Model based development of engine control algorithms
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 b
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
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...
Model-based control of networked systems
Garcia, Eloy; Montestruque, Luis A
2014-01-01
This monograph introduces a class of networked control systems (NCS) called model-based networked control systems (MB-NCS) and presents various architectures and control strategies designed to improve the performance of NCS. The overall performance of NCS considers the appropriate use of network resources, particularly network bandwidth, in conjunction with the desired response of the system being controlled. The book begins with a detailed description of the basic MB-NCS architecture that provides stability conditions in terms of state feedback updates . It also covers typical problems in NCS such as network delays, network scheduling, and data quantization, as well as more general control problems such as output feedback control, nonlinear systems stabilization, and tracking control. Key features and topics include: Time-triggered and event-triggered feedback updates Stabilization of uncertain systems subject to time delays, quantization, and extended absence of feedback Optimal control analysis and ...
Atom-Role-Based Access Control Model
Cai, Weihong; Huang, Richeng; Hou, Xiaoli; Wei, Gang; Xiao, Shui; Chen, Yindong
Role-based access control (RBAC) model has been widely recognized as an efficient access control model and becomes a hot research topic of information security at present. However, in the large-scale enterprise application environments, the traditional RBAC model based on the role hierarchy has the following deficiencies: Firstly, it is unable to reflect the role relationships in complicated cases effectively, which does not accord with practical applications. Secondly, the senior role unconditionally inherits all permissions of the junior role, thus if a user is under the supervisor role, he may accumulate all permissions, and this easily causes the abuse of permission and violates the least privilege principle, which is one of the main security principles. To deal with these problems, we, after analyzing permission types and role relationships, proposed the concept of atom role and built an atom-role-based access control model, called ATRBAC, by dividing the permission set of each regular role based on inheritance path relationships. Through the application-specific analysis, this model can well meet the access control requirements.
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
ROBUST INTERNAL MODEL CONTROL STRATEGY BASED PID CONTROLLER FOR BLDCM
Directory of Open Access Journals (Sweden)
A.PURNA CHANDRA RAO
2010-11-01
Full Text Available All the closed loop control system requires the controller for improvement of transient response of the error signal. Though the tuning of PID controller in real time is bit difficult and moreover it lacks the disturbance rejection capability. This paper presents a tuning of PID parameters based on internal model strategy. The advantageous of the proposed control strategy is well described in the paper. To test the validity of the proposed control, it is implemented in brushless dc motor drive. The mathematical model of brushless dc motor (BLDC is presented for control design. In addition the robustness of the control strategy is discussed. The proposed control strategy possesses good transient responses and good load disturbance response. In addition, the proposed control strategy possesses good tracking ability. To test the effectiveness of the proposed strategy, the BLDC is represented in transfer function model and later implemented in test system. The results are presented to validate the proposed control strategy for BLDC drive.
Model Based Control of Refrigeration Systems
DEFF Research Database (Denmark)
Larsen, Lars Finn Sloth
of the supermarket refrigeration systems therefore greatly relies on a human operator to detect and accommodate failures, and to optimize system performance under varying operational condition. Today these functions are maintained by monitoring centres located all over the world. Initiated by the growing need...... 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.......e. by degrading the performance. The method has been successfully applied on a test frigeration system for minimization of the power consumption; the hereby gained experimental results will be presented. The present control structure in a supermarket refrigeration system is distributed, which means...
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...
Model Based Adaptive Piecewise Linear Controller for Complicated Control Systems
Directory of Open Access Journals (Sweden)
Tain-Sou Tsay
2014-01-01
Full Text Available A model based adaptive piecewise linear control scheme for industry processes with specifications on peak overshoots and rise times is proposed. It is a gain stabilized control technique. Large gain is used for large tracking error to get fast response. Small gain is used between large and small tracking error for good performance. Large gain is used again for small tracking error to cope with large disturbance. Parameters of the three-segment piecewise linear controller are found by an automatic regulating time series which is function of output characteristics of the plant and reference model. The time series will be converged to steady values after the time response of the considered system matching that of the reference model. The proposed control scheme is applied to four numerical examples which have been compensated by PID controllers. Parameters of PID controllers are found by optimization method. It gives an almost command independent response and gives significant improvements for response time and performance.
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...
Internal Model Based Active Disturbance Rejection Control
Pan, Jinwen; Wang, Yong
2016-01-01
The basic active disturbance rejection control (BADRC) algorithm with only one order higher extended state observer (ESO) proves to be robust to both internal and external disturbances. An advantage of BADRC is that in many applications it can achieve high disturbance attenuation level without requiring a detailed model of the plant or disturbance. However, this can be regarded as a disadvantage when the disturbance characteristic is known since the BADRC algorithm cannot exploit such informa...
Model based control of dynamic atomic force microscope
Energy Technology Data Exchange (ETDEWEB)
Lee, Chibum [Department of Mechanical System Design Engineering, Seoul National University of Science and Technology, Seoul 139-743 (Korea, Republic of); Salapaka, Srinivasa M., E-mail: salapaka@illinois.edu [Department of Mechanical Science and Engineering, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801 (United States)
2015-04-15
A model-based robust control approach is proposed that significantly improves imaging bandwidth for the dynamic mode atomic force microscopy. A model for cantilever oscillation amplitude and phase dynamics is derived and used for the control design. In particular, the control design is based on a linearized model and robust H{sub ∞} control theory. This design yields a significant improvement when compared to the conventional proportional-integral designs and verified by experiments.
Model based control of dynamic atomic force microscope.
Lee, Chibum; Salapaka, Srinivasa M
2015-04-01
A model-based robust control approach is proposed that significantly improves imaging bandwidth for the dynamic mode atomic force microscopy. A model for cantilever oscillation amplitude and phase dynamics is derived and used for the control design. In particular, the control design is based on a linearized model and robust H(∞) control theory. This design yields a significant improvement when compared to the conventional proportional-integral designs and verified by experiments.
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...
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.
Mechanics and model-based control of advanced engineering systems
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.
Switching Control System Based on Robust Model Reference Adaptive Control
Institute of Scientific and Technical Information of China (English)
HU Qiong; FEI Qing; MA Hongbin; WU Qinghe; GENG Qingbo
2016-01-01
For conventional adaptive control,time-varying parametric uncertainty and unmodeled dynamics are ticklish problems,which will lead to undesirable performance or even instability and nonrobust behavior,respectively.In this study,a class of discrete-time switched systems with unmodeled dynamics is taken into consideration.Moreover,nonlinear systems are here supposed to be approximated with the class of switched systems considered in this paper,and thereby switching control design is investigated for both switched systems and nonlinear systems to assure stability and performance.For robustness against unmodeled dynamics and uncertainty,robust model reference aclaptive control (RMRAC) law is developed as the basis of controller design for each individual subsystem in the switched systems or nonlinear systems.Meanwhile,two different switching laws are presented for switched systems and nonlinear systems,respectively.Thereby,the authors incorporate the corresponding switching law into the RMRAC law to construct two schemes of switching control respectively for the two kinds of controlled systems.Both closed-loop analyses and simulation examples are provided to illustrate the validity of the two proposed switching control schemes.Furthermore,as to the proposed scheme for nonlinear systems,its potential for practical application is demonstrated through simulations of longitudinal control for F-16 aircraft.
Model based control charts in stage 1 quality control
A.J. Koning (Alex)
1999-01-01
textabstractIn this paper a general method of constructing control charts for preliminary analysis of individual observations is presented, which is based on recursive score residuals. A simulation study shows that certain implementations of these charts are highly effective in detecting assignable
Model-based analysis of control performance in sewer systems
DEFF Research Database (Denmark)
Mollerup, Ane Høyer; Mauricio Iglesias, Miguel; Johansen, N.B.;
2012-01-01
Design and assessment of control in wastewater systems has to be tackled at all levels, including supervisory and regulatory level. We present here an integrated approach to assessment of control in sewer systems based on modelling and the use of process control tools to assess the controllability...... of the process. A case study of a subcatchment area in Copenhagen (Denmark) is used to illustrate the combined approach in modelling of the system and control assessment....
