of internal model based control and individual pitch control to reduce fatigue loads and tower vibrations in wind turbines

    Science.gov (United States)

    Mohammadi, Ebrahim; Fadaeinedjad, Roohollah; Moschopoulos, Gerry

    2018-05-01

    Vibration control and fatigue loads reduction are important issues in large-scale wind turbines. Identifying the vibration frequencies and tuning dampers and controllers at these frequencies are major concerns in many control methods. In this paper, an internal model control (IMC) method with an adaptive algorithm is implemented to first identify the vibration frequency of the wind turbine tower and then to cancel the vibration signal. Standard individual pitch control (IPC) is also implemented to compare the performance of the controllers in term of fatigue loads reduction. Finally, the performance of the system when both controllers are implemented together is evaluated. Simulation results demonstrate that using only IMC or IPC alone has advantages and can reduce fatigue loads on specific components. IMC can identify and suppress tower vibrations in both fore-aft and side-to-side directions, whereas, IPC can reduce fatigue loads on blades, shaft and yaw bearings. When both IMC and IPC are implemented together, the advantages of both controllers can be used. The aforementioned analysis and comparisons were not studied in literature and this study fills this gap. FAST, AreoDyn and Simulink are used to simulate the mechanical, aerodynamic and electrical aspects of wind turbine.

  18. A Model Based Control methodology combining Blade Pitch and Adaptive Trailing Edge Flaps in a common framework

    DEFF Research Database (Denmark)

    Henriksen, Lars Christian; Bergami, Leonardo; Andersen, Peter Bjørn

    2013-01-01

    This work investigates how adaptive trailing edge flaps and classical blade pitch can work in concert using a model-based state space control formulation. The trade-off between load reduction and actuator activity is decided by setting different weights in the objective function used by the model...

  19. A Model Based Control methodology combining Blade Pitch and Adaptive Trailing Edge Flaps in a common framework

    DEFF Research Database (Denmark)

    This work investigates how adaptive trailing edge flaps and classical blade pitch can work in concert using a model-based state space control formulation. The trade-off between load reduction and actuator activity is decided by setting different weights in the objective function used by the model...

  20. An integrated model of statistical process control and maintenance based on the delayed monitoring

    International Nuclear Information System (INIS)

    Yin, Hui; Zhang, Guojun; Zhu, Haiping; Deng, Yuhao; He, Fei

    2015-01-01

    This paper develops an integrated model of statistical process control and maintenance decision. The proposal of delayed monitoring policy postpones the sampling process till a scheduled time and contributes to ten-scenarios of the production process, where equipment failure may occur besides quality shift. The equipment failure and the control chart alert trigger the corrective maintenance and the predictive maintenance, respectively. The occurrence probability, the cycle time and the cycle cost of each scenario are obtained by integral calculation; therefore, a mathematical model is established to minimize the expected cost by using the genetic algorithm. A Monte Carlo simulation experiment is conducted and compared with the integral calculation in order to ensure the analysis of the ten-scenario model. Another ordinary integrated model without delayed monitoring is also established as comparison. The results of a numerical example indicate satisfactory economic performance of the proposed model. Finally, a sensitivity analysis is performed to investigate the effect of model parameters. - Highlights: • We develop an integrated model of statistical process control and maintenance. • We propose delayed monitoring policy and derive an economic model with 10 scenarios. • We consider two deterioration mechanisms, quality shift and equipment failure. • The delayed monitoring policy will help reduce the expected cost

  1. Model-based Optimization and Feedback Control of the Current Density Profile Evolution in NSTX-U

    Science.gov (United States)

    Ilhan, Zeki Okan

    Nuclear fusion research is a highly challenging, multidisciplinary field seeking contributions from both plasma physics and multiple engineering areas. As an application of plasma control engineering, this dissertation mainly explores methods to control the current density profile evolution within the National Spherical Torus eXperiment-Upgrade (NSTX-U), which is a substantial upgrade based on the NSTX device, which is located in Princeton Plasma Physics Laboratory (PPPL), Princeton, NJ. Active control of the toroidal current density profile is among those plasma control milestones that the NSTX-U program must achieve to realize its next-step operational goals, which are characterized by high-performance, long-pulse, MHD-stable plasma operation with neutral beam heating. Therefore, the aim of this work is to develop model-based, feedforward and feedback controllers that can enable time regulation of the current density profile in NSTX-U by actuating the total plasma current, electron density, and the powers of the individual neutral beam injectors. Motivated by the coupled, nonlinear, multivariable, distributed-parameter plasma dynamics, the first step towards control design is the development of a physics-based, control-oriented model for the current profile evolution in NSTX-U in response to non-inductive current drives and heating systems. Numerical simulations of the proposed control-oriented model show qualitative agreement with the high-fidelity physics code TRANSP. The next step is to utilize the proposed control-oriented model to design an open-loop actuator trajectory optimizer. Given a desired operating state, the optimizer produces the actuator trajectories that can steer the plasma to such state. The objective of the feedforward control design is to provide a more systematic approach to advanced scenario planning in NSTX-U since the development of such scenarios is conventionally carried out experimentally by modifying the tokamak's actuator

  2. A Novel Energy Efficient Topology Control Scheme Based on a Coverage-Preserving and Sleep Scheduling Model for Sensor Networks

    OpenAIRE

    Shi, Binbin; Wei, Wei; Wang, Yihuai; Shu, Wanneng

    2016-01-01

    In high-density sensor networks, scheduling some sensor nodes to be in the sleep mode while other sensor nodes remain active for monitoring or forwarding packets is an effective control scheme to conserve energy. In this paper, a Coverage-Preserving Control Scheduling Scheme (CPCSS) based on a cloud model and redundancy degree in sensor networks is proposed. Firstly, the normal cloud model is adopted for calculating the similarity degree between the sensor nodes in terms of their historical d...

  3. Model Predictive Control Based on System Re-Identification (MPC-SRI) to Control Bio-H2 Production from Biomass

    Science.gov (United States)

    Wahid, A.; Taqwallah, H. M. H.

    2018-03-01

    Compressors and a steam reformer are the important units in biohydrogen from biomass plant. The compressors are useful for achieving high-pressure operating conditions while the steam reformer is the main process to produce H2 gas. To control them, in this research used a model predictive control (MPC) expected to have better controller performance than conventional controllers. Because of the explicit model empowerment in MPC, obtaining a better model is the main objective before employing MPC. The common way to get the empirical model is through the identification system, so that obtained a first-order plus dead-time (FOPDT) model. This study has already improved that way since used the system re-identification (SRI) based on closed loop mode. Based on this method the results of the compressor pressure control and temperature control of steam reformer were that MPC based on system re-identification (MPC-SRI) has better performance than MPC without system re-identification (MPCWSRI) and the proportional-integral (PI) controller, by % improvement of 73% against MPCWSRI and 75% against the PI controller.

  4. On-line Multiple-model Based Adaptive Control Reconfiguration for a Class of Non-linear Control Systems

    DEFF Research Database (Denmark)

    Yang, Z.; Izadi-Zamanabadi, R.; Blanke, Mogens

    2000-01-01

    of LTI models are employed to approximate the faulty, reconfigured and nominal nonlinear systems respectively with respect to the on-line information of the operating system, and a set of compensating modules are proposed and designed so as to make the local LTI model approximating to the reconfigured...... nonlinear system match the corresponding LTI model approximating to the nominal nonlinear system in some optimal sense. The compensating modules are designed by the Pseudo-Inverse Method based on the local LTI models for the nominal and faulty nonlinear systems. Moreover, these modules should update...... corresponding to the updating of local LTI models, which validations are determined by the model approximation errors and the optimal index of local design. The test on a nonlinear ship propulsion system shows the promising potential of this method for system reconfiguration...

  5. Active tilting-pad journal bearings supporting flexible rotors: Part II–The model-based feedback-controlled lubrication

    DEFF Research Database (Denmark)

    Salazar, Jorge Andrés González; Santos, Ilmar

    2017-01-01

    This is part II of a twofold paper series dealing with the design and implementation of model-based controllers meant for assisting the hybrid and developing the feedback-controlled lubrication regimes in active tilting pad journal bearings (active TPJBs). In both papers theoretical and experimen...... derived in part I. Results show further suppression of resonant vibrations when using the feedback-controlled or active lubrication, overweighting the reduction already achieved with hybrid lubrication, thus improving the whole machine dynamic performance.......This is part II of a twofold paper series dealing with the design and implementation of model-based controllers meant for assisting the hybrid and developing the feedback-controlled lubrication regimes in active tilting pad journal bearings (active TPJBs). In both papers theoretical...... and experimental analyses are presented with focus on the reduction of rotor lateral vibration. This part is devoted to synthesising model-based LQG optimal controllers (LQR regulator + Kalman Filter) for the feedback-controlled lubrication and is based upon the mathematical model of the rotor-bearing system...

  6. The design and optimization for light-algae bioreactor controller based on Artificial Neural Network-Model Predictive Control

    Science.gov (United States)

    Hu, Dawei; Liu, Hong; Yang, Chenliang; Hu, Enzhu

    As a subsystem of the bioregenerative life support system (BLSS), light-algae bioreactor (LABR) has properties of high reaction rate, efficiently synthesizing microalgal biomass, absorbing CO2 and releasing O2, so it is significant for BLSS to provide food and maintain gas balance. In order to manipulate the LABR properly, it has been designed as a closed-loop control system, and technology of Artificial Neural Network-Model Predictive Control (ANN-MPC) is applied to design the controller for LABR in which green microalgae, Spirulina platensis is cultivated continuously. The conclusion is drawn by computer simulation that ANN-MPC controller can intelligently learn the complicated dynamic performances of LABR, and automatically, robustly and self-adaptively regulate the light intensity illuminating on the LABR, hence make the growth of microalgae in the LABR be changed in line with the references, meanwhile provide appropriate damping to improve markedly the transient response performance of LABR.

  7. Modeling the angular motion dynamics of spacecraft with a magnetic attitude control system based on experimental studies and dynamic similarity

    Science.gov (United States)

    Kulkov, V. M.; Medvedskii, A. L.; Terentyev, V. V.; Firsyuk, S. O.; Shemyakov, A. O.

    2017-12-01

    The problem of spacecraft attitude control using electromagnetic systems interacting with the Earth's magnetic field is considered. A set of dimensionless parameters has been formed to investigate the spacecraft orientation regimes based on dynamically similar models. The results of experimental studies of small spacecraft with a magnetic attitude control system can be extrapolated to the in-orbit spacecraft motion control regimes by using the methods of the dimensional and similarity theory.

  8. Temperature Field-Wind Velocity Field Optimum Control of Greenhouse Environment Based on CFD Model

    Directory of Open Access Journals (Sweden)

    Yongbo Li

    2014-01-01

    Full Text Available The computational fluid dynamics technology is applied as the environmental control model, which can include the greenhouse space. Basic environmental factors are set to be the control objects, the field information is achieved via the division of layers by height, and numerical characteristics of each layer are used to describe the field information. Under the natural ventilation condition, real-time requirements, energy consumption, and distribution difference are selected as index functions. The optimization algorithm of adaptive simulated annealing is used to obtain optimal control outputs. A comparison with full-open ventilation shows that the whole index can be reduced at 44.21% and found that a certain mutual exclusiveness exists between the temperature and velocity field in the optimal course. All the results indicate that the application of CFD model has great advantages to improve the control accuracy of greenhouse.

  9. State-Space Modeling and Performance Analysis of Variable-Speed Wind Turbine Based on a Model Predictive Control Approach

    Directory of Open Access Journals (Sweden)

    H. Bassi

    2017-04-01

    Full Text Available Advancements in wind energy technologies have led wind turbines from fixed speed to variable speed operation. This paper introduces an innovative version of a variable-speed wind turbine based on a model predictive control (MPC approach. The proposed approach provides maximum power point tracking (MPPT, whose main objective is to capture the maximum wind energy in spite of the variable nature of the wind’s speed. The proposed MPC approach also reduces the constraints of the two main functional parts of the wind turbine: the full load and partial load segments. The pitch angle for full load and the rotating force for the partial load have been fixed concurrently in order to balance power generation as well as to reduce the operations of the pitch angle. A mathematical analysis of the proposed system using state-space approach is introduced. The simulation results using MATLAB/SIMULINK show that the performance of the wind turbine with the MPC approach is improved compared to the traditional PID controller in both low and high wind speeds.

  10. Model-based analyses to compare health and economic outcomes of cancer control: inclusion of disparities.

    Science.gov (United States)

    Goldie, Sue J; Daniels, Norman

    2011-09-21

    Disease simulation models of the health and economic consequences of different prevention and treatment strategies can guide policy decisions about cancer control. However, models that also consider health disparities can identify strategies that improve both population health and its equitable distribution. We devised a typology of cancer disparities that considers types of inequalities among black, white, and Hispanic populations across different cancers and characteristics important for near-term policy discussions. We illustrated the typology in the specific example of cervical cancer using an existing disease simulation model calibrated to clinical, epidemiological, and cost data for the United States. We calculated average reduction in cancer incidence overall and for black, white, and Hispanic women under five different prevention strategies (Strategies A1, A2, A3, B, and C) and estimated average costs and life expectancy per woman, and the cost-effectiveness ratio for each strategy. Strategies that may provide greater aggregate health benefit than existing options may also exacerbate disparities. Combining human papillomavirus vaccination (Strategy A2) with current cervical cancer screening patterns (Strategy A1) resulted in an average reduction of 69% in cancer incidence overall but a 71.6% reduction for white women, 68.3% for black women, and 63.9% for Hispanic women. Other strategies targeting risk-based screening to racial and ethnic minorities reduced disparities among racial subgroups and resulted in more equitable distribution of benefits among subgroups (reduction in cervical cancer incidence, white vs. Hispanic women, 69.7% vs. 70.1%). Strategies that employ targeted risk-based screening and new screening algorithms, with or without vaccination (Strategies B and C), provide excellent value. The most effective strategy (Strategy C) had a cost-effectiveness ratio of $28,200 per year of life saved when compared with the same strategy without

  11. Model-based system-of-systems engineering for space-based command, control, communication, and information architecture design

    Science.gov (United States)

    Sindiy, Oleg V.

    executing multi-purpose analysis studies is presented. These efforts are coupled to the generation of aggregate and time-dependent solution performance metrics via the hierarchical decomposition of objectives and the analytical recomposition of multi-attribute qualitative program drivers from quantifiable measures. This methodology was also applied to generate problem-specific solution structure evaluation metrics that facilitate the comparison of alternate solutions at a high level of aggregation, at lower levels of abstraction, and to relate options for design variables with associated performance values. For proof-of-capability demonstration, the selected application problem concerns the design of command, control, communication, and information (C3I) architecture services for a notional campaign of crewed and robotic lunar surface missions. The impetus for the work was the demonstration of using model-based SoSE for design of sustainable interoperability capabilities between all data and communication assets in extended lunar campaigns. A comprehensive Lunar C3I simulation tool was developed by a team of researchers at Purdue University in support of NASA's Constellation Program; the author of this dissertation was a key contributor to the creation of this tool and made modifications and extensions to key components relevant to the methodological concepts presented in this dissertation. The dissertation concludes with a presentation of example results based on the interrogation of the constructed Lunar C3I computational model. The results are based on a family of studies, structured around a trade-tree of architecture options, which were conducted to test the hypothesis that the SoSE approach is efficacious in the information-exchange architecture design in space exploration domain. Included in the family of proof-of-capability studies is a simulation of the Apollo 17 mission, which allows not only for partial verification and validation of the model, but also provides

  12. Combining spanwise morphing, inline motion and model based optimization for force magnitude and direction control

    Science.gov (United States)

    Scheller, Johannes; Braza, Marianna; Triantafyllou, Michael

    2016-11-01

    Bats and other animals rapidly change their wingspan in order to control the aerodynamic forces. A NACA0013 type airfoil with dynamically changing span is proposed as a simple model to experimentally study these biomimetic morphing wings. Combining this large-scale morphing with inline motion allows to control both force magnitude and direction. Force measurements are conducted in order to analyze the impact of the 4 degree of freedom flapping motion on the flow. A blade-element theory augmented unsteady aerodynamic model is then used to derive optimal flapping trajectories.