Model-Based Traffic Control for Sustainable Mobility
Zegeye, S.K.
2011-01-01
Computationally efficient dynamic fuel consumption, emissions, and dispersion of emissions models are developed. Fast and practically feasible model-based controller is proposed. Using the developed models, the controller steers the traffic flow in such a way that a balanced trade-off between the t
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.
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.
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...
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...
Stabilization of model-based networked control systems
Miranda, Francisco; Abreu, Carlos; Mendes, Paulo M.
2016-06-01
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.
Model-based control of hopper dredgers
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
Cascaded process model based control: packed absorption column application.
Govindarajan, Anand; Jayaraman, Suresh Kumar; Sethuraman, Vijayalakshmi; Raul, Pramod R; Rhinehart, R Russell
2014-03-01
Nonlinear, adaptive, process-model based control is demonstrated in a cascaded single-input-single-output mode for pressure drop control in a pilot-scale packed absorption column. The process is shown to be nonlinear. Control is demonstrated in both servo and regulatory modes, for no wind-up in a constrained situation, and for bumpless transfer. Model adaptation is demonstrated and shown to provide process insight. The application procedure is revealed as a design guide to aid others in implementing process-model based control.
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
Intelligent control based on intelligent characteristic model and its application
Institute of Scientific and Technical Information of China (English)
吴宏鑫; 王迎春; 邢琰
2003-01-01
This paper presents a new intelligent control method based on intelligent characteristic model for a kind of complicated plant with nonlinearities and uncertainties, whose controlled output variables cannot be measured on line continuously. The basic idea of this method is to utilize intelligent techniques to form the characteristic model of the controlled plant according to the principle of combining the char-acteristics of the plant with the control requirements, and then to present a new design method of intelli-gent controller based on this characteristic model. First, the modeling principles and expression of the intelligent characteristic model are presented. Then based on description of the intelligent characteristic model, the design principles and methods of the intelligent controller composed of several open-loops and closed-loops sub controllers with qualitative and quantitative information are given. Finally, the ap-plication of this method in alumina concentration control in the real aluminum electrolytic process is in-troduced. It is proved in practice that the above methods not only are easy to implement in engineering design but also avoid the trial-and-error of general intelligent controllers. It has taken better effect in the following application: achieving long-term stable control of low alumina concentration and increasing the controlled ratio of anode effect greatly from 60% to 80%.
Task Delegation Based Access Control Models for Workflow Systems
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.
Support vector machine-based multi-model predictive control
Institute of Scientific and Technical Information of China (English)
Zhejing BA; Youxian SUN
2008-01-01
In this paper,a support vector machine-based multi-model predictive control is proposed,in which SVM classification combines well with SVM regression.At first,each working environment is modeled by SVM regression and the support vector machine network-based model predictive control(SVMN-MPC)algorithm corresponding to each environment is developed,and then a multi-class SVM model is established to recognize multiple operating conditions.As for control,the current environment is identified by the multi-class SVM model and then the corresponding SVMN.MPCcontroller is activated at each sampling instant.The proposed modeling,switching and controller design is demonstrated in simulation results.
PI controller based model reference adaptive control for nonlinear ...
African Journals Online (AJOL)
user
which can deal effectively for real-time online computer control. The NN of the ..... applications such as machine tools, industrial robot control, position control, and other engineering practices. .... Transactions on Mechatronics, vol.1, no.2, pp.
Iterative learning control of SOFC based on ARX identification model
Institute of Scientific and Technical Information of China (English)
无
2007-01-01
This paper presents an application of iterative learning control (ILC) technique to the voltage control of solid oxide fuel cell (SOFC) stack. To meet the demands of the control system design, an autoregressive model with exogenous input (ARX) is established. Firstly, by regulating the variation of the hydrogen flow rate proportional to that of the current, the fuel utilization of the SOFC is kept within its admissible range. Then, based on the ARX model, three kinds of ILC controllers, i.e. P-, PI- and PD-type are designed to keep the voltage at a desired level. Simulation results demonstrate the potential of the ARX model applied to the control of the SOFC, and prove the excellence of the ILC controllers for the voltage control of the SOFC.
Fuzzy control of power converters based on quasilinear modelling
Li, C. K.; Lee, W. L.; Chou, Y. W.
1995-03-01
Unlike feedback control by the fuzzy PID method, a new fuzzy control algorithm based on quasilinear modelling of the DC-DC converter is proposed. Investigation is carried out using a buck-boost converter. Simulation results demonstrated that the converter can be regulated with improved performance even when subjected to input disturbance and load variation.
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
Quality guaranteed aggregation based model predictive control and stability analysis
Institute of Scientific and Technical Information of China (English)
LI DeWei; XI YuGeng
2009-01-01
The input aggregation strategy can reduce the online computational burden of the model predictive controller. But generally aggregation based MPC controller may lead to poor control quality. Therefore, a new concept, equivalent aggregation, is proposed to guarantee the control quality of aggregation based MPC. From the general framework of input linear aggregation, the design methods of equivalent aggregation are developed for unconstrained and terminal zero constrained MPC, which guarantee the actual control inputs exactly to be equal to that of the original MPC. For constrained MPC, quasi-equivalent aggregation strategies are also discussed, aiming to make the difference between the control inputs of aggregation based MPC and original MPC as small as possible. The stability conditions are given for the quasi-equivalent aggregation based MPC as well.
A Model of Workflow-oriented Attributed Based Access Control
Directory of Open Access Journals (Sweden)
Guoping Zhang
2011-02-01
Full Text Available the emergence of “Internet of Things” breaks previous traditional thinking, which integrates physical infrastructure and network infrastructure into unified infrastructure. There will be a lot of resources or information in IoT, so computing and processing of information is the core supporting of IoT. In this paper, we introduce “Service-Oriented Computing” to solve the problem where each device can offer its functionality as standard services. Here we mainly discuss the access control issue of service-oriented computing in Internet of Things. This paper puts forward a model of Workflow-oriented Attributed Based Access Control (WABAC, and design an access control framework based on WABAC model. The model grants permissions to subjects according to subject atttribute, resource attribute, environment attribute and current task, meeting access control request of SOC. Using the approach presented can effectively enhance the access control security for SOC applications, and prevent the abuse of subject permissions.
A comprehensive gaze stabilization controller based on cerebellar internal models
DEFF Research Database (Denmark)
Vannucci, Lorenzo; Falotico, Egidio; Tolu, Silvia
2017-01-01
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...... and on the iCub simulator, validating the robustness of the proposed control method. The first set of experiments focused on the controller response to a set of disturbance frequencies along the vertical plane. The second shows the performances of the system under three-dimensional disturbances. The last set...
Optimal Model-Based Control in HVAC Systems
DEFF Research Database (Denmark)
Komareji, Mohammad; Stoustrup, Jakob; Rasmussen, Henrik;
2008-01-01
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...
Support Vector Machine-Based Nonlinear System Modeling and Control
Institute of Scientific and Technical Information of China (English)
张浩然; 韩正之; 冯瑞; 于志强
2003-01-01
This paper provides an introduction to a support vector machine, a new kernel-based technique introduced in statistical learning theory and structural risk minimization, then presents a modeling-control framework based on SVM.At last a numerical experiment is taken to demonstrate the proposed approach's correctness and effectiveness.
Provably Safe and Robust Learning-Based Model Predictive Control
Aswani, Anil; Sastry, S Shankar; Tomlin, Claire
2011-01-01
Controller design for systems typically faces a trade-off between robustness and performance, and the reliability of linear controllers has caused many control practitioners to focus on the former. However, there is a renewed interest in improving system performance to deal with growing energy and pollution constraints. This paper describes a learning-based model predictive control (MPC) scheme. The MPC provides deterministic guarantees on robustness and safety, and the learning is used to identify richer models of the system to improve controller performance. Our scheme uses a linear model with bounds on its uncertainty to construct invariant sets which help to provide the guarantees, and it can be generalized to other classes of models and to pseudo-spectral methods. This framework allows us to handle state and input constraints and optimize system performance with respect to a cost function. The learning occurs through the use of an oracle which returns the value and gradient of unmodeled dynamics at discr...
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...
Tensor product model transformation based decoupled terminal sliding mode control
Zhao, Guoliang; Li, Hongxing; Song, Zhankui
2016-06-01
The main objective of this paper is to propose a tensor product model transformation based decoupled terminal sliding mode controller design methodology. The methodology is divided into two steps. In the first step, tensor product model transformation is applied to the single-input-multi-output system and a parameter-varying weighted linear time-invariant system is obtained. Then, decoupled terminal sliding mode controller is designed based on the linear time-invariant systems. The main novelty of this paper is that the nonsingular terminal sliding mode control design is based on a numerical model rather than an analytical one. Finally, simulations are tested on cart-pole system and translational oscillations with a rotational actuator system.
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....... As a case study, we present control system that minimizes operational cost of swimming pool heating system, where parameters of the model depend on the weather forecast. Simulation results demonstrate that the proposed method is able to deal with this kind of systems....
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.
Application of model based control to robotic manipulators
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.
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...
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. Th......). In the thesis the pressure control is based on this new method when on/off burner switching is required while the water level control is handled by a model predictive controller........ 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...
Predictive functional control based on fuzzy T-S model for HVAC systems temperature control
Institute of Scientific and Technical Information of China (English)
Hongli L(U); Lei JIA; Shulan KONG; Zhaosheng ZHANG
2007-01-01
In heating,ventilating and air-conditioning(HVAC)systems,there exist severe nonlinearity,time-varying nature,disturbances and uncertainties.A new predictive functional control based on Takagi-Sugeno(T-S)fuzzy model was proposed to control HVAC systems.The T-S fuzzy model of stabilized controlled process was obtained using the least squares method,then on the basis of global linear predictive model from T-S fuzzy model,the process was controlled by the predictive functional controller.Especially the feedback regulation part was developed to compensate uncertainties of fuzzy predictive model.Finally simulation test results in HVAC systems control applications showed that the proposed fuzzy model predictive functional control improves tracking effect and robustness.Compared with the conventional PID controller,this control strategy has the advantages of less overshoot and shorter setting time,etc.
Embedded Control System Design A Model Based Approach
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...
Model Based Control of Single-Phase Marine Cooling Systems
DEFF Research Database (Denmark)
Hansen, Michael
2014-01-01
”, it is shown that the part of the proposed model relating to the thermodynamics is dynamically accurate and with relatively small steady state deviations. The same is shown for a linear version of the part of the model governing the hydraulics of the cooling system. On the subject of control, the main focus...... 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...
Privacy Preservation in Role-based Access Control Model
Directory of Open Access Journals (Sweden)
Zuo Chen
2011-08-01
Full Text Available Privacy preservation is a crucial problem in resource sharing and collaborating among multi-domains. Based on this problem, we propose a role-based access control model for privacy preservation. This scheme avoided the privacy leakage of resources while implementing access control, and it has the advantage of lower communication overhead. We demonstrate this scheme meets the IND-CCA2 semantic security by using random oracle. The simulation result shows this scheme has better execution efficiency and application effects.
TP-model transformation-based-control design frameworks
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...
Aeroservoelastic model based active control for large civil aircraft
Institute of Scientific and Technical Information of China (English)
无
2010-01-01
A modeling and control approach for an advanced configured large civil aircraft with aeroservoelasticity via the LQG method and control allocation is presented.Mathematical models and implementation issues for the multi-input/multi-output(MIMO) aeroservoelastic system simulation developed for a flexible wing with multi control surfaces are described.A fuzzy logic based optimization approach is employed to solve the constrained control allocation problem via intelligently adjusting the components of output vector and find a proper vector in the attainable moment set(AMS) autonomously.The basic idea is to minimize the L2 norm of error between the desired moment and achievable moment using the designing freedom provided by redundantly allocated actuators and control surfaces.Considering the constraints of control surfaces,in order to obtain acceptable performance of aircraft such as stability and maneuverability,the fuzzy weights are updated by the learning algorithm,which makes the closed-loop system self-adaptation.Finally,an application example of flight control designing for the advanced civil aircraft is discussed as a demonstration.The studies we have performed showed that the advanced configured large civil aircraft has good performance with the proper designed control law designed via the proposed approach.The gust alleviation and flutter suppression are applied with the synergetic effects of elevator,ailerons,equivalent rudders and flaps.The results show good closed loop performance and meet the requirement of constraint of control surfaces.
A nonlinear regression model-based predictive control algorithm.
Dubay, R; Abu-Ayyad, M; Hernandez, J M
2009-04-01
This paper presents a unique approach for designing a nonlinear regression model-based predictive controller (NRPC) for single-input-single-output (SISO) and multi-input-multi-output (MIMO) processes that are common in industrial applications. The innovation of this strategy is that the controller structure allows nonlinear open-loop modeling to be conducted while closed-loop control is executed every sampling instant. Consequently, the system matrix is regenerated every sampling instant using a continuous function providing a more accurate prediction of the plant. Computer simulations are carried out on nonlinear plants, demonstrating that the new approach is easily implemented and provides tight control. Also, the proposed algorithm is implemented on two real time SISO applications; a DC motor, a plastic injection molding machine and a nonlinear MIMO thermal system comprising three temperature zones to be controlled with interacting effects. The experimental closed-loop responses of the proposed algorithm were compared to a multi-model dynamic matrix controller (MPC) with improved results for various set point trajectories. Good disturbance rejection was attained, resulting in improved tracking of multi-set point profiles in comparison to multi-model MPC.
Modeling and control of fuel cell based distributed generation systems
Jung, Jin Woo
This dissertation presents circuit models and control algorithms of fuel cell based distributed generation systems (DGS) for two DGS topologies. In the first topology, each DGS unit utilizes a battery in parallel to the fuel cell in a standalone AC power plant and a grid-interconnection. In the second topology, a Z-source converter, which employs both the L and C passive components and shoot-through zero vectors instead of the conventional DC/DC boost power converter in order to step up the DC-link voltage, is adopted for a standalone AC power supply. In Topology 1, two applications are studied: a standalone power generation (Single DGS Unit and Two DGS Units) and a grid-interconnection. First, dynamic model of the fuel cell is given based on electrochemical process. Second, two full-bridge DC to DC converters are adopted and their controllers are designed: an unidirectional full-bridge DC to DC boost converter for the fuel cell and a bidirectional full-bridge DC to DC buck/boost converter for the battery. Third, for a three-phase DC to AC inverter without or with a Delta/Y transformer, a discrete-time state space circuit model is given and two discrete-time feedback controllers are designed: voltage controller in the outer loop and current controller in the inner loop. And last, for load sharing of two DGS units and power flow control of two DGS units or the DGS connected to the grid, real and reactive power controllers are proposed. Particularly, for the grid-connected DGS application, a synchronization issue between an islanding mode and a paralleling mode to the grid is investigated, and two case studies are performed. To demonstrate the proposed circuit models and control strategies, simulation test-beds using Matlab/Simulink are constructed for each configuration of the fuel cell based DGS with a three-phase AC 120 V (L-N)/60 Hz/50 kVA and various simulation results are presented. In Topology 2, this dissertation presents system modeling, modified space
Model of epidemic control based on quarantine and message delivery
Wang, Xingyuan; Zhao, Tianfang; Qin, Xiaomeng
2016-09-01
The model provides two novel strategies for the preventive control of epidemic diseases. One approach is related to the different isolating rates in latent period and invasion period. Experiments show that the increasing of isolating rates in invasion period, as long as over 0.5, contributes little to the preventing of epidemic; the improvement of isolation rate in latent period is key to control the disease spreading. Another is a specific mechanism of message delivering and forwarding. Information quality and information accumulating process are also considered there. Macroscopically, diseases are easy to control as long as the immune messages reach a certain quality. Individually, the accumulating messages bring people with certain immunity to the disease. Also, the model is performed on the classic complex networks like scale-free network and small-world network, and location-based social networks. Results show that the proposed measures demonstrate superior performance and significantly reduce the negative impact of epidemic disease.
Developments in model-based optimization and control distributed control and industrial applications
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...