  13. A Low-Cost Maximum Power Point Tracking System Based on Neural Network Inverse Model Controller

    Directory of Open Access Journals (Sweden)

    Carlos Robles Algarín

    2018-01-01

    Full Text Available This work presents the design, modeling, and implementation of a neural network inverse model controller for tracking the maximum power point of a photovoltaic (PV module. A nonlinear autoregressive network with exogenous inputs (NARX was implemented in a serial-parallel architecture. The PV module mathematical modeling was developed, a buck converter was designed to operate in the continuous conduction mode with a switching frequency of 20 KHz, and the dynamic neural controller was designed using the Neural Network Toolbox from Matlab/Simulink (MathWorks, Natick, MA, USA, and it was implemented on an open-hardware Arduino Mega board. To obtain the reference signals for the NARX and determine the 65 W PV module behavior, a system made of a 0.8 W PV cell, a temperature sensor, a voltage sensor and a static neural network, was used. To evaluate performance a comparison with the P&O traditional algorithm was done in terms of response time and oscillations around the operating point. Simulation results demonstrated the superiority of neural controller over the P&O. Implementation results showed that approximately the same power is obtained with both controllers, but the P&O controller presents oscillations between 7 W and 10 W, in contrast to the inverse controller, which had oscillations between 1 W and 2 W.

  14. Control of trachoma in Australia: a model based evaluation of current interventions.

    Directory of Open Access Journals (Sweden)

    Andrew J Shattock

    2015-04-01

    Full Text Available Australia is the only high-income country in which endemic trachoma persists. In response, the Australian Government has recently invested heavily towards the nationwide control of the disease.A novel simulation model was developed to reflect the trachoma epidemic in Australian Aboriginal communities. The model, which incorporates demographic, migration, mixing, and biological heterogeneities, was used to evaluate recent intervention measures against counterfactual past scenarios, and also to assess the potential impact of a series of hypothesized future intervention measures relative to the current national strategy and intensity. The model simulations indicate that, under the current intervention strategy and intensity, the likelihood of controlling trachoma to less than 5% prevalence among 5-9 year-old children in hyperendemic communities by 2020 is 31% (19%-43%. By shifting intervention priorities such that large increases in the facial cleanliness of children are observed, this likelihood of controlling trachoma in hyperendemic communities is increased to 64% (53%-76%. The most effective intervention strategy incorporated large-scale antibiotic distribution programs whilst attaining ambitious yet feasible screening, treatment, facial cleanliness and housing construction targets. Accordingly, the estimated likelihood of controlling trachoma in these communities is increased to 86% (76%-95%.Maintaining the current intervention strategy and intensity is unlikely to be sufficient to control trachoma across Australia by 2020. However, by shifting the intervention strategy and increasing intensity, the likelihood of controlling trachoma nationwide can be significantly increased.

  15. Dual RBFNNs-Based Model-Free Adaptive Control With Aspen HYSYS Simulation.

    Science.gov (United States)

    Zhu, Yuanming; Hou, Zhongsheng; Qian, Feng; Du, Wenli

    2017-03-01

    In this brief, we propose a new data-driven model-free adaptive control (MFAC) method with dual radial basis function neural networks (RBFNNs) for a class of discrete-time nonlinear systems. The main novelty lies in that it provides a systematic design method for controller structure by the direct usage of I/O data, rather than using the first-principle model or offline identified plant model. The controller structure is determined by equivalent-dynamic-linearization representation of the ideal nonlinear controller, and the controller parameters are tuned by the pseudogradient information extracted from the I/O data of the plant, which can deal with the unknown nonlinear system. The stability of the closed-loop control system and the stability of the training process for RBFNNs are guaranteed by rigorous theoretical analysis. Meanwhile, the effectiveness and the applicability of the proposed method are further demonstrated by the numerical example and Aspen HYSYS simulation of distillation column in crude styrene produce process.

  16. Control of trachoma in Australia: a model based evaluation of current interventions.

    Science.gov (United States)

    Shattock, Andrew J; Gambhir, Manoj; Taylor, Hugh R; Cowling, Carleigh S; Kaldor, John M; Wilson, David P

    2015-04-01

    Australia is the only high-income country in which endemic trachoma persists. In response, the Australian Government has recently invested heavily towards the nationwide control of the disease. A novel simulation model was developed to reflect the trachoma epidemic in Australian Aboriginal communities. The model, which incorporates demographic, migration, mixing, and biological heterogeneities, was used to evaluate recent intervention measures against counterfactual past scenarios, and also to assess the potential impact of a series of hypothesized future intervention measures relative to the current national strategy and intensity. The model simulations indicate that, under the current intervention strategy and intensity, the likelihood of controlling trachoma to less than 5% prevalence among 5-9 year-old children in hyperendemic communities by 2020 is 31% (19%-43%). By shifting intervention priorities such that large increases in the facial cleanliness of children are observed, this likelihood of controlling trachoma in hyperendemic communities is increased to 64% (53%-76%). The most effective intervention strategy incorporated large-scale antibiotic distribution programs whilst attaining ambitious yet feasible screening, treatment, facial cleanliness and housing construction targets. Accordingly, the estimated likelihood of controlling trachoma in these communities is increased to 86% (76%-95%). Maintaining the current intervention strategy and intensity is unlikely to be sufficient to control trachoma across Australia by 2020. However, by shifting the intervention strategy and increasing intensity, the likelihood of controlling trachoma nationwide can be significantly increased.

  17. Programmable Nucleic Acid Based Polygons with Controlled Neuroimmunomodulatory Properties for Predictive QSAR Modeling.

    Science.gov (United States)

    Johnson, Morgan Brittany; Halman, Justin R; Satterwhite, Emily; Zakharov, Alexey V; Bui, My N; Benkato, Kheiria; Goldsworthy, Victoria; Kim, Taejin; Hong, Enping; Dobrovolskaia, Marina A; Khisamutdinov, Emil F; Marriott, Ian; Afonin, Kirill A

    2017-11-01

    In the past few years, the study of therapeutic RNA nanotechnology has expanded tremendously to encompass a large group of interdisciplinary sciences. It is now evident that rationally designed programmable RNA nanostructures offer unique advantages in addressing contemporary therapeutic challenges such as distinguishing target cell types and ameliorating disease. However, to maximize the therapeutic benefit of these nanostructures, it is essential to understand the immunostimulatory aptitude of such tools and identify potential complications. This paper presents a set of 16 nanoparticle platforms that are highly configurable. These novel nucleic acid based polygonal platforms are programmed for controllable self-assembly from RNA and/or DNA strands via canonical Watson-Crick interactions. It is demonstrated that the immunostimulatory properties of these particular designs can be tuned to elicit the desired immune response or lack thereof. To advance the current understanding of the nanoparticle properties that contribute to the observed immunomodulatory activity and establish corresponding designing principles, quantitative structure-activity relationship modeling is conducted. The results demonstrate that molecular weight, together with melting temperature and half-life, strongly predicts the observed immunomodulatory activity. This framework provides the fundamental guidelines necessary for the development of a new library of nanoparticles with predictable immunomodulatory activity. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  18. Automatic Offline Formulation of Robust Model Predictive Control Based on Linear Matrix Inequalities Method

    Directory of Open Access Journals (Sweden)

    Longge Zhang

    2013-01-01

    Full Text Available Two automatic robust model predictive control strategies are presented for uncertain polytopic linear plants with input and output constraints. A sequence of nested geometric proportion asymptotically stable ellipsoids and controllers is constructed offline first. Then the feedback controllers are automatically selected with the receding horizon online in the first strategy. Finally, a modified automatic offline robust MPC approach is constructed to improve the closed system's performance. The new proposed strategies not only reduce the conservatism but also decrease the online computation. Numerical examples are given to illustrate their effectiveness.

  19. Modeling and Control of a DFIG-Based Wind Turbine During a Grid Voltage Drop

    Directory of Open Access Journals (Sweden)

    M. Shahabi

    2011-10-01

    Full Text Available Doubly-fed induction generators (DFIG are widely used in wind energy generation systems. During a grid voltage drop, performance is degraded with rotor over current deteriorating the fault-ride through (FRT capability of the DFIG wind-energy generation system. In this paper, a complete mathematical DFIG model is proposed. The rotor is considered fed by a voltage source converter whereas the stator is connected to the grid directly. Output power and electromagnetic torque are controlled using field-oriented control (FOC. Simulation results show the efficiency of the controller in exploiting the maximum power of wind.

  20. Control volume based modelling in one space dimension of oscillating, compressible flow in reciprocating machines

    DEFF Research Database (Denmark)

    Andersen, Stig Kildegård; Carlsen, Henrik; Thomsen, Per Grove

    2006-01-01

    We present an approach for modelling unsteady, primarily one-dimensional, compressible flow. The conservation laws for mass, energy, and momentum are applied to a staggered mesh of control volumes and loss mechanisms are included directly as extra terms. Heat transfer, flow friction, and multidim...... are presented. The capabilities of the approach are illustrated with an example solution and an experimental validation of a Stirling engine model....

  1. Nonlinear Model-Based Predictive Control applied to Large Scale Cryogenic Facilities

    CERN Document Server

    Blanco Vinuela, Enrique; de Prada Moraga, Cesar

    2001-01-01

    The thesis addresses the study, analysis, development, and finally the real implementation of an advanced control system for the 1.8 K Cooling Loop of the LHC (Large Hadron Collider) accelerator. The LHC is the next accelerator being built at CERN (European Center for Nuclear Research), it will use superconducting magnets operating below a temperature of 1.9 K along a circumference of 27 kilometers. The temperature of these magnets is a control parameter with strict operating constraints. The first control implementations applied a procedure that included linear identification, modelling and regulation using a linear predictive controller. It did improve largely the overall performance of the plant with respect to a classical PID regulator, but the nature of the cryogenic processes pointed out the need of a more adequate technique, such as a nonlinear methodology. This thesis is a first step to develop a global regulation strategy for the overall control of the LHC cells when they will operate simultaneously....

  2. Modelica-based Modeling and Simulation to Support Research and Development in Building Energy and Control Systems

    Energy Technology Data Exchange (ETDEWEB)

    Wetter, Michael

    2009-02-12

    Traditional building simulation programs possess attributes that make them difficult to use for the design and analysis of building energy and control systems and for the support of model-based research and development of systems that may not already be implemented in these programs. This article presents characteristic features of such applications, and it shows how equation-based object-oriented modelling can meet requirements that arise in such applications. Next, the implementation of an open-source component model library for building energy systems is presented. The library has been developed using the equation-based object-oriented Modelica modelling language. Technical challenges of modelling and simulating such systems are discussed. Research needs are presented to make this technology accessible to user groups that have more stringent requirements with respect to the numerical robustness of simulation than a research community may have. Two examples are presented in which models from the here described library were used. The first example describes the design of a controller for a nonlinear model of a heating coil using model reduction and frequency domain analysis. The second example describes the tuning of control parameters for a static pressure reset controller of a variable air volume flow system. The tuning has been done by solving a non-convex optimization problem that minimizes fan energy subject to state constraints.

  3. Model based fleet optimisation and master control of a power production system

    International Nuclear Information System (INIS)

    Joergensen, C.; Mortensen, J.H.; Nielsen, E.O.; Moelbak, T.

    2006-01-01

    This paper discussed an optimization concept for power plants operated by the Danish power company Elsam. The power company operates a distributed power production system with fossil fuel thermal plants, biomass-fired thermal plants, waste incineration plants, on- and offshore wind power, and district heating storage units. Power and regulation power are traded on an hourly basis, while trading of district heating resources is conducted using bilateral contracts. System and plant level case studies on optimization and control were presented. A system control level was developed to ensure compliance with power market requirements. Dynamic constraints were posed by environmental regulations, grid capabilities, and fuel and district heating contracts. System components included a short-term load scheduler; a power controller; a frequency control scheduler; a marginal cost calculator; and a master control. The scheduler consisted of an optimization algorithm and a set of steady-state models designed to minimize fuel, load, and maintenance costs. Quadratic programming and mixed integer programming methods were used to minimize deviations between the total electrical power production reference value and actual power production values. The study showed that control levels can be optimized using advanced modelling and control methods. However, integration and coordination between the various levels is needed to obtain improved performance. It was concluded that a bottom-up approach starting at the lowest possible level can ensure the performance of an optimization scheme. 6 refs., 9 figs

  4. Data-Reconciliation Based Fault-Tolerant Model Predictive Control for a Biomass Boiler

    Directory of Open Access Journals (Sweden)

    Palash Sarkar

    2017-02-01

    Full Text Available This paper presents a novel, effective method to handle critical sensor faults affecting a control system devised to operate a biomass boiler. In particular, the proposed method consists of integrating a data reconciliation algorithm in a model predictive control loop, so as to annihilate the effects of faults occurring in the sensor of the flue gas oxygen concentration, by feeding the controller with the reconciled measurements. Indeed, the oxygen content in flue gas is a key variable in control of biomass boilers due its close connections with both combustion efficiency and polluting emissions. The main benefit of including the data reconciliation algorithm in the loop, as a fault tolerant component, with respect to applying standard fault tolerant methods, is that controller reconfiguration is not required anymore, since the original controller operates on the restored, reliable data. The integrated data reconciliation–model predictive control (MPC strategy has been validated by running simulations on a specific type of biomass boiler—the KPA Unicon BioGrate boiler.

  5. A model reference and sensitivity model-based self-learning fuzzy logic controller as a solution for control of nonlinear servo systems

    NARCIS (Netherlands)

    Kovacic, Z.; Bogdan, S.; Balenovic, M.

    1999-01-01

    In this paper, the design, simulation and experimental verification of a self-learning fuzzy logic controller (SLFLC) suitable for the control of nonlinear servo systems are described. The SLFLC contains a learning algorithm that utilizes a second-order reference model and a sensitivity model

  6. Model-based analysis of digital radio frequency control systems for a heavy-ion synchrotron

    International Nuclear Information System (INIS)

    Spies, Christopher

    2013-12-01

    In this thesis, we investigate the behavior of different radio frequency control systems in a heavy-ion synchrotron, which act on the electrical fields used to accelerate charged particles, along with the longitudinal dynamics of the particles in the beam. Due to the large physical dimensions of the system, the required precision can only be achieved by a distributed control system. Since the plant is highly nonlinear and the overall system is very complex, a purely analytical treatment is not possible without introducing unacceptable simplifications. Instead, we use numerical simulation to investigate the system behavior. This thesis arises from a cooperation between the Institute of Microelectronic Systems at Technische Universitaet Darmstadt and the GSI Helmholtz Center for Heavy-Ion Research. A new heavy-ion synchrotron, the SIS100, is currently being built at GSI; its completion is scheduled for 2016. The starting point for the present thesis was the question whether a control concept previously devised at GSI is feasible - not only in the ideal case, but in the presence of parameter deviations, noise, and other disturbances - and how it can be optimized. In this thesis, we present a system model of a heavy-ion synchrotron. This model comprises the beam dynamics, the relevant components of the accelerator, and the relevant controllers as well as the communication between those controllers. We discuss the simulation techniques as well as several simplifications we applied in order to be able to simulate the model in an acceptable amount of time and show that these simplifications are justified. Using the model, we conducted several case studies in order to demonstrate the practical feasibility of the control concept, analyze the system's sensitivity towards disturbances and explore opportunities for future extensions. We derive specific suggestions for improvements from our results. Finally, we demonstrate that the model represents the physical reality

  7. Entrainment and Control of Bacterial Populations: An in Silico Study over a Spatially Extended Agent Based Model.

    Science.gov (United States)

    Mina, Petros; Tsaneva-Atanasova, Krasimira; Bernardo, Mario di

    2016-07-15

    We extend a spatially explicit agent based model (ABM) developed previously to investigate entrainment and control of the emergent behavior of a population of synchronized oscillating cells in a microfluidic chamber. Unlike most of the work in models of control of cellular systems which focus on temporal changes, we model individual cells with spatial dependencies which may contribute to certain behavioral responses. We use the model to investigate the response of both open loop and closed loop strategies, such as proportional control (P-control), proportional-integral control (PI-control) and proportional-integral-derivative control (PID-control), to heterogeinities and growth in the cell population, variations of the control parameters and spatial effects such as diffusion in the spatially explicit setting of a microfluidic chamber setup. We show that, as expected from the theory of phase locking in dynamical systems, open loop control can only entrain the cell population in a subset of forcing periods, with a wide variety of dynamical behaviors obtained outside these regions of entrainment. Closed-loop control is shown instead to guarantee entrainment in a much wider region of control parameter space although presenting limitations when the population size increases over a certain threshold. In silico tracking experiments are also performed to validate the ability of classical control approaches to achieve other reference behaviors such as a desired constant output or a linearly varying one. All simulations are carried out in BSim, an advanced agent-based simulator of microbial population which is here extended ad hoc to include the effects of control strategies acting onto the population.

  8. A novel multilayer model with controllable mechanical properties for magnesium-based bone plates.

    Science.gov (United States)

    Zhou, Juncen; Huang, Wanru; Li, Qing; She, Zuxin; Chen, Funan; Li, Longqin

    2015-04-01

    Proper mechanical properties are essential for the clinical application of magnesium-based implants. In the present work, a novel multilayer model composed of three layers with desirable features was developed. The modulus of the multilayer model can be adjusted by changing the thickness of each layer. To combine three layers and improve the corrosion resistance of the whole multilayer model, the polycaprolactone coating was employed. In the immersion test, pH values, the concentration of released magnesium ions, and weight loss indicate that the corrosion rate of multilayer models is considerable lower than that of the one-layer bare substrate. The three-point bending test, which is used to examine models' mechanical properties, shows that the flexural modulus of multilayer models is reduced effectively. In addition, the mechanical degradation of multilayer models is more stable, compared to the one-layer substrate.

  9. Theory of agent-based market models with controlled levels of greed and anxiety

    Energy Technology Data Exchange (ETDEWEB)

    Papadopoulos, P; Coolen, A C C [Department of Mathematics, King' s College London, The Strand, London WC2R 2LS (United Kingdom)], E-mail: panagiotis.2.papadopoulos@kcl.ac.uk, E-mail: ton.coolen@kcl.ac.uk

    2010-01-15

    We use generating functional analysis to study minority-game-type market models with generalized strategy valuation updates that control the psychology of agents' actions. The agents' choice between trend-following and contrarian trading, and their vigor in each, depends on the overall state of the market. Even in 'fake history' models, the theory now involves an effective overall bid process (coupled to the effective agent process) which can exhibit profound remanence effects and new phase transitions. For some models the bid process can be solved directly, others require Maxwell-construction-type approximations.

  10. Theory of agent-based market models with controlled levels of greed and anxiety

    International Nuclear Information System (INIS)

    Papadopoulos, P; Coolen, A C C

    2010-01-01

    We use generating functional analysis to study minority-game-type market models with generalized strategy valuation updates that control the psychology of agents' actions. The agents' choice between trend-following and contrarian trading, and their vigor in each, depends on the overall state of the market. Even in 'fake history' models, the theory now involves an effective overall bid process (coupled to the effective agent process) which can exhibit profound remanence effects and new phase transitions. For some models the bid process can be solved directly, others require Maxwell-construction-type approximations.

  11. Decentralized model predictive based load frequency control in an interconnected power system

    Energy Technology Data Exchange (ETDEWEB)

    Mohamed, T.H., E-mail: tarekhie@yahoo.co [High Institute of Energy, South Valley University (Egypt); Bevrani, H., E-mail: bevrani@ieee.or [Dept. of Electrical Engineering and Computer Science, University of Kurdistan (Iran, Islamic Republic of); Hassan, A.A., E-mail: aahsn@yahoo.co [Faculty of Engineering, Dept. of Electrical Engineering, Minia University, Minia (Egypt); Hiyama, T., E-mail: hiyama@cs.kumamoto-u.ac.j [Dept. of Electrical Engineering and Computer Science, Kumamoto University, Kumamoto (Japan)

    2011-02-15

    This paper presents a new load frequency control (LFC) design using the model predictive control (MPC) technique in a multi-area power system. The MPC technique has been designed such that the effect of the uncertainty due to governor and turbine parameters variation and load disturbance is reduced. Each local area controller is designed independently such that stability of the overall closed-loop system is guaranteed. A frequency response model of multi-area power system is introduced, and physical constraints of the governors and turbines are considered. The model was employed in the MPC structures. Digital simulations for both two and three-area power systems are provided to validate the effectiveness of the proposed scheme. The results show that, with the proposed MPC technique, the overall closed-loop system performance demonstrated robustness in the face of uncertainties due to governors and turbines parameters variation and loads disturbances. A performance comparison between the proposed controller and a classical integral control scheme is carried out confirming the superiority of the proposed MPC technique.

  12. Decentralized model predictive based load frequency control in an interconnected power system

    International Nuclear Information System (INIS)

    Mohamed, T.H.; Bevrani, H.; Hassan, A.A.; Hiyama, T.

    2011-01-01

    This paper presents a new load frequency control (LFC) design using the model predictive control (MPC) technique in a multi-area power system. The MPC technique has been designed such that the effect of the uncertainty due to governor and turbine parameters variation and load disturbance is reduced. Each local area controller is designed independently such that stability of the overall closed-loop system is guaranteed. A frequency response model of multi-area power system is introduced, and physical constraints of the governors and turbines are considered. The model was employed in the MPC structures. Digital simulations for both two and three-area power systems are provided to validate the effectiveness of the proposed scheme. The results show that, with the proposed MPC technique, the overall closed-loop system performance demonstrated robustness in the face of uncertainties due to governors and turbines parameters variation and loads disturbances. A performance comparison between the proposed controller and a classical integral control scheme is carried out confirming the superiority of the proposed MPC technique.

  13. Precise Modeling Based on Dynamic Phasors for Droop-Controlled Parallel-Connected Inverters

    DEFF Research Database (Denmark)

    Wang, L.; Guo, X.Q.; Gu, H.R.

    2012-01-01

    This paper deals with the precise modeling of droop controlled parallel inverters. This is very attractive since that is a common structure that can be found in a stand-alone droopcontrolled MicroGrid. The conventional small-signal dynamic is not able to predict instabilities of the system, so...

  14. Modeling tumor control probability for spatially inhomogeneous risk of failure based on clinical outcome data

    DEFF Research Database (Denmark)

    Lühr, Armin; Löck, Steffen; Jakobi, Annika

    2017-01-01

    PURPOSE: Objectives of this work are (1) to derive a general clinically relevant approach to model tumor control probability (TCP) for spatially variable risk of failure and (2) to demonstrate its applicability by estimating TCP for patients planned for photon and proton irradiation. METHODS AND ...

  15. Modeling And Control Of Excitation And Governor Based On PSO For MHPP

    Directory of Open Access Journals (Sweden)

    Adi Soeprijanto

    2013-07-01

    Full Text Available This paper presents the modeling and control of the excitation system via the automatic voltage regulator (AVR and governor system through the automatic generation control (AGC or frequency load control (FLC to improve stability on a micro hydro power plant (MHPP. Three main parts of the generation system are synchronous generator, AVR/excitation, AGC modelled linearly. Generator is modelled by a single machine connected to infinite bus (SMIB which is equipped by AVR and excitation linear model. Excitation control system made ??by optimizing the gain of the AVR (KA and the governor with the gain of the AGC (Ki. Optimization is done using the method improved particle swam optimization (IPSO. The main purpose of setting the gain of the AVR-AGC is to stabilize the oscillation frequency of the MHPP is connected to an infinite bus. Simulations are conducted by inputting step function with 5% load fluctuations as a representation of dynamic load. The simulation results show that the proposed method effectively raises the level  of electromechanical damping oscillations the SMIB by generating the comprehensive damping index (CDI is minimum.

  16. Model-based predictive control scheme for cost optimization and balancing services for supermarket refrigeration Systems

    NARCIS (Netherlands)

    Weerts, H.H.M.; Shafiei, S.E.; Stoustrup, J.; Izadi-Zamanabadi, R.; Boje, E.; Xia, X.

    2014-01-01

    A new formulation of model predictive control for supermarket refrigeration systems is proposed to facilitate the regulatory power services as well as energy cost optimization of such systems in the smart grid. Nonlinear dynamics existed in large-scale refrigeration plants challenges the predictive

  17. Unhealthy weight control behaviours in adolescent girls: a process model based on self-determination theory.

    Science.gov (United States)

    Thøgersen-Ntoumani, Cecilie; Ntoumanis, Nikos; Nikitaras, Nikitas

    2010-06-01

    This study used self-determination theory (Deci, E.L., & Ryan, R.M. (2000). The 'what' and 'why' of goal pursuits: Human needs and the self-determination of behavior. Psychological Inquiry, 11, 227-268.) to examine predictors of body image concerns and unhealthy weight control behaviours in a sample of 350 Greek adolescent girls. A process model was tested which proposed that perceptions of parental autonomy support and two life goals (health and image) would predict adolescents' degree of satisfaction of their basic psychological needs. In turn, psychological need satisfaction was hypothesised to negatively predict body image concerns (i.e. drive for thinness and body dissatisfaction) and, indirectly, unhealthy weight control behaviours. The predictions of the model were largely supported indicating that parental autonomy support and adaptive life goals can indirectly impact upon the extent to which female adolescents engage in unhealthy weight control behaviours via facilitating the latter's psychological need satisfaction.

  18. Model based control and optimization of a feed-water heater train; Modellbaserad reglering och optimering av en foervaermarekedja

    Energy Technology Data Exchange (ETDEWEB)

    Velut, Stephane; Raaberg, Martin; Wendel, Hans (Grontmij AB (SE))

    2007-12-15

    Thermal power plants are complex processes in which many variables must be monitored and controlled in real-time for a safe and economic operation. The complex interactions between actuators and controlled variables as well as the load dependent dynamics make the design and tuning of all controllers a challenging task. A mathematical model of the process that describes critical characteristics such as dynamics, interactions, and nonlinearities might greatly facilitate the task of the control engineer. Such controllers can be designed in a rather systematic way to achieve good performance in terms of response time and robustness. This enables the operator to run the process closer to its limits while minimizing damage risks. The goal of the project was threefold. The first objective was to describe the available methods to compute process models directly from experimental data and illustrate how those models can be used for control design. The second objective was to apply some of the fore mentioned methods on a specific process, namely a feed water heater train to control the level in each preheater. The third objective was to analyze how the level in each preheater affects the thermal efficiency of the plant and derive adequate set-points for the model-based controllers. The project started at the end of the production season, which resulted in a tight schedule for the planning and the realization of experiments. Informative data could however be collected and models could be derived for some specific loads. Unfortunately the effect of the changes in the level set point could not be verified because of the limited length of the experiments. The project results can be summarized as follows: The way the condensate level should be chosen in every preheater has been formulated as a simple optimization problem that aims as maximizing the thermal efficiency of the plant. Even though the model used in the optimization was simple, the results were pretty intuitive. The

  19. Musculoskeletal model-based control interface mimics physiologic hand dynamics during path tracing task

    Science.gov (United States)

    Crouch, Dustin L.; (Helen Huang, He

    2017-06-01

    Objective. We investigated the feasibility of a novel, customizable, simplified EMG-driven musculoskeletal model for estimating coordinated hand and wrist motions during a real-time path tracing task. Approach. A two-degree-of-freedom computational musculoskeletal model was implemented for real-time EMG-driven control of a stick figure hand displayed on a computer screen. After 5-10 minutes of undirected practice, subjects were given three attempts to trace 10 straight paths, one at a time, with the fingertip of the virtual hand. Able-bodied subjects completed the task on two separate test days. Main results. Across subjects and test days, there was a significant linear relationship between log-transformed measures of accuracy and speed (Pearson’s r  =  0.25, p  bodied subjects in 8 of 10 trials. For able-bodied subjects, tracing accuracy was lower at the extremes of the model’s range of motion, though there was no apparent relationship between tracing accuracy and fingertip location for the amputee. Our result suggests that, unlike able-bodied subjects, the amputee’s motor control patterns were not accustomed to the multi-joint dynamics of the wrist and hand, possibly as a result of post-amputation cortical plasticity, disuse, or sensory deficits. Significance. To our knowledge, our study is one of very few that have demonstrated the real-time simultaneous control of multi-joint movements, especially wrist and finger movements, using an EMG-driven musculoskeletal model, which differs from the many data-driven algorithms that dominate the literature on EMG-driven prosthesis control. Real-time control was achieved with very little training and simple, quick (~15 s) calibration. Thus, our model is potentially a practical and effective control platform for multifunctional myoelectric prostheses that could restore more life-like hand function for individuals with upper limb amputation.

  20. Robust Model-based Control of Open-loop Unstable Processes

    International Nuclear Information System (INIS)

    Emad, Ali

    1999-01-01

    This paper addresses the development of new formulations for estimating modeling errors or unmeasured disturbances to be used in Model Predictive Control (MPC) algorithms during open-loop prediction. Two different formulations were developed in this paper. One is used in MPC that directly utilizes linear models and the other in MPC that utilizes non-linear models. These estimation techniques were utilized to provide robust performance for MPC algorithms when the plant is open-loop unstable and under the influence of modeling error and/or unmeasured disturbances. For MPC that utilizes a non-linear model, the estimation technique is formulated as a fixed small size on-line optimization problem, while for linear MPC, the unmeasured disturbances are estimated via a proposed linear disturbance model. The disturbance model coefficients are identified on-line from historical estimates of plant-model mismatch. The effectiveness of incorporating these proposed estimation techniques into MPC is tested through simulated implementation on non-linear unstable exothermic fluidized bed reactor. Closed-loop simulations proved the capability of the proposed estimation methods to stabilize and, thereby, improve the MPC performance in such cases. (Author)

  1. Model-Based Predictive Control Scheme for Cost Optimization and Balancing Services for Supermarket Refrigeration Systems

    DEFF Research Database (Denmark)

    Weerts, Hermanus H. M.; Shafiei, Seyed Ehsan; Stoustrup, Jakob

    2014-01-01

    A new formulation of model predictive control for supermarket refrigeration systems is proposed to facilitate the regulatory power services as well as energy cost optimization of such systems in the smart grid. Nonlinear dynamics existed in large-scale refrigeration plants challenges the predictive...... control design. It is however shown that taking into account the knowledge of different time scales in the dynamical subsystems makes possible a linear formulation of a centralized predictive controller. A realistic scenario of regulatory power services in the smart grid is considered and formulated...... in the same objective as of cost optimization one. A simulation benchmark validated against real data and including significant dynamics of the system are employed to show the effectiveness of the proposed control scheme....

  2. Adaptive integral backstepping sliding mode control for opto-electronic tracking system based on modified LuGre friction model

    Science.gov (United States)

    Yue, Fengfa; Li, Xingfei; Chen, Cheng; Tan, Wenbin

    2017-12-01

    In order to improve the control accuracy and stability of opto-electronic tracking system fixed on reef or airport under friction and external disturbance conditions, adaptive integral backstepping sliding mode control approach with friction compensation is developed to achieve accurate and stable tracking for fast moving target. The nonlinear observer and slide mode controller based on modified LuGre model with friction compensation can effectively reduce the influence of nonlinear friction and disturbance of this servo system. The stability of the closed-loop system is guaranteed by Lyapunov theory. The steady-state error of the system is eliminated by integral action. The adaptive integral backstepping sliding mode controller and its performance are validated by a nonlinear modified LuGre dynamic model of the opto-electronic tracking system in simulation and practical experiments. The experiment results demonstrate that the proposed controller can effectively realise the accuracy and stability control of opto-electronic tracking system.

  3. Port-Based Modeling and Control for Efficient Bipedal Walking Robots

    NARCIS (Netherlands)

    Duindam, V.

    2006-01-01

    Research on walking robots has shown that the process of walking, in itself, requires little energy. Indeed, many robots have been built that walk with high efficiency. General analysis and control tools for such efficient walkers, however, are lacking, and many results are based on engineering

  4. Engine Modelling for Control Applications

    DEFF Research Database (Denmark)

    Hendricks, Elbert

    1997-01-01

    In earlier work published by the author and co-authors, a dynamic engine model called a Mean Value Engine Model (MVEM) was developed. This model is physically based and is intended mainly for control applications. In its newer form, it is easy to fit to many different engines and requires little...... engine data for this purpose. It is especially well suited to embedded model applications in engine controllers, such as nonlinear observer based air/fuel ratio and advanced idle speed control. After a brief review of this model, it will be compared with other similar models which can be found...

  5. Integrated Sensing and Controls for Coal Gasification - Development of Model-Based Controls for GE's Gasifier and Syngas Cooler

    Energy Technology Data Exchange (ETDEWEB)

    Aditya Kumar

    2010-12-30

    This report summarizes the achievements and final results of this program. The objective of this program is to develop a comprehensive systems approach to integrated design of sensing and control systems for an Integrated Gasification Combined Cycle (IGCC) plant, using advanced model-based techniques. In particular, this program is focused on the model-based sensing and control system design for the core gasification section of an IGCC plant. The overall approach consists of (i) developing a first-principles physics-based dynamic model of the gasification section, (ii) performing model-reduction where needed to derive low-order models suitable for controls analysis and design, (iii) developing a sensing system solution combining online sensors with model-based estimation for important process variables not measured directly, and (iv) optimizing the steady-state and transient operation of the plant for normal operation as well as for startup using model predictive controls (MPC). Initially, available process unit models were implemented in a common platform using Matlab/Simulink{reg_sign}, and appropriate model reduction and model updates were performed to obtain the overall gasification section dynamic model. Also, a set of sensor packages were developed through extensive lab testing and implemented in the Tampa Electric Company IGCC plant at Polk power station in 2009, to measure temperature and strain in the radiant syngas cooler (RSC). Plant operation data was also used to validate the overall gasification section model. The overall dynamic model was then used to develop a sensing solution including a set of online sensors coupled with model-based estimation using nonlinear extended Kalman filter (EKF). Its performance in terms of estimating key unmeasured variables like gasifier temperature, carbon conversion, etc., was studied through extensive simulations in the presence sensing errors (noise and bias) and modeling errors (e.g. unknown gasifier kinetics, RSC

  6. Walking dynamics of the passive compass-gait model under OGY-based control: Emergence of bifurcations and chaos

    Science.gov (United States)

    Gritli, Hassène; Belghith, Safya

    2017-06-01

    An analysis of the passive dynamic walking of a compass-gait biped model under the OGY-based control approach using the impulsive hybrid nonlinear dynamics is presented in this paper. We describe our strategy for the development of a simplified analytical expression of a controlled hybrid Poincaré map and then for the design of a state-feedback control. Our control methodology is based mainly on the linearization of the impulsive hybrid nonlinear dynamics around a desired nominal one-periodic hybrid limit cycle. Our analysis of the controlled walking dynamics is achieved by means of bifurcation diagrams. Some interesting nonlinear phenomena are displayed, such as the period-doubling bifurcation, the cyclic-fold bifurcation, the period remerging, the period bubbling and chaos. A comparison between the raised phenomena in the impulsive hybrid nonlinear dynamics and the hybrid Poincaré map under control was also presented.