Model-based control of district heating supply temperature
Energy Technology Data Exchange (ETDEWEB)
Saarinen, Linn
2010-11-15
A model-based control strategy for the supply temperature to a district heating network was tested during three weeks at Idbaecken's CHP plant. The aim was to increase the electricity efficiency by a lower supply temperature, without risking the delivery reliability of heat to the district heating customers. Simulations and tests showed that at high loads, the mean supply temperature could be reduced by 4 deg C and the electricity production could be increased by 2.5%
Synthetical Control of AGC/LPC System Based on Neural Networks Internal Model Control
Institute of Scientific and Technical Information of China (English)
无
2001-01-01
One synthetical control method of AGC/LPC system based on intelligence control theory-neural networks internal model control method is presented. Genetic algorithm (GA) is applied to optimize the parameters of the neural networks. Simulation results prove that this method is effective.
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.
OJADEAC: An Ontology Based Access Control Model for JADE Platform
Directory of Open Access Journals (Sweden)
Ban Sharief Mustafa
2014-06-01
Full Text Available Java Agent Development Framework (JADE is a software framework to make easy the development of Multi-Agent applications in compliance with the Foundation for Intelligent Physical Agents (FIPA specifications. JADE propose new infrastructure solutions to support the development of useful and convenient distributed applications. Security is one of the most important issues in implementing and deploying such applications. JADE-S security add-ons are one of the most popular security solutions in JADE platform. It provides several security services including authentication, authorization, signature and encryption services. Authorization service will give authorities to perform an action based on a set of permission objects attached to every authenticated user. This service has several drawbacks when implemented in a scalable distributed context aware applications. In this paper, an ontology-based access control model called (OJADEAC is proposed to be applied in JADE platform by combining Semantic Web technologies with context-aware policy mechanism to overcome the shortcoming of this service. The access control model is represented by a semantic ontology, and a set of two level semantic rules representing platform and application specific policy rules. OJADEAC model is distributed, intelligent, dynamic, context-aware and use reasoning engine to infer access decisions based on ontology knowledge.
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.
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.
Zhao, Guoliang; Sun, Kaibiao; Li, Hongxing
2013-01-01
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.
CONTROL OF NONLINEAR PROCESS USING NEURAL NETWORK BASED MODEL PREDICTIVE CONTROL
Directory of Open Access Journals (Sweden)
Dr.A.TRIVEDI
2011-04-01
Full Text Available This paper presents a Neural Network based Model Predictive Control (NNMPC strategy to control nonlinear process. Multilayer Perceptron Neural Network (MLP is chosen to represent a Nonlinear Auto Regressive with eXogenous signal (NARX model of a nonlinear system. NARX dynamic model is based on feed-forward architecture and offers good approximation capabilities along with robustness and accuracy. Based on the identified neural model, a generalized predictive control (GPC algorithm is implemented to control the composition in acontinuous stirred tank reactor (CSTR, whose parameters are optimally determined by solving quadratic performance index using well known Levenberg-Marquardt and Quasi-Newton algorithm. NNMPC is tuned by selecting few horizon parameters and weighting factor. The tracking performance of the NNMPC is tested using different amplitude function as a reference signal on CSTR application. Also the robustness and performance is tested in the presence of disturbance on random reference signal.
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
Experience-based model predictive control using reinforcement learning
Negenborn, R.R.; De Schutter, B.; Wiering, M.A.; Hellendoorn, J.
2004-01-01
Model predictive control (MPC) is becoming an increasingly popular method to select actions for controlling dynamic systems. TraditionallyMPC uses a model of the system to be controlled and a performance function to characterize the desired behavior of the system. The MPC agent finds actions over a
Model Based Monitoring and Control of Chemical and Biochemical Processes
DEFF Research Database (Denmark)
Huusom, Jakob Kjøbsted
This presentation will give an overview of the work performed at the department of Chemical and Biochemical Engineering related to process control. A research vision is formulated and related to a number of active projects at the department. In more detail a project describing model estimation...... and controller tuning in Model Predictive Control application is discussed....
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...
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.
Adaptive model-based control systems and methods for controlling a gas turbine
Brunell, Brent Jerome (Inventor); Mathews, Jr., Harry Kirk (Inventor); Kumar, Aditya (Inventor)
2004-01-01
Adaptive model-based control systems and methods are described so that performance and/or operability of a gas turbine in an aircraft engine, power plant, marine propulsion, or industrial application can be optimized under normal, deteriorated, faulted, failed and/or damaged operation. First, a model of each relevant system or component is created, and the model is adapted to the engine. Then, if/when deterioration, a fault, a failure or some kind of damage to an engine component or system is detected, that information is input to the model-based control as changes to the model, constraints, objective function, or other control parameters. With all the information about the engine condition, and state and directives on the control goals in terms of an objective function and constraints, the control then solves an optimization so the optimal control action can be determined and taken. This model and control may be updated in real-time to account for engine-to-engine variation, deterioration, damage, faults and/or failures using optimal corrective control action command(s).
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.
Model based control for run-of-river system. Part 2: Comparison of control structures
Directory of Open Access Journals (Sweden)
Liubomyr Vytvytskyi
2015-10-01
Full Text Available Optimal operation and control of a run-of-river hydro power plant depend on good knowledge of the elements of the plant in the form of models. Both the control architecture of the system, i.e. the choice of inputs and outputs, and to what degree a model is used, will affect the achievable control performance. Here, a model of a river reach based on the Saint Venant equations for open channel flow illustrates the dynamics of the run-of-river system. The hyperbolic partial differential equations are discretized using the Kurganov-Petrova central upwind scheme - see Part I for details. A comparison is given of achievable control performance using two alternative control signals: the inlet or the outlet volumetric flow rates to the system, in combination with a number of different control structures such as PI control, PI control with Smith predictor, and predictive control. The control objective is to keep the level just in front of the dam as high as possible, and with little variation in the level to avoid overflow over the dam. With a step change in the volumetric inflow to the river reach (disturbance and using the volumetric outflow as the control signal, PI control gives quite good performance. Model predictive control (MPC gives superior control in the sense of constraining the variation in the water level, at a cost of longer computational time and thus constraints on possible sample time. Details on controller tuning are given. With volumetric inflow to the river reach as control signal and outflow (production as disturbance, this introduces a considerable time delay in the control signal. Because of nonlinearity in the system (varying time delay, etc., it is difficult to achieve stable closed loop performance using a simple PI controller. However, by combining a PI controller with a Smith predictor based on a simple integrator + fixed time delay model, stable closed loop operation is possible with decent control performance. Still, an MPC
Matsumoto, Atsushi; Hasegawa, Masaru; Matsui, Keiju
In this paper, a novel position sensorless control method for interior permanent magnet synchronous motors (IPMSMs) that is based on a novel flux model suitable for maximum torque control has been proposed. Maximum torque per ampere (MTPA) control is often utilized for driving IPMSMs with the maximum efficiency. In order to implement this control, generally, the parameters are required to be accurate. However, the inductance varies dramatically because of magnetic saturation, which has been one of the most important problems in recent years. Therefore, the conventional MTPA control method fails to achieve maximum efficiency for IPMSMs because of parameter mismatches. In this paper, first, a novel flux model has been proposed for realizing the position sensorless control of IPMSMs, which is insensitive to Lq. In addition, in this paper, it has been shown that the proposed flux model can approximately estimate the maximum torque control (MTC) frame, which as a new coordinate aligned with the current vector for MTPA control. Next, in this paper, a precise estimation method for the MTC frame has been proposed. By this method, highly accurate maximum torque control can be achieved. A decoupling control algorithm based on the proposed model has also been addressed in this paper. Finally, some experimental results demonstrate the feasibility and effectiveness of the proposed method.
Batch Process Modelling and Optimal Control Based on Neural Network Models
Institute of Scientific and Technical Information of China (English)
Jie Zhang
2005-01-01
This paper presents several neural network based modelling, reliable optimal control, and iterative learning control methods for batch processes. In order to overcome the lack of robustness of a single neural network, bootstrap aggregated neural networks are used to build reliable data based empirical models. Apart from improving the model generalisation capability, a bootstrap aggregated neural network can also provide model prediction confidence bounds. A reliable optimal control method by incorporating model prediction confidence bounds into the optimisation objective function is presented. A neural network based iterative learning control strategy is presented to overcome the problem due to unknown disturbances and model-plant mismatches. The proposed methods are demonstrated on a simulated batch polymerisation process.