  7. A Cyber Physical Model Based on a Hybrid System for Flexible Load Control in an Active Distribution Network

    Directory of Open Access Journals (Sweden)

    Yun Wang

    2017-02-01

    Full Text Available To strengthen the integration of the primary and secondary systems, a concept of Cyber Physical Systems (CPS is introduced to construct a CPS in Power Systems (Power CPS. The most basic work of the Power CPS is to build an integration model which combines both a continuous process and a discrete process. The advanced form of smart grid, the Active Distribution Network (ADN is a typical example of Power CPS. After designing the Power CPS model architecture and its application in ADN, a Hybrid System based model and control method of Power CPS is proposed in this paper. As an application example, ADN flexible load is modeled and controlled with ADN feeder power control by a control strategy which includes the normal condition and the underpowered condition. In this model and strategy, some factors like load power consumption and load functional demand are considered and optimized. In order to make up some of the deficiencies of centralized control, a distributed control method is presented to reduce model complexity and improve calculation speed. The effectiveness of all the models and methods are demonstrated in the case study.

  8. A new computational account of cognitive control over reinforcement-based decision-making: Modeling of a probabilistic learning task.

    Science.gov (United States)

    Zendehrouh, Sareh

    2015-11-01

    Recent work on decision-making field offers an account of dual-system theory for decision-making process. This theory holds that this process is conducted by two main controllers: a goal-directed system and a habitual system. In the reinforcement learning (RL) domain, the habitual behaviors are connected with model-free methods, in which appropriate actions are learned through trial-and-error experiences. However, goal-directed behaviors are associated with model-based methods of RL, in which actions are selected using a model of the environment. Studies on cognitive control also suggest that during processes like decision-making, some cortical and subcortical structures work in concert to monitor the consequences of decisions and to adjust control according to current task demands. Here a computational model is presented based on dual system theory and cognitive control perspective of decision-making. The proposed model is used to simulate human performance on a variant of probabilistic learning task. The basic proposal is that the brain implements a dual controller, while an accompanying monitoring system detects some kinds of conflict including a hypothetical cost-conflict one. The simulation results address existing theories about two event-related potentials, namely error related negativity (ERN) and feedback related negativity (FRN), and explore the best account of them. Based on the results, some testable predictions are also presented. Copyright © 2015 Elsevier Ltd. All rights reserved.

  9. Adaptive robust motion trajectory tracking control of pneumatic cylinders with LuGre model-based friction compensation

    Science.gov (United States)

    Meng, Deyuan; Tao, Guoliang; Liu, Hao; Zhu, Xiaocong

    2014-07-01

    Friction compensation is particularly important for motion trajectory tracking control of pneumatic cylinders at low speed movement. However, most of the existing model-based friction compensation schemes use simple classical models, which are not enough to address applications with high-accuracy position requirements. Furthermore, the friction force in the cylinder is time-varying, and there exist rather severe unmodelled dynamics and unknown disturbances in the pneumatic system. To deal with these problems effectively, an adaptive robust controller with LuGre model-based dynamic friction compensation is constructed. The proposed controller employs on-line recursive least squares estimation (RLSE) to reduce the extent of parametric uncertainties, and utilizes the sliding mode control method to attenuate the effects of parameter estimation errors, unmodelled dynamics and disturbances. In addition, in order to realize LuGre model-based friction compensation, the modified dual-observer structure for estimating immeasurable friction internal state is developed. Therefore, a prescribed motion tracking transient performance and final tracking accuracy can be guaranteed. Since the system model uncertainties are unmatched, the recursive backstepping design technology is applied. In order to solve the conflicts between the sliding mode control design and the adaptive control design, the projection mapping is used to condition the RLSE algorithm so that the parameter estimates are kept within a known bounded convex set. Finally, the proposed controller is tested for tracking sinusoidal trajectories and smooth square trajectory under different loads and sudden disturbance. The testing results demonstrate that the achievable performance of the proposed controller is excellent and is much better than most other studies in literature. Especially when a 0.5 Hz sinusoidal trajectory is tracked, the maximum tracking error is 0.96 mm and the average tracking error is 0.45 mm. This

  10. Robust master-slave synchronization for general uncertain delayed dynamical model based on adaptive control scheme.

    Science.gov (United States)

    Wang, Tianbo; Zhou, Wuneng; Zhao, Shouwei; Yu, Weiqin

    2014-03-01

    In this paper, the robust exponential synchronization problem for a class of uncertain delayed master-slave dynamical system is investigated by using the adaptive control method. Different from some existing master-slave models, the considered master-slave system includes bounded unmodeled dynamics. In order to compensate the effect of unmodeled dynamics and effectively achieve synchronization, a novel adaptive controller with simple updated laws is proposed. Moreover, the results are given in terms of LMIs, which can be easily solved by LMI Toolbox in Matlab. A numerical example is given to illustrate the effectiveness of the method. Copyright © 2013 ISA. Published by Elsevier Ltd. All rights reserved.

  11. Is outdoor vector control needed for malaria elimination? An individual-based modelling study.

    Science.gov (United States)

    Zhu, Lin; Müller, Günter C; Marshall, John M; Arheart, Kristopher L; Qualls, Whitney A; Hlaing, WayWay M; Schlein, Yosef; Traore, Sekou F; Doumbia, Seydou; Beier, John C

    2017-07-03

    Residual malaria transmission has been reported in many areas even with adequate indoor vector control coverage, such as long-lasting insecticidal nets (LLINs). The increased insecticide resistance in Anopheles mosquitoes has resulted in reduced efficacy of the widely used indoor tools and has been linked with an increase in outdoor malaria transmission. There are considerations of incorporating outdoor interventions into integrated vector management (IVM) to achieve malaria elimination; however, more information on the combination of tools for effective control is needed to determine their utilization. A spatial individual-based model was modified to simulate the environment and malaria transmission activities in a hypothetical, isolated African village setting. LLINs and outdoor attractive toxic sugar bait (ATSB) stations were used as examples of indoor and outdoor interventions, respectively. Different interventions and lengths of efficacy periods were tested. Simulations continued for 420 days, and each simulation scenario was repeated 50 times. Mosquito populations, entomologic inoculation rates (EIRs), probabilities of local mosquito extinction, and proportion of time when the annual EIR was reduced below one were compared between different intervention types and efficacy periods. In the village setting with clustered houses, the combinational intervention of 50% LLINs plus outdoor ATSBs significantly reduced mosquito population and EIR in short term, increased the probability of local mosquito extinction, and increased the time when annual EIR is less than one per person compared to 50% LLINs alone; outdoor ATSBs alone significantly reduced mosquito population in short term, increased the probability of mosquito extinction, and increased the time when annual EIR is less than one compared to 50% LLINs alone, but there was no significant difference in EIR in short term between 50% LLINs and outdoor ATSBs. In the village setting with dispersed houses, the

  12. A model based message passing approach for flexible and scalable home automation controllers

    Energy Technology Data Exchange (ETDEWEB)

    Bienhaus, D. [INNIAS GmbH und Co. KG, Frankenberg (Germany); David, K.; Klein, N.; Kroll, D. [ComTec Kassel Univ., SE Kassel Univ. (Germany); Heerdegen, F.; Jubeh, R.; Zuendorf, A. [Kassel Univ. (Germany). FG Software Engineering; Hofmann, J. [BSC Computer GmbH, Allendorf (Germany)

    2012-07-01

    There is a large variety of home automation systems that are largely proprietary systems from different vendors. In addition, the configuration and administration of home automation systems is frequently a very complex task especially, if more complex functionality shall be achieved. Therefore, an open model for home automation was developed that is especially designed for easy integration of various home automation systems. This solution also provides a simple modeling approach that is inspired by typical home automation components like switches, timers, etc. In addition, a model based technology to achieve rich functionality and usability was implemented. (orig.)

  13. Optimal blood glucose level control using dynamic programming based on minimal Bergman model

    Science.gov (United States)

    Rettian Anggita Sari, Maria; Hartono

    2018-03-01

    The purpose of this article is to simulate the glucose dynamic and the insulin kinetic of diabetic patient. The model used in this research is a non-linear Minimal Bergman model. Optimal control theory is then applied to formulate the problem in order to determine the optimal dose of insulin in the treatment of diabetes mellitus such that the glucose level is in the normal range for some specific time range. The optimization problem is solved using dynamic programming. The result shows that dynamic programming is quite reliable to represent the interaction between glucose and insulin levels in diabetes mellitus patient.

  14. A Model Predictive Control-Based Power Converter System for Oscillating Water Column Wave Energy Converters

    Directory of Open Access Journals (Sweden)

    Gimara Rajapakse

    2017-10-01

    Full Text Available Despite the predictability and availability at large scale, wave energy conversion (WEC has still not become a mainstream renewable energy technology. One of the main reasons is the large variations in the extracted power which could lead to instabilities in the power grid. In addition, maintaining the speed of the turbine within optimal range under changing wave conditions is another control challenge, especially in oscillating water column (OWC type WEC systems. As a solution to the first issue, this paper proposes the direct connection of a battery bank into the dc-link of the back-to-back power converter system, thereby smoothening the power delivered to the grid. For the second issue, model predictive controllers (MPCs are developed for the rectifier and the inverter of the back-to-back converter system aiming to maintain the turbine speed within its optimum range. In addition, MPC controllers are designed to control the battery current as well, in both charging and discharging conditions. Operations of the proposed battery direct integration scheme and control solutions are verified through computer simulations. Simulation results show that the proposed integrated energy storage and control solutions are capable of delivering smooth power to the grid while maintaining the turbine speed within its optimum range under varying wave conditions.

  15. An Inventory Controlled Supply Chain Model Based on Improved BP Neural Network

    Directory of Open Access Journals (Sweden)

    Wei He

    2013-01-01

    Full Text Available Inventory control is a key factor for reducing supply chain cost and increasing customer satisfaction. However, prediction of inventory level is a challenging task for managers. As one of the widely used techniques for inventory control, standard BP neural network has such problems as low convergence rate and poor prediction accuracy. Aiming at these problems, a new fast convergent BP neural network model for predicting inventory level is developed in this paper. By adding an error offset, this paper deduces the new chain propagation rule and the new weight formula. This paper also applies the improved BP neural network model to predict the inventory level of an automotive parts company. The results show that the improved algorithm not only significantly exceeds the standard algorithm but also outperforms some other improved BP algorithms both on convergence rate and prediction accuracy.

  16. Simplified model-based optimal control of VAV air-conditioning system

    Energy Technology Data Exchange (ETDEWEB)

    Nassif, N.; Kajl, S.; Sabourin, R. [Ecole de Technologie Superieure, Montreal, PQ (Canada). Dept. of Construction Engineering

    2005-07-01

    The improvement of Variable Air Volume (VAV) system performance is one of several attempts being made to minimize the high energy use associated with the operation of heating, ventilation and air conditioning (HVAC) systems. A Simplified Optimization Process (SOP) comprised of controller set point strategies and a simplified VAV model was presented in this paper. The aim of the SOP was to determine supply set points. The advantage of the SOP over previous methods was that it did not require a detailed VAV model and optimization program. In addition, the monitored data for representative local-loop control can be checked on-line, after which controller set points can be updated in order to ensure proper operation by opting for real situations with minimum energy use. The SOP was validated using existing monitoring data and a model of an existing VAV system. Energy use simulations were compared to that of the existing VAV system. At each simulation step, 3 controller set point values were proposed and studied using the VAV model in order to select a value for each point which corresponded to the best performance of the VAV system. Simplified VAV component models were presented. Strategies for controller set points were described, including zone air temperature, duct static pressure set points; chilled water supply set points and supply air temperature set points. Simplified optimization process calculations were presented. Results indicated that the SOP provided significant energy savings when applied to specific AHU systems. In a comparison with a Detailed Optimization Process (DOP), the SOP was capable of determining set points close to those obtained by the DOP. However, it was noted that the controller set points determined by the SOP need a certain amount of time to reach optimal values when outdoor conditions or thermal loads are significantly changed. It was suggested that this disadvantage could be overcome by the use of a dynamic incremental value, which

  17. A distributed model predictive control based load frequency control scheme for multi-area interconnected power system using discrete-time Laguerre functions.

    Science.gov (United States)

    Zheng, Yang; Zhou, Jianzhong; Xu, Yanhe; Zhang, Yuncheng; Qian, Zhongdong

    2017-05-01

    This paper proposes a distributed model predictive control based load frequency control (MPC-LFC) scheme to improve control performances in the frequency regulation of power system. In order to reduce the computational burden in the rolling optimization with a sufficiently large prediction horizon, the orthonormal Laguerre functions are utilized to approximate the predicted control trajectory. The closed-loop stability of the proposed MPC scheme is achieved by adding a terminal equality constraint to the online quadratic optimization and taking the cost function as the Lyapunov function. Furthermore, the treatments of some typical constraints in load frequency control have been studied based on the specific Laguerre-based formulations. Simulations have been conducted in two different interconnected power systems to validate the effectiveness of the proposed distributed MPC-LFC as well as its superiority over the comparative methods. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

  18. Reduced-order model based active disturbance rejection control of hydraulic servo system with singular value perturbation theory.

    Science.gov (United States)

    Wang, Chengwen; Quan, Long; Zhang, Shijie; Meng, Hongjun; Lan, Yuan

    2017-03-01

    Hydraulic servomechanism is the typical mechanical/hydraulic double-dynamics coupling system with the high stiffness control and mismatched uncertainties input problems, which hinder direct applications of many advanced control approaches in the hydraulic servo fields. In this paper, by introducing the singular value perturbation theory, the original double-dynamics coupling model of the hydraulic servomechanism was reduced to a integral chain system. So that, the popular ADRC (active disturbance rejection control) technology could be directly applied to the reduced system. In addition, the high stiffness control and mismatched uncertainties input problems are avoided. The validity of the simplified model is analyzed and proven theoretically. The standard linear ADRC algorithm is then developed based on the obtained reduced-order model. Extensive comparative co-simulations and experiments are carried out to illustrate the effectiveness of the proposed method. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

  19. Performance of grid connected DFIG during recurring symmetrical faults using Internal Model Controller based Enhanced Field Oriented Control

    Directory of Open Access Journals (Sweden)

    D.V.N.Ananth

    2016-06-01

    Full Text Available The modern grid rules forces DFIG to withstand and operate during single as well as multiple low voltage grid faults. The system must not lose synchronism during any type of fault for a given time period. This withstanding capacity is called low voltage ride through (LVRT. To improve performance during LVRT, enhanced field oriented control (EFOC method is adopted in rotor side converter. This method helps in improving power transfer capability during steady state and better dynamic and transient stability during abnormal conditions. In this technique, rotor flux reference change from synchronous speed to some smaller speed or zero during the fault for injecting current at the rotor slip frequency. In this process, DC-Offset component of flux is controlled beyond decomposing to a lower value during faults and maintaining it. This offset decomposition of flux will be oscillatory in conventional FOC, whereas in EFOC with internal model controller, flux can damp quickly not only for single fault but during multiple faults. This strategy can regulate stator and rotor current waveform to sinusoidal without distortion during and after fault. It has better damped torque oscillations, control in rotor speed and generator flux during and after fault. The fluctuations in DC bus voltage across capacitor are also controlled using proposed EFOC technique. The system performance with under-voltage grid fault of 30% and 60% of the rated voltage occurring at the point of common coupling during 1 to 1.25 and another fault between 1.6 to 1.85 seconds are analyzed using simulation studies.

  20. Modelling and controlling hydropower plants

    CERN Document Server

    Munoz-Hernandez, German Ardul; Jones, Dewi Ieuan

    2013-01-01

    Hydroelectric power stations are a major source of electricity around the world; understanding their dynamics is crucial to achieving good performance.  Modelling and Controlling Hydropower Plants discusses practical and well-documented cases of modelling and controlling hydropower station modelling and control, focussing on a pumped storage scheme based in Dinorwig, North Wales.  Single-input-single-output and multiple-input-multiple-output models, which cover the linear and nonlinear characteristics of pump-storage hydroelectric power stations, are reviewed. The most important dynamic features are discussed, and the verification of these models by hardware in the loop simulation is described. To show how the performance of a pump-storage hydroelectric power station can be improved, classical and modern controllers are applied to simulated models of the Dinorwig power plant. These include PID, fuzzy approximation, feed-forward and model-based predictive control with linear and hybrid prediction models. Mod...

  1. Longitudinal control behaviour: Analysis and modelling based on experimental surveys in Italy and the UK.

    Science.gov (United States)

    Pariota, Luigi; Bifulco, Gennaro Nicola; Galante, Francesco; Montella, Alfonso; Brackstone, Mark

    2016-04-01

    This paper analyses driving behaviour in car-following conditions, based on extensive individual vehicle data collected during experimental field surveys carried out in Italy and the UK. The aim is to contribute to identify simple evidence to be exploited in the ongoing process of driving assistance and automation which, in turn, would reduce rear-end crashes. In particular, identification of differences and similarities in observed car-following behaviours for different samples of drivers could justify common tuning, at a European or worldwide level, of a technological solution aimed at active safety, or, in the event of differences, could suggest the most critical aspects to be taken into account for localisation or customisation of driving assistance solutions. Without intending to be exhaustive, this paper moves one step in this direction. Indeed, driving behaviour and human errors are considered to be among the main crash contributory factors, and a promising approach for safety improvement is the progressive introduction of increasing levels of driving automation in next-generation vehicles, according to the active/preventive safety approach. However, the more advanced the system, the more complex will be the integration in the vehicle, and the interaction with the driver may sometimes become unproductive, or risky, should the driver be removed from the driving control loop. Thus, implementation of these systems will require the interaction of human driving logics with automation logics and then an enhanced ability in modelling drivers' behaviour. This will allow both higher active-safety levels and higher user acceptance to be achieved, thus ensuring that the driver is always in the control loop, even if his/her role is limited to supervising the automatic logic. Currently, the driving mode most targeted by driving assistance systems is longitudinal driving. This is required in various driving conditions, among which car-following assumes key importance

  2. Discrete Model Predictive Control-Based Maximum Power Point Tracking for PV Systems: Overview and Evaluation

    DEFF Research Database (Denmark)

    Lashab, Abderezak; Sera, Dezso; Guerrero, Josep M.

    2018-01-01

    The main objective of this work is to provide an overview and evaluation of discrete model predictive controlbased maximum power point tracking (MPPT) for PV systems. A large number of MPC based MPPT methods have been recently introduced in the literature with very promising performance, however......, an in-depth investigation and comparison of these methods have not been carried out yet. Therefore, this paper has set out to provide an in-depth analysis and evaluation of MPC based MPPT methods applied to various common power converter topologies. The performance of MPC based MPPT is directly linked...... with the converter topology, and it is also affected by the accurate determination of the converter parameters, sensitivity to converter parameter variations is also investigated. The static and dynamic performance of the trackers are assessed according to the EN 50530 standard, using detailed simulation models...

  3. Model reference adaptive control (MRAC)-based parameter identification applied to surface-mounted permanent magnet synchronous motor

    Science.gov (United States)

    Zhong, Chongquan; Lin, Yaoyao

    2017-11-01

    In this work, a model reference adaptive control-based estimated algorithm is proposed for online multi-parameter identification of surface-mounted permanent magnet synchronous machines. By taking the dq-axis equations of a practical motor as the reference model and the dq-axis estimation equations as the adjustable model, a standard model-reference-adaptive-system-based estimator was established. Additionally, the Popov hyperstability principle was used in the design of the adaptive law to guarantee accurate convergence. In order to reduce the oscillation of identification result, this work introduces a first-order low-pass digital filter to improve precision regarding the parameter estimation. The proposed scheme was then applied to an SPM synchronous motor control system without any additional circuits and implemented using a DSP TMS320LF2812. For analysis, the experimental results reveal the effectiveness of the proposed method.

  4. Modeling and Control of VSC based DC Connection for Active Stall Wind Farms to Grid

    DEFF Research Database (Denmark)

    Iov, Florin; Sorensen, Poul; Hansen, Anca-Daniela

    2005-01-01

    Currently, there is an increasing trend to connect large MW wind farms to the transmission system. Therefore the power system becomes more vulnerable and dependent on the wind energy production. At the same time requirements that focus on the influence of the farms on the grid stability and power...... quality, and on the control capabilities of wind farms have already been established. The main trends of modem wind turbines/farms are clearly the variable speed operation and a grid connection through a power electronic interface, especially using doubly-fed induction generators. Using power electronics...... the control capabilities of these wind turbines/farms are extended and thus the grid requirements are fulfilled. However, the traditional squirrel-cage generators based wind turbines/wind farms directly connected to the grid does not have such control capabilities. They produce maximum possible power...

  5. Modelling and Control of VSC based DC Connection for Active Stall Wind Farms to Grid

    DEFF Research Database (Denmark)

    Iov, Florin; Sørensen, Poul; Hansen, Anca Daniela

    2006-01-01

    Currently, there is an increasing trend to connect large MW wind farms to the transmission system. Therefore the power system becomes more vulnerable and dependent on the wind energy production. At the same time requirements that focus on the influence of the farms on the grid stability and power...... quality, and on the control capabilities of wind farms have already been established. The main trends of modern wind turbines/farms are clearly the variable speed operation and a grid connection through a power electronic interface, especially using doubly-fed induction generators. Using power electronics...... the control capabilities of these wind turbines/farms are extended and thus the grid requirements are fulfilled.  However, the traditional squirrel-cage generators based wind turbines/wind farms directly connected to the grid does not have such control capabilities. They produce maximum possible power...

  6. Control of Process Operations and Monitoring of Product Qualities through Generic Model-based Framework in Crystallization Processes

    DEFF Research Database (Denmark)

    Abdul Samad, Noor Asma Fazli Bin

    A generic and systematic model-based framework for the design of a process monitoring and control system to achieve the desired crystal size distribution (CSD) and crystal shape for a wide range of crystallization processes has been developed. This framework combines a generic multi-dimensional m...

  7. 3D controlled-source electromagnetic modeling in anisotropic medium using edge-based finite element method

    DEFF Research Database (Denmark)

    Cai, Hongzhu; Xiong, Bin; Han, Muran

    2014-01-01

    This paper presents a linear edge-based finite element method for numerical modeling of 3D controlled-source electromagnetic data in an anisotropic conductive medium. We use a nonuniform rectangular mesh in order to capture the rapid change of diffusive electromagnetic field within the regions of...... are in a good agreement with the solutions obtained by the integral equation method....

  8. Feedforward-feedback hybrid control for magnetic shape memory alloy actuators based on the Krasnosel'skii-Pokrovskii model.

    Directory of Open Access Journals (Sweden)

    Miaolei Zhou

    Full Text Available As a new type of smart material, magnetic shape memory alloy has the advantages of a fast response frequency and outstanding strain capability in the field of microdrive and microposition actuators. The hysteresis nonlinearity in magnetic shape memory alloy actuators, however, limits system performance and further application. Here we propose a feedforward-feedback hybrid control method to improve control precision and mitigate the effects of the hysteresis nonlinearity of magnetic shape memory alloy actuators. First, hysteresis nonlinearity compensation for the magnetic shape memory alloy actuator is implemented by establishing a feedforward controller which is an inverse hysteresis model based on Krasnosel'skii-Pokrovskii operator. Secondly, the paper employs the classical Proportion Integration Differentiation feedback control with feedforward control to comprise the hybrid control system, and for further enhancing the adaptive performance of the system and improving the control accuracy, the Radial Basis Function neural network self-tuning Proportion Integration Differentiation feedback control replaces the classical Proportion Integration Differentiation feedback control. Utilizing self-learning ability of the Radial Basis Function neural network obtains Jacobian information of magnetic shape memory alloy actuator for the on-line adjustment of parameters in Proportion Integration Differentiation controller. Finally, simulation results show that the hybrid control method proposed in this paper can greatly improve the control precision of magnetic shape memory alloy actuator and the maximum tracking error is reduced from 1.1% in the open-loop system to 0.43% in the hybrid control system.

  9. Feedforward-feedback hybrid control for magnetic shape memory alloy actuators based on the Krasnosel'skii-Pokrovskii model.

    Science.gov (United States)

    Zhou, Miaolei; Zhang, Qi; Wang, Jingyuan

    2014-01-01

    As a new type of smart material, magnetic shape memory alloy has the advantages of a fast response frequency and outstanding strain capability in the field of microdrive and microposition actuators. The hysteresis nonlinearity in magnetic shape memory alloy actuators, however, limits system performance and further application. Here we propose a feedforward-feedback hybrid control method to improve control precision and mitigate the effects of the hysteresis nonlinearity of magnetic shape memory alloy actuators. First, hysteresis nonlinearity compensation for the magnetic shape memory alloy actuator is implemented by establishing a feedforward controller which is an inverse hysteresis model based on Krasnosel'skii-Pokrovskii operator. Secondly, the paper employs the classical Proportion Integration Differentiation feedback control with feedforward control to comprise the hybrid control system, and for further enhancing the adaptive performance of the system and improving the control accuracy, the Radial Basis Function neural network self-tuning Proportion Integration Differentiation feedback control replaces the classical Proportion Integration Differentiation feedback control. Utilizing self-learning ability of the Radial Basis Function neural network obtains Jacobian information of magnetic shape memory alloy actuator for the on-line adjustment of parameters in Proportion Integration Differentiation controller. Finally, simulation results show that the hybrid control method proposed in this paper can greatly improve the control precision of magnetic shape memory alloy actuator and the maximum tracking error is reduced from 1.1% in the open-loop system to 0.43% in the hybrid control system.

  10. A Source-Term Based Boundary Layer Bleed/Effusion Model for Passive Shock Control

    Science.gov (United States)

    Baurle, Robert A.; Norris, Andrew T.

    2011-01-01

    A modeling framework for boundary layer effusion has been developed based on the use of source (or sink) terms instead of the usual practice of specifying bleed directly as a boundary condition. This framework allows the surface boundary condition (i.e. isothermal wall, adiabatic wall, slip wall, etc.) to remain unaltered in the presence of bleed. This approach also lends itself to easily permit the addition of empirical models for second order effects that are not easily accounted for by simply defining effective transpiration values. Two effusion models formulated for supersonic flows have been implemented into this framework; the Doerffer/Bohning law and the Slater formulation. These models were applied to unit problems that contain key aspects of the flow physics applicable to bleed systems designed for hypersonic air-breathing propulsion systems. The ability of each model to predict bulk bleed properties was assessed, as well as the response of the boundary layer as it passes through and downstream of a porous bleed system. The model assessment was performed with and without the presence of shock waves. Three-dimensional CFD simulations that included the geometric details of the porous plate bleed systems were also carried out to supplement the experimental data, and provide additional insights into the bleed flow physics. Overall, both bleed formulations fared well for the tests performed in this study. However, the sample of test problems considered in this effort was not large enough to permit a comprehensive validation of the models.

  11. The Role of Model Fidelity in Model Predictive Control Based Hazard Avoidance in Unmanned Ground Vehicles Using Lidar Sensors

    Science.gov (United States)

    2013-03-08

    34 VPH : A New Laser Radar Based Obstacle Avoidance Method for Intelligent Mobile Robots", Proceedings of World Congress on Intelligent Control and...Automation, Hangzhou, China, 5, pp. 4681- 4685. [9] Gong, J., Duan, Y., Man, Y., and Xiong, G., 2007, " VPH +: An Enhanced Vector Polar Histogram Method

  12. A study on the energy management in domestic micro-grids based on Model Predictive Control strategies

    International Nuclear Information System (INIS)

    Bruni, G.; Cordiner, S.; Mulone, V.; Rocco, V.; Spagnolo, F.

    2015-01-01

    Highlights: • Development of a domestic microgrid and house thermal model. • Model Predictive Control for simultaneous management of power flow and thermal comfort. • Modeling of summer and winter typical conditions. • Comparison with standard rule based controller results. • Fuel cell downsizing potential of output is up to 60%. - Abstract: In this paper a Model Predictive Control (MPC) logic, based on weather forecasts, has been applied to the analysis of power management in a domestic off-grid system. The system is laid out as the integration of renewable energy conversion devices (Photovoltaic, PV), a high efficiency energy conversion programmable system (a Fuel Cell, FC) and an electrochemical energy storage (batteries). The control strategy has the objective of minimizing energy costs, while maintaining the optimal environmental comfort in the house, thus optimizing the use of renewable sources. To that aim, a validated numerical model of the whole system has been developed, and simulations have been carried out for winter and summer periods. Performances attainable with a MPC-based logic have been evaluated in comparison with a standard Rule Based Control logic, by means of costs and efficiency parameters of the micro-grid. Temperature violations have been taken into account to represent the impact of the control on comfort. Results show an improvement of the house comfort conditions and a lower use (on average 14.5%) of primary fossil energy. This is due both to a reduction of required energy, and to an increased use of renewable energy sources. Moreover, the modulation of the HVAC load and of the FC operation gives a reduction of requested power by approximately 40%. Smoother battery pack charge and discharge processes are also obtained. As a main positive effect, a reduction of the FC powerplant size and an increase of its durability seems feasible, leading to an overall reduction of capital costs

  13. Controlling for false negatives in agent-based models

    DEFF Research Database (Denmark)

    Secchi, Davide; Seri, Raffaello

    2017-01-01

    This article is concerned with the study of statistical power in agent-based modeling (ABM). After an overview of classic statistics theory on how to interpret Type-II error (whose occurrence is also referred to as a false negative) and power, the manuscript presents a study on ABM simulation art...... of simulation runs to reach an appropriate level of power. The study concludes with the importance for organizational behavior scholars to perform their models in an attempt to reach a power of 0.95 or higher at the 0.01 significance level....

  14. Investigation of a Ball Screw Feed Drive System Based on Dynamic Modeling for Motion Control

    Directory of Open Access Journals (Sweden)

    Yi-Cheng Huang

    2017-06-01

    Full Text Available This paper examines the frequency response relationship between the ball screw nut preload, ball screw torsional stiffness variations and table mass effect for a single-axis feed drive system. Identification for the frequency response of an industrial ball screw drive system is very important for the precision motion when the vibration modes of the system are critical for controller design. In this study, there is translation and rotation modes of a ball screw feed drive system when positioning table is actuated by a servo motor. A lumped dynamic model to study the ball nut preload variation and torsional stiffness of the ball screw drive system is derived first. The mathematical modeling and numerical simulation provide the information of peak frequency response as the different levels of ball nut preload, ball screw torsional stiffness and table mass. The trend of increasing preload will indicate the abrupt peak change in frequency response spectrum analysis in some mode shapes. This study provides an approach to investigate the dynamic frequency response of a ball screw drive system, which provides significant information for better control performance when precise motion control is concerned.

  15. Modeling and Optimal Control of a Class of Warfare Hybrid Dynamic Systems Based on Lanchester (n,1) Attrition Model

    OpenAIRE

    Chen, Xiangyong; Zhang, Ancai

    2014-01-01

    For the particularity of warfare hybrid dynamic process, a class of warfare hybrid dynamic systems is established based on Lanchester equation in a (n,1) battle, where a heterogeneous force of n different troop types faces a homogeneous force. This model can be characterized by the interaction of continuous-time models (governed by Lanchester equation), and discrete event systems (described by variable tactics). Furthermore, an expository discussion is presented on an optimal variable tact...

  16. New approaches to infection prevention and control: implementing a risk-based model regionally.

    Science.gov (United States)

    Wale, Martin; Kibsey, Pamela; Young, Lisa; Dobbyn, Beverly; Archer, Jana

    2016-06-01

    Infectious disease outbreaks result in substantial inconvenience to patients and disruption of clinical activity. Between 1 April 2008 and 31 March 2009, the Vancouver Island Health Authority (Island Health) declared 16 outbreaks of Vancomycin Resistant Enterococci and Clostridium difficile in acute care facilities. As a result, infection prevention and control became one of Island Health's highest priorities. Quality improvement methodology, which promotes a culture of co-production between front-line staff, physicians and Infection Control Practitioners, was used to develop and test a bundle of changes in practices. A series of rapid Plan-Do-Study-Act cycles, specific to decreasing hospital-acquired infections, were undertaken by a community hospital, selected for its size, clinical specialty representation, and enthusiasm amongst staff and physicians for innovation and change. Positive results were incorporated into practice at the test site, and then introduced throughout the rest of the Health Authority. The changes implemented as a result of this study have enabled better control of antibiotic resistant organisms and have minimized disruption to routine activity, as well as saving an estimated $6.5 million per annum. When outbreaks do occur, they are now controlled much more promptly, even in existing older facilities. Through this process, we have changed our approach in Infection Prevention and Control (IPAC) from a rules-based approach to one that is risk-based, focusing attention on identifying and managing high-risk situations. © The Author 2016. Published by Oxford University Press in association with the International Society for Quality in Health Care; all rights reserved.