Optimal control based on adaptive model reduction approach to control transfer phenomena
Oulghelou, Mourad; Allery, Cyrille
2017-01-01
The purpose of optimal control is to act on a set of parameters characterizing a dynamical system to achieve a target dynamics. In order to reduce CPU time and memory storage needed to perform control on evolution systems, it is possible to use reduced order models (ROMs). The mostly used one is the Proper Orthogonal Decomposition (POD). However the bases constructed in this way are sensitive to the configuration of the dynamical system. Consequently, the need of full simulations to build a basis for each configuration is time consuming and makes that approach still relatively expensive. In this paper, to overcome this difficulty we suggest to use an adequate bases interpolation method. It consists in computing the associated bases to a distribution of control parameters. These bases are afterwards called in the control algorithm to build a reduced basis adapted to a given control parameter. This interpolation method involves results of the calculus of Geodesics on Grassmann manifold.
Neural network-based nonlinear model predictive control vs. linear quadratic gaussian control
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.
A Model of FPGA-based Direct Torque Controller
Directory of Open Access Journals (Sweden)
Auzani Jidin
2013-02-01
Full Text Available This paper presents a generic model of a fully FPGA-based direct torque controller. This model is developed using two’s-complement fixed-point format approaches, in register-transfer-level (RTL VHDL abstraction for minimizing calculation errors and consuming hardware resource usage. Therefore, the model is universal and can be implemented for all FPGA types. The model is prepared for fast computation, without using of CORDIC algorithm, a soft-core CPU, a transformation from Cartesian-to-polar coordinates, and without the help of third-party applications. To get simpler implementation and fast computation, several methods were introduced: i the backward-Euler approach to calculate the discrete-integration operation of stator flux, ii the modified non-restoring method to calculate complicated square-root operation of stator flux, iii a new sector analysis method. The design, which was coded in synthesizable VHDL in RTL abstraction for implementation on Altera DE2-board has produced very-precise calculations, with minimal error when being compared to MATLAB/Simulink double-precision calculation.
Support vector regression-based internal model control
Institute of Scientific and Technical Information of China (English)
HUANG Yan-wei; PENG Tie-gen
2007-01-01
This paper proposes a design of internal model control systems for process with delay by using support vector regression (SVR). The proposed system fully uses the excellent nonlinear estimation performance of SVR with the structural risk minimization principle. Closed-system stability and steady error are analyzed for the existence of modeling errors. The simulations show that the proposed control systems have the better control performance than that by neural networks in the cases of the training samples with small size and noises.
Application of Attribute Based Access Control Model for Industrial Control Systems
Directory of Open Access Journals (Sweden)
Erkan Yalcinkaya
2017-02-01
Full Text Available The number of reported security vulnerabilities and incidents related to the industrial control systems (ICS has increased recent years. As argued by several researchers, authorization issues and poor access control are key incident vectors. The majority of ICS are not designed security in mind and they usually lack strong and granular access control mechanisms. The attribute based access control (ABAC model offers high authorization granularity, central administration of access policies with centrally consolidated and monitored logging properties. This research proposes to harness the ABAC model to address the present and future ICS access control challenges. The proposed solution is also implemented and rigorously tested to demonstrate the feasibility and viability of ABAC model for ICS.
Probabilistic Priority Message Checking Modeling Based on Controller Area Networks
Lin, Cheng-Min
Although the probabilistic model checking tool called PRISM has been applied in many communication systems, such as wireless local area network, Bluetooth, and ZigBee, the technique is not used in a controller area network (CAN). In this paper, we use PRISM to model the mechanism of priority messages for CAN because the mechanism has allowed CAN to become the leader in serial communication for automobile and industry control. Through modeling CAN, it is easy to analyze the characteristic of CAN for further improving the security and efficiency of automobiles. The Markov chain model helps us to model the behaviour of priority messages.
Multiple Model Adaptive Estimation Techniques for Adaptive Model-Based Robot Control
1989-12-01
Proportional Derivative (PD) or Propor- tional Integral Derivative (PID) feedback controller [6]. 1-1 The PD or PID controllers feedback the measured...Unfortunately, as the speed of the trajectory increases or the con- figuration of the robot changes, the PD or PID controllers cannot maintain track along the...desired trajectory. The main reason for poor tracking is that the PD and PID controllers were developed based on a simplified linear dynamics model
Model Predictive Control-Based Fast Charging for Vehicular Batteries
Directory of Open Access Journals (Sweden)
Zhibin Song
2011-08-01
Full Text Available Battery fast charging is one of the most significant and difficult techniques affecting the commercialization of electric vehicles (EVs. In this paper, we propose a fast charge framework based on model predictive control, with the aim of simultaneously reducing the charge duration, which represents the out-of-service time of vehicles, and the increase in temperature, which represents safety and energy efficiency during the charge process. The RC model is employed to predict the future State of Charge (SOC. A single mode lumped-parameter thermal model and a neural network trained by real experimental data are also applied to predict the future temperature in simulations and experiments respectively. A genetic algorithm is then applied to find the best charge sequence under a specified fitness function, which consists of two objectives: minimizing the charging duration and minimizing the increase in temperature. Both simulation and experiment demonstrate that the Pareto front of the proposed method dominates that of the most popular constant current constant voltage (CCCV charge method.
A General Attribute and Rule Based Role-Based Access Control Model
Institute of Scientific and Technical Information of China (English)
无
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.
Ripamonti, Francesco; Orsini, Lorenzo; Resta, Ferruccio
2015-04-01
Non-linear behavior is present in many mechanical system operating conditions. In these cases, a common engineering practice is to linearize the equation of motion around a particular operating point, and to design a linear controller. The main disadvantage is that the stability properties and validity of the controller are local. In order to improve the controller performance, non-linear control techniques represent a very attractive solution for many smart structures. The aim of this paper is to compare non-linear model-based and non-model-based control techniques. In particular the model-based sliding-mode-control (SMC) technique is considered because of its easy implementation and the strong robustness of the controller even under heavy model uncertainties. Among the non-model-based control techniques, the fuzzy control (FC), allowing designing the controller according to if-then rules, has been considered. It defines the controller without a system reference model, offering many advantages such as an intrinsic robustness. These techniques have been tested on the pendulum nonlinear system.
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....
UAV Formation Flight Based on Nonlinear Model Predictive Control
Directory of Open Access Journals (Sweden)
Zhou Chao
2012-01-01
Full Text Available We designed a distributed collision-free formation flight control law in the framework of nonlinear model predictive control. Formation configuration is determined in the virtual reference point coordinate system. Obstacle avoidance is guaranteed by cost penalty, and intervehicle collision avoidance is guaranteed by cost penalty combined with a new priority strategy.
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.
Human Behavior Model Based Control Program for ACC Mobile Robot
Directory of Open Access Journals (Sweden)
Claudiu Pozna
2006-07-01
Full Text Available Present work is a part of the ACC autonomous car project. This paper will focuson the control program architecture. To design this architecture we will start from thehuman driver behavior model. Using this model we have constructed a three level controlprogram. Preliminary results are presented.
Reduced-order models for dynamic control of power plants based on controllability and observability
Energy Technology Data Exchange (ETDEWEB)
Ahmed, G.S.; Abdel-Magid, Y.L.
1987-07-01
A new technique for constructing dynamic equivalents of power systems is developed. The method identifies the important modes of the system utilizing a performance index based on the notions of controllability and observability. The system state variables corresponding to the retained modes are identified by inspection of the elements of the sensitivity matrix relating the eigenvalues to the state variables. The suitability of the method for obtaining reduced-order models of power systems for dynamic-control purposes is demonstrated on a single-machine infinite-bus system. Several reduced-order models are produced and their accuracy discussed. 11 refs.
Embarked electrical network robust control based on singular perturbation model.
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.
Model-based control of fuel cells (2): Optimal efficiency
Energy Technology Data Exchange (ETDEWEB)
Golbert, Joshua; Lewin, Daniel R. [PSE Research Group, Wolfson Department of Chemical Engineering, Technion IIT, Haifa 32000 (Israel)
2007-11-08
A dynamic PEM fuel cell model has been developed, taking into account spatial dependencies of voltage, current, material flows, and temperatures. The voltage, current, and therefore, the efficiency are dependent on the temperature and other variables, which can be optimized on the fly to achieve optimal efficiency. In this paper, we demonstrate that a model predictive controller, relying on a reduced-order approximation of the dynamic PEM fuel cell model can satisfy setpoint changes in the power demand, while at the same time, minimize fuel consumption to maximize the efficiency. The main conclusion of the paper is that by appropriate formulation of the objective function, reliable optimization of the performance of a PEM fuel cell can be performed in which the main tunable parameter is the prediction and control horizons, V and U, respectively. We have demonstrated that increased fuel efficiency can be obtained at the expense of slower responses, by increasing the values of these parameters. (author)
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......-Load Tap Changing (OLTC) Transformer, and they are coordinated to keep the voltages of all the buses within the feasible range. Moreover, the reactive power distribution is optimized throughout the wind farm in order to maximize the dynamic reactive power reserve. The sensitivity coefficients...... 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...
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
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......, 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...
Multi-loop adaptive internal model control based on a dynamic partial least squares model
Institute of Scientific and Technical Information of China (English)
Zhao ZHAO; Bin HU; Jun LIANG
2011-01-01
A multi-loop adaptive internal model control (IMC) strategy based on a dynamic partial least squares (PLS) framework is proposed to account for plant model errors caused by slow aging, drift in operational conditions, or environmental changes. Since PLS decomposition structure enables multi-loop controller design within latent spaces, a multivariable adaptive control scheme can be converted easily into several independent univariable control loops in the PLS space. In each latent subspace,once the model error exceeds a specific threshold, online adaptation rules are implemented separately to correct the plant model mismatch via a recursive least squares (RLS) algorithm. Because the IMC extracts the inverse of the minimum part of the internal model as its structure, the IMC controller is self-tuned by explicitly updating the parameters, which are parts of the internal model.Both parameter convergence and system stability are briefly analyzed, and proved to be effective. Finally, the proposed control scheme is tested and evaluated using a widely-used benchmark of a multi-input multi-output (MIMO) system with pure delay.
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.
Multiple Model-Based Robot Control: Development and Initial Evaluation
1988-12-01
the control systems must be as precise as possible to ac- count for high speed robot dynamics . Previous research has shown that payload adaptation is...model for robot dynamics is adequate, and that the coefficients of the model are estimated on-line DD79,Ser87,LE97,KG83]. The adaptive per- turbation...eigenvalues of F(a, t) revealed that linearized robot dynamics was a function of the trajectory and had a weak dependence on payload. The slight F(a
Design of Takagi-Sugeno fuzzy model based nonlinear sliding model controller
Institute of Scientific and Technical Information of China (English)
Xu Yong; Chen Zengqiang; Yuan Zhuzhi
2005-01-01
A design method is presented for Takagi-Sugeno (T-S) fuzzy model based nonlinear sliding model controller. First, the closed-loop fuzzy system is divided into a set of dominant local linear systems according to operating sub-regions. In each sub-region the fuzzy system consists of nominal linear system and a group of interacting systems. Then the controller composed two parts is designed. One part is designed to control the nominal system, the other is designed to control the interacting systems with sliding mode theory. The proposed controller can improve the robustness and guarantee tracking performance of the fuzzy system. Stability is guaranteed without finding a common positive definite matrix.
A Biopsychosocial Model Based on Negative Feedback and Control
Directory of Open Access Journals (Sweden)
Timothy Andrew Carey
2014-02-01
Full Text Available Although the biopsychosocial model has been a popular topic of discussion for over four decades it has not had the traction in fields of research that might be expected of such an intuitively appealing idea. One reason for this might be the absence of an identified mechanism or a functional architecture that is authentically biopsychosocial. What is needed is a robust mechanism that is equally important to biochemical processes as it is to psychological and social processes. Negative feedback may be the mechanism that is required. Negative feedback has been implicated in the regulation of neurotransmitters as well as important psychological and social processes such as emotional regulation and the relationship between a psychotherapist and a client. Moreover, negative feedback is purported to also govern the activity of all other organisms as well as humans. Perceptual Control Theory (PCT describes the way in which negative feedback establishes control at increasing levels of perceptual complexity. Thus, PCT may be the first biopsychosocial model to be articulated in functional terms. In this paper we outline the working model of PCT and explain how PCT provides an embodied hierarchical neural architecture that utilises negative feedback to control physiological, psychological, and social variables. PCT has major implications for both research and practice and, importantly, provides a guide by which fields of research that are currently separated may be integrated to bring about substantial progress in understanding the way in which the brain alters, and is altered by, its behavioural and environmental context.
Vehicle active steering control research based on two-DOF robust internal model control
Wu, Jian; Liu, Yahui; Wang, Fengbo; Bao, Chunjiang; Sun, Qun; Zhao, Youqun
2016-07-01
Because of vehicle's external disturbances and model uncertainties, robust control algorithms have obtained popularity in vehicle stability control. The robust control usually gives up performance in order to guarantee the robustness of the control algorithm, therefore an improved robust internal model control(IMC) algorithm blending model tracking and internal model control is put forward for active steering system in order to reach high performance of yaw rate tracking with certain robustness. The proposed algorithm inherits the good model tracking ability of the IMC control and guarantees robustness to model uncertainties. In order to separate the design process of model tracking from the robustness design process, the improved 2 degree of freedom(DOF) robust internal model controller structure is given from the standard Youla parameterization. Simulations of double lane change maneuver and those of crosswind disturbances are conducted for evaluating the robust control algorithm, on the basis of a nonlinear vehicle simulation model with a magic tyre model. Results show that the established 2-DOF robust IMC method has better model tracking ability and a guaranteed level of robustness and robust performance, which can enhance the vehicle stability and handling, regardless of variations of the vehicle model parameters and the external crosswind interferences. Contradiction between performance and robustness of active steering control algorithm is solved and higher control performance with certain robustness to model uncertainties is obtained.
Tracking control of piezoelectric actuators using a polynomial-based hysteresis model
Gan, Jinqiang; Zhang, Xianmin; Wu, Heng
2016-06-01
A polynomial-based hysteresis model that describes hysteresis behavior in piezoelectric actuators is presented. The polynomial-based model is validated by comparing with the classic Prandtl-Ishlinskii model. Taking the advantages of the proposed model into consideration, inverse control using the polynomial-based model is proposed. To achieve better tracking performance, a hybrid control combining the developed inverse control and a proportional-integral-differential feedback loop is then proposed. To demonstrate the effectiveness of the proposed tracking controls, several comparative experiments of the polynomial-based model and Prandtl-Ishlinskii model are conducted. The experimental results show that inverse control and hybrid control using the polynomial-based model in trajectory-tracking applications are effective and meaningful.
Neural Network Model Based Cluster Head Selection for Power Control
Directory of Open Access Journals (Sweden)
Krishan Kumar
2011-01-01
Full Text Available Mobile ad-hoc network has challenge of the limited power to prolong the lifetime of the network, because power is a valuable resource in mobile ad-hoc network. The status of power consumption should be continuously monitored after network deployment. In this paper, we propose coverage aware neural network based power control routing with the objective of maximizing the network lifetime. Cluster head selection is proposed using adaptive learning in neural networks followed by coverage. The simulation results show that the proposed scheme can be used in wide area of applications in mobile ad-hoc network.
Directory of Open Access Journals (Sweden)
Ye Xie
2015-01-01
Full Text Available To handle different perspectives of unstructured uncertainties, two robust control techniques on the basis of a universal model are studied in this paper. Rather than building a model only applicable to a specific small-scale multirotor helicopter (MHeli, the paper proposes a modeling technique to develop a universal model-framework. Particularly, it is straightforward to apply the universal model to a certain MHeli because the contribution and allocation matrix is proposed in the model-framework. Based on the model uncertainties, the load perturbation of the rotor is the primary focus due to its indispensable importance in the tracking performance. In contrast to the common methods, it is proposed to take this unstructured uncertainty in that external disturbance and designs disturbance observer (DOB. In addition, a class of lead-compensator is specifically designed as for compensating phase lag induced by DOB. Compared with H∞ loop-shaping, greater robust tracking performance on rejecting load perturbation could be achieved as a tradeoff between robust stability and tracking performance which is successfully avoided with DOB-based control strategy.