  17. Model-Based Evaluation of Strategies to Control Brucellosis in China.

    Science.gov (United States)

    Li, Ming-Tao; Sun, Gui-Quan; Zhang, Wen-Yi; Jin, Zhen

    2017-03-12

    Brucellosis, the most common zoonotic disease worldwide, represents a great threat to animal husbandry with the potential to cause enormous economic losses. Brucellosis has become a major public health problem in China, and the number of human brucellosis cases has increased dramatically in recent years. In order to evaluate different intervention strategies to curb brucellosis transmission in China, a novel mathematical model with a general indirect transmission incidence rate was presented. By comparing the results of three models using national human disease data and 11 provinces with high case numbers, the best fitted model with standard incidence was used to investigate the potential for future outbreaks. Estimated basic reproduction numbers were highly heterogeneous, varying widely among provinces. The local basic reproduction numbers of provinces with an obvious increase in incidence were much larger than the average for the country as a whole, suggesting that environment-to-individual transmission was more common than individual-to-individual transmission. We concluded that brucellosis can be controlled through increasing animal vaccination rates, environment disinfection frequency, or elimination rates of infected animals. Our finding suggests that a combination of animal vaccination, environment disinfection, and elimination of infected animals will be necessary to ensure cost-effective control for brucellosis.

  18. A Dynamic Model for the Evaluation of Aircraft Engine Icing Detection and Control-Based Mitigation Strategies

    Science.gov (United States)

    Simon, Donald L.; Rinehart, Aidan W.; Jones, Scott M.

    2017-01-01

    Aircraft flying in regions of high ice crystal concentrations are susceptible to the buildup of ice within the compression system of their gas turbine engines. This ice buildup can restrict engine airflow and cause an uncommanded loss of thrust, also known as engine rollback, which poses a potential safety hazard. The aviation community is conducting research to understand this phenomena, and to identify avoidance and mitigation strategies to address the concern. To support this research, a dynamic turbofan engine model has been created to enable the development and evaluation of engine icing detection and control-based mitigation strategies. This model captures the dynamic engine response due to high ice water ingestion and the buildup of ice blockage in the engines low pressure compressor. It includes a fuel control system allowing engine closed-loop control effects during engine icing events to be emulated. The model also includes bleed air valve and horsepower extraction actuators that, when modulated, change overall engine operating performance. This system-level model has been developed and compared against test data acquired from an aircraft turbofan engine undergoing engine icing studies in an altitude test facility and also against outputs from the manufacturers customer deck. This paper will describe the model and show results of its dynamic response under open-loop and closed-loop control operating scenarios in the presence of ice blockage buildup compared against engine test cell data. Planned follow-on use of the model for the development and evaluation of icing detection and control-based mitigation strategies will also be discussed. The intent is to combine the model and control mitigation logic with an engine icing risk calculation tool capable of predicting the risk of engine icing based on current operating conditions. Upon detection of an operating region of risk for engine icing events, the control mitigation logic will seek to change the

  19. Optimal blood glucose control in diabetes mellitus treatment using dynamic programming based on Ackerman’s linear model

    Science.gov (United States)

    Pradanti, Paskalia; Hartono

    2018-03-01

    Determination of insulin injection dose in diabetes mellitus treatment can be considered as an optimal control problem. This article is aimed to simulate optimal blood glucose control for patient with diabetes mellitus. The blood glucose regulation of diabetic patient is represented by Ackerman’s Linear Model. This problem is then solved using dynamic programming method. The desired blood glucose level is obtained by minimizing the performance index in Lagrange form. The results show that dynamic programming based on Ackerman’s Linear Model is quite good to solve the problem.

  20. On-line monitoring and modelling based process control of high rate nitrification - lab scale experimental results

    Energy Technology Data Exchange (ETDEWEB)

    Pirsing, A. [Technische Univ. Berlin (Germany). Inst. fuer Verfahrenstechnik; Wiesmann, U. [Technische Univ. Berlin (Germany). Inst. fuer Verfahrenstechnik; Kelterbach, G. [Technische Univ. Berlin (Germany). Inst. fuer Mess- und Regelungstechnik; Schaffranietz, U. [Technische Univ. Berlin (Germany). Inst. fuer Mess- und Regelungstechnik; Roeck, H. [Technische Univ. Berlin (Germany). Inst. fuer Mess- und Regelungstechnik; Eichner, B. [Technische Univ. Berlin (Germany). Inst. fuer Anorganische und Analytische Chemie; Szukal, S. [Technische Univ. Berlin (Germany). Inst. fuer Anorganische und Analytische Chemie; Schulze, G. [Technische Univ. Berlin (Germany). Inst. fuer Anorganische und Analytische Chemie

    1996-09-01

    This paper presents a new concept for the control of nitrification in highly polluted waste waters. The approach is based on mathematical modelling. To determine the substrate degradation rates of the microorganisms involved, a mathematical model using gas measurement is used. A fuzzy-controller maximises the capacity utilisation efficiencies. The experiments carried out in a lab-scale reactor demonstrate that even with highly varying ammonia concentrations in the influent, the nitrogen concentrations in the effluent can be kept within legal limits. (orig.). With 11 figs.

  1. An equilibrium-point model of electromyographic patterns during single-joint movements based on experimentally reconstructed control signals.

    Science.gov (United States)

    Latash, M L; Goodman, S R

    1994-01-01

    The purpose of this work has been to develop a model of electromyographic (EMG) patterns during single-joint movements based on a version of the equilibrium-point hypothesis, a method for experimental reconstruction of the joint compliant characteristics, the dual-strategy hypothesis, and a kinematic model of movement trajectory. EMG patterns are considered emergent properties of hypothetical control patterns that are equally affected by the control signals and peripheral feedback reflecting actual movement trajectory. A computer model generated the EMG patterns based on simulated movement kinematics and hypothetical control signals derived from the reconstructed joint compliant characteristics. The model predictions have been compared to published recordings of movement kinematics and EMG patterns in a variety of movement conditions, including movements over different distances, at different speeds, against different-known inertial loads, and in conditions of possible unexpected decrease in the inertial load. Changes in task parameters within the model led to simulated EMG patterns qualitatively similar to the experimentally recorded EMG patterns. The model's predictive power compares it favourably to the existing models of the EMG patterns. Copyright © 1994. Published by Elsevier Ltd.

  2. Free terminal time optimal control problem of an HIV model based on a conjugate gradient method.

    Science.gov (United States)

    Jang, Taesoo; Kwon, Hee-Dae; Lee, Jeehyun

    2011-10-01

    The minimum duration of treatment periods and the optimal multidrug therapy for human immunodeficiency virus (HIV) type 1 infection are considered. We formulate an optimal tracking problem, attempting to drive the states of the model to a "healthy" steady state in which the viral load is low and the immune response is strong. We study an optimal time frame as well as HIV therapeutic strategies by analyzing the free terminal time optimal tracking control problem. The minimum duration of treatment periods and the optimal multidrug therapy are found by solving the corresponding optimality systems with the additional transversality condition for the terminal time. We demonstrate by numerical simulations that the optimal dynamic multidrug therapy can lead to the long-term control of HIV by the strong immune response after discontinuation of therapy.

  3. Model predictive control of PMSG-based wind turbines for frequency regulation in an isolated grid

    DEFF Research Database (Denmark)

    Wang, Haixin; Yang, Junyou; Ma, Yiming

    2017-01-01

    This paper proposes a frequency regulation strategy applied to wind turbine generators (WTGs) in an isolated grid. In order to complement active power shortage caused by sudden load or wind speed change, an improved deloading method is proposed to solve inconsistent regulation capabilities...... in different speed regions and provide WTGs a certain capacity of power reserves. Considering the torque compensation may bring about power oscillation, speed reference of conventional pitch control system should be reset. Moreover, to suppress disturbances of load and wind speed as well as overcome dependence...... on system parameters, a model predictive controller (MPC) of wind farm is designed to generate torque compensation for each deloaded WTG. The key feature of this strategy is that each WTG reacts to grid disturbances in different ways, which depends on generator speeds. Hardware-in-the-loop simulation...

  4. Rapid Deployment of Optimal Control for Building HVAC Systems using Innovative Software Tools and a Hybrid Heuristic/Model Based Control Approach

    Science.gov (United States)

    2017-03-21

    Monitoring and Verification Protocol LCDR Lieutenant Commander ME Mechanical Engineering MPC Model Predictive Control: a model-based system...Activity PE Professional Engineer PG&E Pacific Gas & Electric : a California utility company PI Proportional + Integral: a common software element...INTRODUCTION The Department of Defense (DoD) spends approximately $4 billion per year on facility energy consumption to power and fuel over 500

  5. Unhealthy weight control behaviours in adolescent girls: a process model based on self-determination theory

    OpenAIRE

    Thøgersen-Ntoumani, Cecilie; Ntoumanis, Nikos

    2009-01-01

    This study used self-determination theory (Deci, E.L., & Ryan, R.M. (2000). The 'what' and 'why' of goal pursuits: Human needs and the self-determination of behavior. Psychological Inquiry, 11, 227-268.) to examine predictors of body image concerns and unhealthy weight control behaviours in a sample of 350 Greek adolescent girls. A process model was tested which proposed that perceptions of parental autonomy support and two life goals (health and image) would predict adolescents' degree of sa...

  6. Model predictive control-based dynamic coordinate strategy for hydraulic hub-motor auxiliary system of a heavy commercial vehicle

    Science.gov (United States)

    Zeng, Xiaohua; Li, Guanghan; Yin, Guodong; Song, Dafeng; Li, Sheng; Yang, Nannan

    2018-02-01

    Equipping a hydraulic hub-motor auxiliary system (HHMAS), which mainly consists of a hydraulic variable pump, a hydraulic hub-motor, a hydraulic valve block and hydraulic accumulators, with part-time all-wheel-drive functions improves the power performance and fuel economy of heavy commercial vehicles. The coordinated control problem that occurs when HHMAS operates in the auxiliary drive mode is addressed in this paper; the solution to this problem is the key to the maximization of HHMAS. To achieve a reasonable distribution of the engine power between mechanical and hydraulic paths, a nonlinear control scheme based on model predictive control (MPC) is investigated. First, a nonlinear model of HHMAS with vehicle dynamics and tire slip characteristics is built, and a controller-design-oriented model is simplified. Then, a steady-state feedforward + dynamic MPC feedback controller (FMPC) is designed to calculate the control input sequence of engine torque and hydraulic variable pump displacement. Finally, the controller is tested in the MATLAB/Simulink and AMESim co-simulation platform and the hardware-in-the-loop experiment platform, and its performance is compared with that of the existing proportional-integral-derivative controller and the feedforward controller under the same conditions. Simulation results show that the designed FMPC has the best performance, and control performance can be guaranteed in a real-time environment. Compared with the tracking control error of the feedforward controller, that of the designed FMPC is decreased by 85% and the traction efficiency performance is improved by 23% under a low-friction-surface condition. Moreover, under common road conditions for heavy commercial vehicles, the traction force can increase up to 13.4-15.6%.

  7. Control-volume-based model of the steam-water injector flow

    Science.gov (United States)

    Kwidziński, Roman

    2010-03-01

    The paper presents equations of a mathematical model to calculate flow parameters in characteristic cross-sections in the steam-water injector. In the model, component parts of the injector (steam nozzle, water nozzle, mixing chamber, condensation wave region, diffuser) are treated as a series of connected control volumes. At first, equations for the steam nozzle and water nozzle are written and solved for known flow parameters at the injector inlet. Next, the flow properties in two-phase flow comprising mixing chamber and condensation wave region are determined from mass, momentum and energy balance equations. Then, water compression in diffuser is taken into account to evaluate the flow parameters at the injector outlet. Irreversible losses due to friction, condensation and shock wave formation are taken into account for the flow in the steam nozzle. In two-phase flow domain, thermal and mechanical nonequilibrium between vapour and liquid is modelled. For diffuser, frictional pressure loss is considered. Comparison of the model predictions with experimental data shows good agreement, with an error not exceeding 15% for discharge (outlet) pressure and 1 K for outlet temperature.

  8. Healthy habits: efficacy of simple advice on weight control based on a habit-formation model.

    Science.gov (United States)

    Lally, P; Chipperfield, A; Wardle, J

    2008-04-01

    To evaluate the efficacy of a simple weight loss intervention, based on principles of habit formation. An exploratory trial in which overweight and obese adults were randomized either to a habit-based intervention condition (with two subgroups given weekly vs monthly weighing; n=33, n=36) or to a waiting-list control condition (n=35) over 8 weeks. Intervention participants were followed up for 8 months. A total of 104 adults (35 men, 69 women) with an average BMI of 30.9 kg m(-2). Intervention participants were given a leaflet containing advice on habit formation and simple recommendations for eating and activity behaviours promoting negative energy balance, together with a self-monitoring checklist. Weight change over 8 weeks in the intervention condition compared with the control condition and weight loss maintenance over 32 weeks in the intervention condition. At 8 weeks, people in the intervention condition had lost significantly more weight (mean=2.0 kg) than those in the control condition (0.4 kg), with no difference between weekly and monthly weighing subgroups. At 32 weeks, those who remained in the study had lost an average of 3.8 kg, with 54% losing 5% or more of their body weight. An intention-to-treat analysis (based on last-observation-carried-forward) reduced this to 2.6 kg, with 26% achieving a 5% weight loss. This easily disseminable, low-cost, simple intervention produced clinically significant weight loss. In limited resource settings it has potential as a tool for obesity management.

  9. Model-based derivation, analysis and control of unstable microaerobic steady-states--considering Rhodospirillum rubrum as an example.

    Science.gov (United States)

    Carius, Lisa; Rumschinski, Philipp; Faulwasser, Timm; Flockerzi, Dietrich; Grammel, Hartmut; Findeisen, Rolf

    2014-04-01

    Microaerobic (oxygen-limited) conditions are critical for inducing many important microbial processes in industrial or environmental applications. At very low oxygen concentrations, however, the process performance often suffers from technical limitations. Available dissolved oxygen measurement techniques are not sensitive enough and thus control techniques, that can reliable handle these conditions, are lacking. Recently, we proposed a microaerobic process control strategy, which overcomes these restrictions and allows to assess different degrees of oxygen limitation in bioreactor batch cultivations. Here, we focus on the design of a control strategy for the automation of oxygen-limited continuous cultures using the microaerobic formation of photosynthetic membranes (PM) in Rhodospirillum rubrum as model phenomenon. We draw upon R. rubrum since the considered phenomenon depends on the optimal availability of mixed-carbon sources, hence on boundary conditions which make the process performance challenging. Empirically assessing these specific microaerobic conditions is scarcely practicable as such a process reacts highly sensitive to changes in the substrate composition and the oxygen availability in the culture broth. Therefore, we propose a model-based process control strategy which allows to stabilize steady-states of cultures grown under these conditions. As designing the appropriate strategy requires a detailed knowledge of the system behavior, we begin by deriving and validating an unstructured process model. This model is used to optimize the experimental conditions, and identify properties of the system which are critical for process performance. The derived model facilitates the good process performance via the proposed optimal control strategy. In summary the presented model-based control strategy allows to access and maintain microaerobic steady-states of interest and to precisely and efficiently transfer the culture from one stable microaerobic steady

  10. Model-based analysis and control of a network of basal ganglia spiking neurons in the normal and Parkinsonian states

    Science.gov (United States)

    Liu, Jianbo; Khalil, Hassan K.; Oweiss, Karim G.

    2011-08-01

    Controlling the spatiotemporal firing pattern of an intricately connected network of neurons through microstimulation is highly desirable in many applications. We investigated in this paper the feasibility of using a model-based approach to the analysis and control of a basal ganglia (BG) network model of Hodgkin-Huxley (HH) spiking neurons through microstimulation. Detailed analysis of this network model suggests that it can reproduce the experimentally observed characteristics of BG neurons under a normal and a pathological Parkinsonian state. A simplified neuronal firing rate model, identified from the detailed HH network model, is shown to capture the essential network dynamics. Mathematical analysis of the simplified model reveals the presence of a systematic relationship between the network's structure and its dynamic response to spatiotemporally patterned microstimulation. We show that both the network synaptic organization and the local mechanism of microstimulation can impose tight constraints on the possible spatiotemporal firing patterns that can be generated by the microstimulated network, which may hinder the effectiveness of microstimulation to achieve a desired objective under certain conditions. Finally, we demonstrate that the feedback control design aided by the mathematical analysis of the simplified model is indeed effective in driving the BG network in the normal and Parskinsonian states to follow a prescribed spatiotemporal firing pattern. We further show that the rhythmic/oscillatory patterns that characterize a dopamine-depleted BG network can be suppressed as a direct consequence of controlling the spatiotemporal pattern of a subpopulation of the output Globus Pallidus internalis (GPi) neurons in the network. This work may provide plausible explanations for the mechanisms underlying the therapeutic effects of deep brain stimulation (DBS) in Parkinson's disease and pave the way towards a model-based, network level analysis and closed

  11. Robust observer based control for axial offset in pressurized-water nuclear reactors based on the multipoint reactor model using Lyapunov approach

    Energy Technology Data Exchange (ETDEWEB)

    Zaidabadinejad, Majid; Ansarifar, Gholam Reza [Isfahan Univ. (Iran, Islamic Republic of). Dept. of Nuclear Engineering

    2017-11-15

    In nuclear reactor imbalance of axial power distribution induces xenon oscillations. These fluctuations must be maintained bounded within allowable limits. Otherwise, the nuclear power plant could become unstable. Therefore, bounded these oscillations is considered to be a restriction for the load following operation. Also, in order to design the nuclear reactor control systems, poisons concentrations, especially xenon must be accessible. But, physical measurement of these parameters is impossible. In this paper, for the first time, in order to estimate the axial xenon oscillations and ensures these oscillations are kept bounded within allowable limits during load-following operation, a robust observer based nonlinear control based on multipoint kinetics reactor model for pressurized-water nuclear reactors is presented. The reactor core is simulated based on the multi-point nuclear reactor model (neutronic and thermal-hydraulic). Simulation results are presented to demonstrate the effectiveness of the proposed observer based controller for the load-following operation.

  12. Robust observer based control for axial offset in pressurized-water nuclear reactors based on the multipoint reactor model using Lyapunov approach

    International Nuclear Information System (INIS)

    Zaidabadinejad, Majid; Ansarifar, Gholam Reza

    2017-01-01

    In nuclear reactor imbalance of axial power distribution induces xenon oscillations. These fluctuations must be maintained bounded within allowable limits. Otherwise, the nuclear power plant could become unstable. Therefore, bounded these oscillations is considered to be a restriction for the load following operation. Also, in order to design the nuclear reactor control systems, poisons concentrations, especially xenon must be accessible. But, physical measurement of these parameters is impossible. In this paper, for the first time, in order to estimate the axial xenon oscillations and ensures these oscillations are kept bounded within allowable limits during load-following operation, a robust observer based nonlinear control based on multipoint kinetics reactor model for pressurized-water nuclear reactors is presented. The reactor core is simulated based on the multi-point nuclear reactor model (neutronic and thermal-hydraulic). Simulation results are presented to demonstrate the effectiveness of the proposed observer based controller for the load-following operation.

  13. Model-Based Control of a Nonlinear Aircraft Engine Simulation using an Optimal Tuner Kalman Filter Approach

    Science.gov (United States)

    Connolly, Joseph W.; Csank, Jeffrey Thomas; Chicatelli, Amy; Kilver, Jacob

    2013-01-01

    This paper covers the development of a model-based engine control (MBEC) methodology featuring a self tuning on-board model applied to an aircraft turbofan engine simulation. Here, the Commercial Modular Aero-Propulsion System Simulation 40,000 (CMAPSS40k) serves as the MBEC application engine. CMAPSS40k is capable of modeling realistic engine performance, allowing for a verification of the MBEC over a wide range of operating points. The on-board model is a piece-wise linear model derived from CMAPSS40k and updated using an optimal tuner Kalman Filter (OTKF) estimation routine, which enables the on-board model to self-tune to account for engine performance variations. The focus here is on developing a methodology for MBEC with direct control of estimated parameters of interest such as thrust and stall margins. Investigations using the MBEC to provide a stall margin limit for the controller protection logic are presented that could provide benefits over a simple acceleration schedule that is currently used in traditional engine control architectures.

  14. Testing seasonal and long-term controls of streamwater DOC using empirical and process-based models.

    Science.gov (United States)

    Futter, Martyn N; de Wit, Heleen A

    2008-12-15

    Concentrations of dissolved organic carbon (DOC) in surface waters are increasing across Europe and parts of North America. Several mechanisms have been proposed to explain these increases including reductions in acid deposition, change in frequency of winter storms and changes in temperature and precipitation patterns. We used two modelling approaches to identify the mechanisms responsible for changing surface water DOC concentrations. Empirical regression analysis and INCA-C, a process-based model of stream-water DOC, were used to simulate long-term (1986--2003) patterns in stream water DOC concentrations in a small boreal stream. Both modelling approaches successfully simulated seasonal and inter-annual patterns in DOC concentration. In both models, seasonal patterns of DOC concentration were controlled by hydrology and inter-annual patterns were explained by climatic variation. There was a non-linear relationship between warmer summer temperatures and INCA-C predicted DOC. Only the empirical model was able to satisfactorily simulate the observed long-term increase in DOC. The observed long-term trends in DOC are likely to be driven by in-soil processes controlled by SO4(2-) and Cl(-) deposition, and to a lesser extent by temperature-controlled processes. Given the projected changes in climate and deposition, future modelling and experimental research should focus on the possible effects of soil temperature and moisture on organic carbon production, sorption and desorption rates, and chemical controls on organic matter solubility.

  15. Novel variable structure control for the temperature of PEM fuel cell stack based on the dynamic thermal affine model

    International Nuclear Information System (INIS)

    Li Xi; Deng Zhonghua; Wei Dong; Xu Chunshan; Cao Guangyi

    2011-01-01

    Highlights: → The affine state space control-oriented model is designed and realized for the variant structure control (VSC) strategy. → The VSC with rapid-smooth reaching law and rapid-convergent sliding mode is presented for the PEMFC stack temperature. → Numerical results show that the method can control the operating temperature to reach the target value satisfactorily. - Abstract: Dynamic thermal management of proton exchange membrane fuel cell stack (PEMFC) is a very important aspect, which plays an important role on electro-reaction. Its variation also has a significant influence on the performance and lifespan of PEMFC stack. The temperature of stack should be controlled efficiently, which has great impacts on the performance of PEMFC due to the thermal variation. Based on the control-oriented dynamic thermal affine model identified by optimization algorithm, a novel variable structures control (VSC) with rapid-smooth reaching law (RSRL) and rapid-convergent sliding mode (FCSM) is presented for the temperature control system of PEMFC stack. Numerical test results show that the method can control the operating temperature to reach the target value satisfactorily, which proves the effectiveness and robustness of the algorithm.

  16. Hand interception of occluded motion in humans: a test of model-based vs. on-line control.

    Science.gov (United States)

    La Scaleia, Barbara; Zago, Myrka; Lacquaniti, Francesco

    2015-09-01

    Two control schemes have been hypothesized for the manual interception of fast visual targets. In the model-free on-line control, extrapolation of target motion is based on continuous visual information, without resorting to physical models. In the model-based control, instead, a prior model of target motion predicts the future spatiotemporal trajectory. To distinguish between the two hypotheses in the case of projectile motion, we asked participants to hit a ball that rolled down an incline at 0.2 g and then fell in air at 1 g along a parabola. By varying starting position, ball velocity and trajectory differed between trials. Motion on the incline was always visible, whereas parabolic motion was either visible or occluded. We found that participants were equally successful at hitting the falling ball in both visible and occluded conditions. Moreover, in different trials the intersection points were distributed along the parabolic trajectories of the ball, indicating that subjects were able to extrapolate an extended segment of the target trajectory. Remarkably, this trend was observed even at the very first repetition of movements. These results are consistent with the hypothesis of model-based control, but not with on-line control. Indeed, ball path and speed during the occlusion could not be extrapolated solely from the kinematic information obtained during the preceding visible phase. The only way to extrapolate ball motion correctly during the occlusion was to assume that the ball would fall under gravity and air drag when hidden from view. Such an assumption had to be derived from prior experience. Copyright © 2015 the American Physiological Society.

  17. Space construction base control system

    Science.gov (United States)

    1978-01-01

    Aspects of an attitude control system were studied and developed for a large space base that is structurally flexible and whose mass properties change rather dramatically during its orbital lifetime. Topics of discussion include the following: (1) space base orbital pointing and maneuvering; (2) angular momentum sizing of actuators; (3) momentum desaturation selection and sizing; (4) multilevel control technique applied to configuration one; (5) one-dimensional model simulation; (6) N-body discrete coordinate simulation; (7) structural analysis math model formulation; and (8) discussion of control problems and control methods.

  18. Arduino based laser control

    OpenAIRE

    Bernal Muñoz, Ferran

    2015-01-01

    ARDUINO is a vey usefull platform for prototypes. In this project ARDUINO will be used for controling a Semiconductor Tuneable Laser. [ANGLÈS] Diode laser for communications control based on an Arduino board. Temperature control implementation. Software and hardware protection for the laser implementation. [CASTELLÀ] Control de un láser de comunicaciones ópticas desde el ordenador utilizando una placa Arduino. Implementación de un control de temperatura y protección software y hardware ...

  19. Controlling chaos in Internet congestion control model

    International Nuclear Information System (INIS)

    Chen Liang; Wang Xiaofan; Han Zhengzhi

    2004-01-01

    The TCP end-to-end congestion control plus RED router queue management can be modeled as a discrete-time dynamical system, which may create complex bifurcating and chaotic behavior. Based on the basic features of the TCP-RED model, we propose a time-dependent delayed feedback control algorithm to control chaos in the system by perturbing the accessible RED parameter p max . This method is able to stabilized a router queue occupancy at a level without knowing the exact knowledge of the network. Further, we study the situation of the presence of the UDP traffic

  20. Controlling chaos in Internet congestion control model

    Energy Technology Data Exchange (ETDEWEB)

    Chen Liang E-mail: chenmoon110@yahoo.com.cn; Wang Xiaofan; Han Zhengzhi

    2004-07-01

    The TCP end-to-end congestion control plus RED router queue management can be modeled as a discrete-time dynamical system, which may create complex bifurcating and chaotic behavior. Based on the basic features of the TCP-RED model, we propose a time-dependent delayed feedback control algorithm to control chaos in the system by perturbing the accessible RED parameter p{sub max}. This method is able to stabilized a router queue occupancy at a level without knowing the exact knowledge of the network. Further, we study the situation of the presence of the UDP traffic.

  1. New Smith Internal Model Control of Two-Motor Drive System Based on Neural Network Generalized Inverse

    Directory of Open Access Journals (Sweden)

    Guohai Liu

    2016-01-01

    Full Text Available Multimotor drive system is widely applied in industrial control system. Considering the characteristics of multi-input multioutput, nonlinear, strong-coupling, and time-varying delay in two-motor drive systems, this paper proposes a new Smith internal model (SIM control method, which is based on neural network generalized inverse (NNGI. This control strategy adopts the NNGI system to settle the decoupling issue and utilizes the SIM control structure to solve the delay problem. The NNGI method can decouple the original system into several composite pseudolinear subsystems and also complete the pole-zero allocation of subsystems. Furthermore, based on the precise model of pseudolinear system, the proposed SIM control structure is used to compensate the network delay and enhance the interference resisting the ability of the whole system. Both simulation and experimental results are given, verifying that the proposed control strategy can effectively solve the decoupling problem and exhibits the strong robustness to load impact disturbance at various operations.

  2. Modeling the controllable pH-responsive swelling and pore size of networked alginate based biomaterials.

    Science.gov (United States)

    Chan, Ariel W; Neufeld, Ronald J

    2009-10-01

    Semisynthetic network alginate polymer (SNAP), synthesized by acetalization of linear alginate with di-aldehyde, is a pH-responsive tetrafunctionally linked 3D gel network, and has potential application in oral delivery of protein therapeutics and active biologicals, and as tissue bioscaffold for regenerative medicine. A constitutive polyelectrolyte gel model based on non-Gaussian polymer elasticity, Flory-Huggins liquid lattice theory, and non-ideal Donnan membrane equilibria was derived, to describe SNAP gel swelling in dilute and ionic solutions containing uni-univalent, uni-bivalent, bi-univalent or bi-bi-valent electrolyte solutions. Flory-Huggins interaction parameters as a function of ionic strength and characteristic ratio of alginates of various molecular weights were determined experimentally to numerically predict SNAP hydrogel swelling. SNAP hydrogel swells pronouncedly to 1000 times in dilute solution, compared to its compact polymer volume, while behaving as a neutral polymer with limited swelling in high ionic strength or low pH solutions. The derived model accurately describes the pH-responsive swelling of SNAP hydrogel in acid and alkaline solutions of wide range of ionic strength. The pore sizes of the synthesized SNAP hydrogels of various crosslink densities were estimated from the derived model to be in the range of 30-450 nm which were comparable to that measured by thermoporometry, and diffusion of bovine serum albumin. The derived equilibrium swelling model can characterize hydrogel structure such as molecular weight between crosslinks and crosslinking density, or can be used as predictive model for swelling, pore size and mechanical properties if gel structural information is known, and can potentially be applied to other point-link network polyelectrolytes such as hyaluronic acid gel.

  3. Sliding Mode Control of Diesel Engine Air-path System With Dual-loop EGR and VGT Based on the Reduced-order Model

    Directory of Open Access Journals (Sweden)

    Kim Sooyoung

    2016-01-01

    Full Text Available This paper presents the design of a model-based controller for the diesel engine air-path system. The controller is implemented based on a reduced order model consisting of only pressure and power dynamics with practical concerns. To deal with the model uncertainties effectively, a sliding mode controller, which is robust to model uncertainties, is proposed for the air-path system. The control performance of the proposed control scheme is verified through simulation with the valid plant model of a 6,000cc heavy duty diesel engine.

  4. Model-based drug administration : current status of target-controlled infusion and closed-loop control

    NARCIS (Netherlands)

    Kuizenga, Merel H.; Vereecke, Hugo E. M.; Struys, Michel M. R. F.

    Purpose of review Drug administration might be optimized by incorporating pharmacokinetic-dynamic (PK/PD) principles and control engineering theories. This review gives an update of the actual status of target-controlled infusion (TCI) and closed-loop computer-controlled drug administration and the

  5. Model-based control and application of a thermomanagement engine cooling system; Modellbasierte Regelung und Applikation eines Thermomanagement-Motorkuehlsystems

    Energy Technology Data Exchange (ETDEWEB)

    Mann, K.; Zeitz, M. [Robert Bosch GmbH, Stuttgart (Germany); Schmitt, M.

    2002-07-01

    Efficient heat management is a central development goal today. So-called thermomanagement systems cool the engine as required, ensuring energy-efficient control of a given engine temperature. The contribution presents a model-based process guidance structure and an application concept which can be adapted to various thermomanagement systems, ensureing high control quality and low application expenditure. Application requirements are minimized by model-based generation of the greater part of the application data. [German] Im Bereich der Fahrzeugentwicklung wird derzeit intensiv an Konzepten fuer ein effizienteres Waermemanagement gearbeitet. Mit einem sogenannten Thermomanagement-System wird der Motor bedarfsgerecht gekuehlt. Hierfuer wird eine vorgegebene Motortemperatur moeglichst energieeffizient geregelt. In dem Beitrag werden eine modellbasierte Prozessfuehrungsstruktur und ein Applikationskonzept vorgestellt, die flexibel fuer verschiedene Thermomanagement-Systeme angepasst werden koennen und bei geringem Applikationsaufwand eine hohe Regelguete gewaehrleisten. Der Applikationsaufwand wird minimiert, indem ein Grossteil der Applikationsdaten modellbasiert generiert wird. (orig.)

  6. Modeling and analysis of a robust thermal control system based on forced convection thermal switches

    Science.gov (United States)

    Williams, Andrew D.; Palo, Scott E.

    2006-05-01

    There is a critical need, not just in the Department of Defense (DOD) but the entire space industry, to reduce the development time and overall cost of satellite missions. To that end, the DOD is actively pursuing the capability to reduce the deployment time of a new system from years to weeks or even days. The goal is to provide the advantages space affords not just to the strategic planner but also to the battlefield commanders. One of the most challenging aspects of this problem is the satellite's thermal control system (TCS). Traditionally the TCS must be vigorously designed, analyzed, tested, and optimized from the ground up for every satellite mission. This "reinvention of the wheel" is costly and time intensive. The next generation satellite TCS must be modular and scalable in order to cover a wide range of applications, orbits, and mission requirements. To meet these requirements a robust thermal control system utilizing forced convection thermal switches was investigated. The problem was investigated in two separate stages. The first focused on the overall design of the bus. The second stage focused on the overarching bus architecture and the design impacts of employing a thermal switch based TCS design. For the hot case, the fan provided additional cooling to increase the heat transfer rate of the subsystem. During the cold case, the result was a significant reduction in survival heater power.