Nonlinear model predictive control based on collective neurodynamic optimization.
Yan, Zheng; Wang, Jun
2015-04-01
In general, nonlinear model predictive control (NMPC) entails solving a sequential global optimization problem with a nonconvex cost function or constraints. This paper presents a novel collective neurodynamic optimization approach to NMPC without linearization. Utilizing a group of recurrent neural networks (RNNs), the proposed collective neurodynamic optimization approach searches for optimal solutions to global optimization problems by emulating brainstorming. Each RNN is guaranteed to converge to a candidate solution by performing constrained local search. By exchanging information and iteratively improving the starting and restarting points of each RNN using the information of local and global best known solutions in a framework of particle swarm optimization, the group of RNNs is able to reach global optimal solutions to global optimization problems. The essence of the proposed collective neurodynamic optimization approach lies in the integration of capabilities of global search and precise local search. The simulation results of many cases are discussed to substantiate the effectiveness and the characteristics of the proposed approach.
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.
An Observer-Based Finite Control Set Model Predictive Control for Three-Phase Power Converters
Directory of Open Access Journals (Sweden)
Tao Liu
2014-01-01
Full Text Available Finite control set model predictive control (FCS-MPC for three-phase power converters uses a discrete mathematical model of the power converter to predict the future current value for all possible switching states. The circuit parameters and measured input currents are necessary components. For this reason, parameter error and time delay of current signals may degrade the performance of the control system. In the previous studies of the FCS-MPC, few articles study these aspects in detail and almost no method is proposed to avoid these negative influences. This paper, first, investigates the negative impacts of inductance inaccuracy and AC-side current distortion due to the time delay caused by filter on FCS-MPC system. Then, it proposes an observer-based FCS-MPC approach with which the inductance error can be corrected, the current signal’s time delay caused by filter can be compensated, and therefore the performance of FCS-MPC will be improved. At last, as an example, it illustrates the effectiveness of the proposed approach with experimental testing results for a power converter.
Wang, W B; Cao, Z M; Hu, R F
2013-01-01
A model based on a thermodynamic approach is proposed for predicting the dynamics of communicable epidemics in a city, when the epidemic is governed by controlling efforts of multiple scales so that an entropy is associated with the system. All the epidemic details are factored into a single parameter that is determined by maximizing the rate of entropy production. Despite the simplicity of the final model, it predicts the number of hospitalized cases with a reasonable accuracy, using the data of SARS of the year 2003, once the inflexion point characterizing the effect of multiple controlling efforts is known. This model is supposed to be of potential usefulness since epidemics such as avian influenza like H7H9 in China this year have the risk to become communicable among human beings.
Small-signal modelling and control of photovoltaic based water pumping system.
Ghosh, Arun; Ganesh Malla, Siva; Narayan Bhende, Chandrasekhar
2015-07-01
This paper studies small-signal modelling and control design for a photovoltaic (PV) based water pumping system without energy storage. First, the small-signal model is obtained and then, using this model, two proportional-integral (PI) controllers, where one controller is used to control the dc-link voltage and the other one to control the speed of induction motor, are designed to meet control goals such as settling time and peak overshoot of the closed loop responses. The loop robustness of the design is also studied. For a given set of system parameters, simulations are carried out to validate the modelling and the control design.
Inverse grey-box model-based control of a dielectric elastomer actuator
DEFF Research Database (Denmark)
Jones, Richard William; Sarban, Rahimullah
2012-01-01
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...
Coelho, Antonio Augusto Rodrigues
2016-01-01
This paper introduces the Fuzzy Logic Hypercube Interpolator (FLHI) and demonstrates applications in control of multiple-input single-output (MISO) and multiple-input multiple-output (MIMO) processes with Hammerstein nonlinearities. FLHI consists of a Takagi-Sugeno fuzzy inference system where membership functions act as kernel functions of an interpolator. Conjunction of membership functions in an unitary hypercube space enables multivariable interpolation of N-dimensions. Membership functions act as interpolation kernels, such that choice of membership functions determines interpolation characteristics, allowing FLHI to behave as a nearest-neighbor, linear, cubic, spline or Lanczos interpolator, to name a few. The proposed interpolator is presented as a solution to the modeling problem of static nonlinearities since it is capable of modeling both a function and its inverse function. Three study cases from literature are presented, a single-input single-output (SISO) system, a MISO and a MIMO system. Good results are obtained regarding performance metrics such as set-point tracking, control variation and robustness. Results demonstrate applicability of the proposed method in modeling Hammerstein nonlinearities and their inverse functions for implementation of an output compensator with Model Based Predictive Control (MBPC), in particular Dynamic Matrix Control (DMC). PMID:27657723
Preparation Model Based Control System For Hot Steel Strip Rolling Mill Stands
Bouazza, S. E.; Abbassi, H. A.; Moussaoui, A. K.
2008-06-01
As part of a research project on El-hadjar Hot Steel Rolling Mill Plant Annaba Algeria a new Model based control system is suggested to improve the performance of the hot strip rolling mill process. In this paper off-line model based controllers and a process simulator are described. The process models are based on the laws of physics. these models can predict the future behavior and the stability of the controlled process very reliably. The control scheme consists of a control algorithm. This Model based Control system is evaluated on a simulation model that represents accurately the dynamic of the process. Finally the usefulness to the Steel Industry of the suggested method is highlighted.
Directory of Open Access Journals (Sweden)
Fetah Kolonic
2006-10-01
Full Text Available The Tensor Product (TP model transformation is a recently proposed techniquefor transforming given Linear Parameter Varying (LPV state-space models into polytopicmodel form, namely, to parameter varying convex combination of Linear Time Invariant(LTI systems. The main advantage of the TP model transformation is that it is executablein a few minutes and the Linear Matrix Inequality (LMI-based control design frameworkscan immediately be applied to the resulting polytopc models to yield controllers withtractable and guaranteed performance. Various applications of the TP modeltransformation-based design were studied via academic complex and benchmark problems,but no real experimental environment-based study was published. Thus, the main objectiveof this paper is to study how the TP model transformation performs in a real world problemand control setup. The laboratory concept for TP model-based controller design,simulation and real time running on an electromechanical system is presented.Development system for TP model-based controller with one hardware/software platformand target system with real-time hardware/ software support are connected in the uniquesystem. Proposed system is based on microprocessor of personal computer (PC forsimulation and software development as well as for real-time control. Control algorithm,designed and simulated in MATLAB/SIMULINK environment, use graphically orientedsoftware interface for real-time code generation. Some specific conflicting industrial tasksin real industrial crane application, such as fast load positioning control and load swingangle minimization, are considered and compared with other controller types.
Institute of Scientific and Technical Information of China (English)
无
2007-01-01
It is devoted to the development of an autonomous flight control system for small size unmanned helicopter based on dynamical model. At first, the mathematical model of a small size helicopter is described. After that simple but effective MTCV control algorithm was proposed. The whole flight control algorithm is composed of two parts:orientation controller based on the model for rotation dynamics and a robust position controller for a double integrator. The MTCV block is also used to achieve translation velocity control. To demonstrate the performance of the presented algorithm, simulation results and results achieved in real flight experiments were presented.
Energy Technology Data Exchange (ETDEWEB)
Mjalli, F.S.; Al-Asheh, S. [Chemical Engineering Department, Qatar University, Doha (Qatar)
2005-10-01
In this work advanced nonlinear neural networks based control system design algorithms are adopted to control a mechanistic model for an ethanol fermentation process. The process model equations for such systems are highly nonlinear. A neural network strategy has been implemented in this work for capturing the dynamics of the mechanistic model for the fermentation process. The neural network achieved has been validated against the mechanistic model. Two neural network based nonlinear control strategies have also been adopted using the model identified. The performance of the feedback linearization technique was compared to neural network model predictive control in terms of stability and set point tracking capabilities. Under servo conditions, the feedback linearization algorithm gave comparable tracking and stability. The feedback linearization controller achieved the control target faster than the model predictive one but with vigorous and sudden controller moves. (Abstract Copyright [2005], Wiley Periodicals, Inc.)