  7. Disturbance observer-based L1 robust tracking control for hypersonic vehicles with T-S disturbance modeling

    Directory of Open Access Journals (Sweden)

    Yang Yi

    2016-11-01

    Full Text Available This article concerns a disturbance observer-based L1 robust anti-disturbance tracking algorithm for the longitudinal models of hypersonic flight vehicles with different kinds of unknown disturbances. On one hand, by applying T-S fuzzy models to represent those modeled disturbances, a disturbance observer relying on T-S disturbance models can be constructed to track the dynamics of exogenous disturbances. On the other hand, L1 index is introduced to analyze the attenuation performance of disturbance for those unmodeled disturbances. By utilizing the existing convex optimization algorithm, a disturbance observer-based proportional-integral-controlled input is proposed such that the stability of hypersonic flight vehicles can be ensured and the tracking error for velocity and altitude in hypersonic flight vehicle models can converge to equilibrium point. Furthermore, the satisfactory disturbance rejection and attenuation with L1 index can be obtained simultaneously. Simulation results on hypersonic flight vehicle models can reflect the feasibility and effectiveness of the proposed control algorithm.

  8. Model-based control of a ballast-stabilized floating wind turbine exposed to wind and waves

    Energy Technology Data Exchange (ETDEWEB)

    Christiansen, Soeren

    2013-01-15

    The wind turbine is a commercial product which is competing against other sources of energy, such as coal and gas. This competition drives a constant development to reduce costs and improve efficiency in order to reduce the total cost of the energy. The latest offshore development is the floating wind turbine, for water depths beyond 50 meters where winds are stronger and less turbulent. A floating wind turbine is subject to not only aerodynamics and wind induced loads, but also to hydrodynamics and wave induced loads. In contrast to a bottom fixed wind turbine, the floating structure, the hydrodynamics and the loads change the dynamic behavior of a floating wind turbine. Consequently, conventional wind turbine control cause instabilities on floating wind turbines. This work addresses the control of a floating spar buoy wind turbine, and focuses on the impact of the additional platform dynamics. A time varying control model is presented based on the wind speed and wave frequency. Estimates of the wind speed and wave frequency are used as scheduling variables in a gain scheduled linear quadratic controller to improve the electrical power production while reducing fatigue. To address the problem of negative damped fore-aft tower motion, additional control loops are suggested which stabilize the response of the onshore controller and reduce the impact of the wave induced loads. This research is then extended to model predictive control, to further address wave disturbances. In the context of control engineering, the dynamics and disturbances of a floating wind turbine have been identified and modeled. The objectives of maximizing the production of electrical power and minimizing fatigue have been reached by using advanced methods of estimation and control. (Author)

  9. Models and synchronization of time-delayed complex dynamical networks with multi-links based on adaptive control

    International Nuclear Information System (INIS)

    Peng Haipeng; Wei Nan; Li Lixiang; Xie Weisheng; Yang Yixian

    2010-01-01

    In this Letter, time-delay has been introduced in to split the networks, upon which a model of complex dynamical networks with multi-links has been constructed. Moreover, based on Lyapunov stability theory and some hypotheses, we achieve synchronization between two complex networks with different structures by designing effective controllers. The validity of the results was proved through numerical simulations of this Letter.

  10. Adaptive adjustment of interval predictive control based on combined model and application in shell brand petroleum distillation tower

    Science.gov (United States)

    Sun, Chao; Zhang, Chunran; Gu, Xinfeng; Liu, Bin

    2017-10-01

    Constraints of the optimization objective are often unable to be met when predictive control is applied to industrial production process. Then, online predictive controller will not find a feasible solution or a global optimal solution. To solve this problem, based on Back Propagation-Auto Regressive with exogenous inputs (BP-ARX) combined control model, nonlinear programming method is used to discuss the feasibility of constrained predictive control, feasibility decision theorem of the optimization objective is proposed, and the solution method of soft constraint slack variables is given when the optimization objective is not feasible. Based on this, for the interval control requirements of the controlled variables, the slack variables that have been solved are introduced, the adaptive weighted interval predictive control algorithm is proposed, achieving adaptive regulation of the optimization objective and automatically adjust of the infeasible interval range, expanding the scope of the feasible region, and ensuring the feasibility of the interval optimization objective. Finally, feasibility and effectiveness of the algorithm is validated through the simulation comparative experiments.

  11. Study on inventory control model based on the B2C mode in big data environment

    Directory of Open Access Journals (Sweden)

    Zhiping Zhang

    2017-03-01

    Full Text Available The current inventory problem has become the key issue in the enterprise survival and development. In this paper, we take “Taobao” as an example to conduct a detailed study of the inventory of the high conversion rate based on data mining. First, by using a funnel model to predict the conversion of the commodities on the critical path, we capture the factors influencing the consumer decision-making on each key point, and propose corresponding solutions of improving the conversion rate; Second, we use BP neural network algorithm to predict the goods traffic, and then obtain the corresponding weights by the relation analysis and the output of the goods traffic by the input of large data sample goods; Third, we can predict the inventory in accordance with the commodity conversion rate and flow prediction, and amend the predicted results to get accurate and real-time inventory forecast, avoiding the economic loss due to the inaccurate inventory.

  12. Model-Based Control of a Ballast-Stabilized Floating Wind Turbine Exposed to Wind and Waves

    DEFF Research Database (Denmark)

    Christiansen, Søren

    2013-01-01

    wind turbine, for water depths beyond 50 meters where winds are stronger and less turbulent. A floating wind turbine is subject to not only aerodynamics and wind induced loads, but also to hy-drodynamics and wave induced loads. In contrast to a bottom fixed wind turbine, the floating structure......, the hydrodynamics and the loads change the dynamic behavior of a floating wind turbine. Consequently, conventional wind turbine control cause instabilities on floating wind turbines. This work addresses the control of a floating spar buoy wind turbine, and focuses on the impact of the additional platform dynamics....... A time varying control model is presented based on the wind speed and wave frequency. Estimates of the wind speed and wave frequency are used as scheduling variables in a gain scheduled linear quadratic controller to improve the electrical power production while reducing fatigue. To address the problem...

  13. Perti Net-Based Workflow Access Control Model%基于Perti网的工作流访问控制模型研究

    Institute of Scientific and Technical Information of China (English)

    陈卓; 骆婷; 石磊; 洪帆

    2004-01-01

    Access control is an important protection mechanism for information systems.This paper shows how to make access control in workflow system.We give a workflow access control model (WACM) based on several current access control models.The model supports roles assignment and dynamic authorization.The paper defines the workflow using Petri net.It firstly gives the definition and description of the workflow, and then analyzes the architecture of the workflow access control model (WACM).Finally, an example of an e-commerce workflow access control model is discussed in detail.

  14. Testing a hydraulic trait based model of stomatal control: results from a controlled drought experiment on aspen (Populus tremuloides, Michx.) and ponderosa pine (Pinus ponderosa, Douglas)

    Science.gov (United States)

    Love, D. M.; Venturas, M.; Sperry, J.; Wang, Y.; Anderegg, W.

    2017-12-01

    Modeling approaches for tree stomatal control often rely on empirical fitting to provide accurate estimates of whole tree transpiration (E) and assimilation (A), which are limited in their predictive power by the data envelope used to calibrate model parameters. Optimization based models hold promise as a means to predict stomatal behavior under novel climate conditions. We designed an experiment to test a hydraulic trait based optimization model, which predicts stomatal conductance from a gain/risk approach. Optimal stomatal conductance is expected to maximize the potential carbon gain by photosynthesis, and minimize the risk to hydraulic transport imposed by cavitation. The modeled risk to the hydraulic network is assessed from cavitation vulnerability curves, a commonly measured physiological trait in woody plant species. Over a growing season garden grown plots of aspen (Populus tremuloides, Michx.) and ponderosa pine (Pinus ponderosa, Douglas) were subjected to three distinct drought treatments (moderate, severe, severe with rehydration) relative to a control plot to test model predictions. Model outputs of predicted E, A, and xylem pressure can be directly compared to both continuous data (whole tree sapflux, soil moisture) and point measurements (leaf level E, A, xylem pressure). The model also predicts levels of whole tree hydraulic impairment expected to increase mortality risk. This threshold is used to estimate survivorship in the drought treatment plots. The model can be run at two scales, either entirely from climate (meteorological inputs, irrigation) or using the physiological measurements as a starting point. These data will be used to study model performance and utility, and aid in developing the model for larger scale applications.

  15. Investigating textural controls on Archie's porosity exponent using process-based, pore-scale modelling

    Science.gov (United States)

    Niu, Q.; Zhang, C.

    2017-12-01

    Archie's law is an important empirical relationship linking the electrical resistivity of geological materials to their porosity. It has been found experimentally that the porosity exponent m in Archie's law in sedimentary rocks might be related to the degree of cementation, and therefore m is termed as "cementation factor" in most literatures. Despite it has been known for many years, there is lack of well-accepted physical interpretations of the porosity exponent. Some theoretical and experimental evidences have also shown that m may be controlled by the particle and/or pore shape. In this study, we conduct a pore-scale modeling of the porosity exponent that incorporates different geological processes. The evolution of m of eight synthetic samples with different particle sizes and shapes are calculated during two geological processes, i.e., compaction and cementation. The numerical results show that in dilute conditions, m is controlled by the particle shape. As the samples deviate from dilute conditions, m increases gradually due to the strong interaction between particles. When the samples are at static equilibrium, m is noticeably larger than its values at dilution condition. The numerical simulation results also show that both geological compaction and cementation induce a significant increase in m. In addition, the geometric characteristics of these samples (e.g., pore space/throat size, and their distributions) during compaction and cementation are also calculated. Preliminary analysis shows a unique correlation between the pore size broadness and porosity exponent for all eight samples. However, such a correlation is not found between m and other geometric characteristics.

  16. Climatic factors controlling the productivity of pine stands. A model-based analysis

    International Nuclear Information System (INIS)

    McMurtrie, R.E.; Gholz, H.L.; Linder, S.; Gower, S.T.

    1994-01-01

    A process-based forest growth model, BIOMASS, is applied to stands of four pine species (Pinus elliottii, P. radiata, P. resinosa, and P. sylvestris) growing in five sub-tropical, temperate and boreal environments (in Australia, New Zealand, Florida, Sweden and Wisconsin). Measured annual above-ground net primary production (ANPP) at these sites ranges from 0.2 to 1.6 kg C m -2 . After establishing that simulated ANPP closely matches biomass production measured for the various stands, we analyse model runs to relate simulated productivity to absorbed photosynthetically-active radiation (APAR). Annual photosynthetic productivity (or gross primary production, GPP) simulated for the five stands is linearly related to utilizable APAR, derived by estimating the extent to which photosynthesis is limited by soil water deficit, high air saturation vapor deficit or low temperature. The reduction of GPP due to incomplete radiation interception is 10 to 25% for stands with high leaf area index (LAI) in Australia, New Zealand and Wisconsin and 50 to 60% for low LAI stands in Florida and Sweden. Gross carbon gain is reduced by a further 50 to 70% at sites experiencing cold winters (Sweden and Wisconsin), summer drought (Australia) or high summer humidity deficits (Australia and Wisconsin). Simulated carbon losses due to above-ground respiration average 50% of GPP, but are highly variable among the sites due to large differences in live biomass and tissue nitrogen concentrations. This results in a weaker relationship between simulated NPP and APAR. (au) 93 refs

  17. Model-based development of low-level control strategies for transient operation of solid oxide fuel cell systems

    Science.gov (United States)

    Sorrentino, Marco; Pianese, Cesare

    The exploitation of an SOFC-system model to define and test control and energy management strategies is presented. Such a work is motivated by the increasing interest paid to SOFC technology by industries and governments due to its highly appealing potentialities in terms of energy savings, fuel flexibility, cogeneration, low-pollution and low-noise operation. The core part of the model is the SOFC stack, surrounded by a number of auxiliary devices, i.e. air compressor, regulating pressure valves, heat exchangers, pre-reformer and post-burner. Due to the slow thermal dynamics of SOFCs, a set of three lumped-capacity models describes the dynamic response of fuel cell and heat exchangers to any operation change. The dynamic model was used to develop low-level control strategies aimed at guaranteeing targeted performance while keeping stack temperature derivative within safe limits to reduce stack degradation due to thermal stresses. Control strategies for both cold-start and warmed-up operations were implemented by combining feedforward and feedback approaches. Particularly, the main cold-start control action relies on the precise regulation of methane flow towards anode and post-burner via by-pass valves; this strategy is combined with a cathode air-flow adjustment to have a tight control of both stack temperature gradient and warm-up time. Results are presented to show the potentialities of the proposed model-based approach to: (i) serve as a support to control strategies development and (ii) solve the trade-off between fast SOFC cold-start and avoidance of thermal-stress caused damages.

  18. Performance measurement, modeling, and evaluation of integrated concurrency control and recovery algorithms in distributed data base systems

    Energy Technology Data Exchange (ETDEWEB)

    Jenq, B.C.

    1986-01-01

    The performance evaluation of integrated concurrency-control and recovery mechanisms for distributed data base systems is studied using a distributed testbed system. In addition, a queueing network model was developed to analyze the two phase locking scheme in the distributed testbed system. The combination of testbed measurement and analytical modeling provides an effective tool for understanding the performance of integrated concurrency control and recovery algorithms in distributed database systems. The design and implementation of the distributed testbed system, CARAT, are presented. The concurrency control and recovery algorithms implemented in CARAT include: a two phase locking scheme with distributed deadlock detection, a distributed version of optimistic approach, before-image and after-image journaling mechanisms for transaction recovery, and a two-phase commit protocol. Many performance measurements were conducted using a variety of workloads. A queueing network model is developed to analyze the performance of the CARAT system using the two-phase locking scheme with before-image journaling. The combination of testbed measurements and analytical modeling provides significant improvements in understanding the performance impacts of the concurrency control and recovery algorithms in distributed database systems.

  19. Non-Model-Based Control of a Wheeled Vehicle Pulling Two Trailers to Provide Early Powered Mobility and Driving Experiences.

    Science.gov (United States)

    Sanders Td Vr, David A

    2018-01-01

    Non-model-based control of a wheeled vehicle pulling two trailers is proposed. It is a fun train for disabled children consisting of a locomotive and two carriages. The fun train has afforded opportunities for both disabled and able bodied young people to share an activity and has provided early driving experiences for disabled children; it has introduced them to assistive and powered mobility. The train is a nonlinear system and subject to nonholonomic kinematic constraints, so that position and state depend on the path taken to get there. The train is described, and then, a robust control algorithm using proportional-derivative filtered errors is proposed to control the locomotive. The controller was not dependent on an accurate model of the train, because the mass of the vehicle and two carriages changed depending on the number, size, and shape of children and wheelchair seats on the train. The controller was robust and stable in uncertainty. Results are presented to show the effectiveness of the approach, and the suggested control algorithm is shown to be acceptable without knowing the exact plant dynamics.

  20. Model based multivariable controller for large scale compression stations. Design and experimental validation on the LHC 18KW cryorefrigerator

    Energy Technology Data Exchange (ETDEWEB)

    Bonne, François; Bonnay, Patrick [INAC, SBT, UMR-E 9004 CEA/UJF-Grenoble, 17 rue des Martyrs, 38054 Grenoble (France); Alamir, Mazen [Gipsa-Lab, Control Systems Department, CNRS-University of Grenoble, 11, rue des Mathématiques, BP 46, 38402 Saint Martin d' Hères (France); Bradu, Benjamin [CERN, CH-1211 Genève 23 (Switzerland)

    2014-01-29

    In this paper, a multivariable model-based non-linear controller for Warm Compression Stations (WCS) is proposed. The strategy is to replace all the PID loops controlling the WCS with an optimally designed model-based multivariable loop. This new strategy leads to high stability and fast disturbance rejection such as those induced by a turbine or a compressor stop, a key-aspect in the case of large scale cryogenic refrigeration. The proposed control scheme can be used to have precise control of every pressure in normal operation or to stabilize and control the cryoplant under high variation of thermal loads (such as a pulsed heat load expected to take place in future fusion reactors such as those expected in the cryogenic cooling systems of the International Thermonuclear Experimental Reactor ITER or the Japan Torus-60 Super Advanced fusion experiment JT-60SA). The paper details how to set the WCS model up to synthesize the Linear Quadratic Optimal feedback gain and how to use it. After preliminary tuning at CEA-Grenoble on the 400W@1.8K helium test facility, the controller has been implemented on a Schneider PLC and fully tested first on the CERN's real-time simulator. Then, it was experimentally validated on a real CERN cryoplant. The efficiency of the solution is experimentally assessed using a reasonable operating scenario of start and stop of compressors and cryogenic turbines. This work is partially supported through the European Fusion Development Agreement (EFDA) Goal Oriented Training Program, task agreement WP10-GOT-GIRO.