Institute of Scientific and Technical Information of China (English)
钟伟民; 何国龙; 皮道映; 孙优贤
2005-01-01
A support vector machine (SVM) with quadratic polynomial kernel function based nonlinear model one-step-ahead predictive controller is presented. The SVM based predictive model is established with black-box identification method. By solving a cubic equation in the feature space, an explicit predictive control law is obtained through the predictive control mechanism. The effect of controller is demonstrated on a recognized benchmark problem and on the control of continuous-stirred tank reactor (CSTR). Simulation results show that SVM with quadratic polynomial kernel function based predictive controller can be well applied to nonlinear systems, with good performance in following reference trajectory as well as in disturbance-rejection.
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...
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.
Decentralized model reference adaptive sliding mode control based on fuzzy model
Institute of Scientific and Technical Information of China (English)
Gu Haijun; Zhang Tianping; Shen Qikun
2006-01-01
A new design scheme of decentralized model reference adaptive sliding mode controller for a class of MIMO nonlinear systems with the high-order interconnections is proposed. The design is based on the universal approximation capability of the Takagi - Seguno (T-S) fuzzy systems. Motivated by the principle of certainty equivalentcontrol, a decentralized adaptive controller is designed to achieve the tracking objective without computation of the T-S fuzz ymodel. The approach does not require the upper bound of the uncertainty term to be known through some adaptive estimation. By theoretical analysis, the closed-loop fuzzy control system is proven to be globally stable in the sense that all signalsinvolved are bounded, with tracking errors converging to zero. Simulation results demonstrate the effectiveness of the approach.
Model-Based Development and Evaluation of Control for Complex Multi-Domain Systems
DEFF Research Database (Denmark)
Grujic, Ivan; Nilsson, Rene
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...
Investigation into Model-Based Fuzzy Logic Control
1993-12-01
Logic, in this context, will be used to bridge the gap between linear systems theory and nonlinear control application. Said another way, the language of...to demonstrate the value of applying both Fuzzy Set theory and linear systems theory to the control of nonlinear plants. It is conjectured that the... linear systems theory , to the extent possible. * The plant should be as simple as possible to dearly demonstrate the the developed controller. The
On-line and Model-based Approaches to the Visual Control of Action
Zhao, Huaiyong; Warren, William H.
2014-01-01
Two general approaches to the visual control of action have emerged in last few decades, known as the on-line and model-based approaches. The key difference between them is whether action is controlled by current visual information or on the basis of an internal world model. In this paper, we evaluate three hypotheses: strong on-line control, strong model-based control, and a hybrid solution that combines on-line control with weak off-line strategies. We review experimental research on the co...
Sun, Jianliang; Peng, Yan; Liu, Hongmin
2013-01-01
The crown is a key quality index of strip and plate, the rolling mill system is a complex nonlinear system, the strip qualities are directly affected by the dynamic characteristics of the rolling mil. At present, the studies about the dynamic modeling of the rolling mill system mainly focus on the dynamic simulation for the strip thickness control system, the dynamic characteristics of the strip along the width direction and that of the rolls along axial direction are not considered. In order to study the dynamic changes of strip crown in the rolling process, the dynamic simulation model based on strip crown control is established. The work roll and backup roll are considered as elastic continuous bodies and the work roll and backup roll are joined by a Winkler elastic layer. The rolls are considered as double freely supported beams. The change rate of roll gap is taken into consideration in the metal deformation, based on the principle of dynamic conservation of material flow, the two dimensional dynamic model of metal is established. The model of metal deformation provides exciting force for the rolls dynamic model, and the rolls dynamic model and metal deformation model couple together. Then, based on the two models, the dynamic model of rolling mill system based on strip crown control is established. The Newmark-β method is used to solve the problem, and the dynamic changes of these parameters are obtained as follows: (1) The bending of work roll and backup roll changes with time; (2) The strip crown changes with time; (3) The distribution of rolling force changes with time. Take some cold tandem rolling mill as subject investigated, simulation results and the comparisons with experimental results show that the dynamic model built is rational and correct. The proposed research provides effective theory for optimization of device and technological parameters and development of new technology, plays an important role to improve the strip control precision and
Implementation of a Fractional Model-Based Fault Detection Algorithm into a PLC Controller
Kopka, Ryszard
2014-12-01
This paper presents results related to the implementation of model-based fault detection and diagnosis procedures into a typical PLC controller. To construct the mathematical model and to implement the PID regulator, a non-integer order differential/integral calculation was used. Such an approach allows for more exact control of the process and more precise modelling. This is very crucial in model-based diagnostic methods. The theoretical results were verified on a real object in the form of a supercapacitor connected to a PLC controller by a dedicated electronic circuit controlled directly from the PLC outputs.
Model-based control of mechanical ventilation: design and clinical validation.
Martinoni, E P; Pfister, Ch A; Stadler, K S; Schumacher, P M; Leibundgut, D; Bouillon, T; Böhlen, T; Zbinden, A M
2004-06-01
We developed a model-based control system using end-tidal carbon dioxide fraction (FE'(CO(2))) to adjust a ventilator during clinical anaesthesia. We studied 16 ASA I-II patients (mean age 38 (range 20-59) yr; weight 67 (54-87) kg) during i.v. anaesthesia for elective surgery. After periods of normal ventilation the patients were either hyper- or hypoventilated to assess precision and dynamic behaviour of the control system. These data were compared with a previous group where a fuzzy-logic controller had been used. Responses to different clinical events (invalid carbon dioxide measurement, limb tourniquet release, tube cuff leak, exhaustion of carbon dioxide absorbent, simulation of pulmonary embolism) were also noted. The model-based controller correctly maintained the setpoint. No significant difference was found for the static performance between the two controllers. The dynamic response of the model-based controller was more rapid (Pfuzzy-logic and model-based control, respectively, and after a 1 vol% decrease was 355 (127) s and 177 (36) s, respectively. The new model-based controller had a consistent response to clinical artefacts. A model-based FE'(CO(2)) controller can be used in a clinical setting. It reacts appropriately to artefacts, and has a better dynamic response to setpoint changes than a previously described fuzzy-logic controller.
Energy-based modelling and control of wind energy conversion system with DFIG
Song, H. H.; Qu, Y. B.
2011-02-01
Focusing on wind energy conversion system (WECS) at the doubly-fed induction generator (DFIG) control level, a novel control approach was proposed to optimise wind energy capture from consideration of physical nature and energy relationship. According to energy flowing, the WECS was divided into several multi-ports energy conversion subsystems, and the structure matrices of the subsystems were elaborately designed. Based on this, port-controlled Hamiltonian models of the subsystems were obtained, and energy-based control using the models was provided to realise the machine side and the grid side control objectives of the WECS. The approach was applied on a 2 MW WECS, and compared with classical proportional-integral (PI) controller using MATLAB/Simulink. The results show that the energy-based control not only fully satisfies both side control requirements, but also has more robust control performances for a turbulent wind than the PI control.
Artificial Neural Networks Based Modeling and Control of Continuous Stirred Tank Reactor
Directory of Open Access Journals (Sweden)
R. S.M.N. Malar
2009-01-01
Full Text Available Continuous Stirred Tank Reactor (CSTR is one of the common reactors in chemical plant. Problem statement: Developing a model incorporating the nonlinear dynamics of the system warrants lot of computation. An efficient control of the product concentration can be achieved only through accurate model. Approach: In this study, attempts were made to alleviate the above mentioned problem using Artificial Intelligence (AI techniques. One of the AI techniques namely Artificial Neural Networks (ANN was used to model the CSTR incorporating its non-linear characteristics. Two nonlinear models based control strategies namely internal model control and direct inverse control were designed using the neural networks and applied to the control of isothermal CSTR. Results: The simulation results for the above control schemes with set point tracking were presented. Conclusion: Results indicated that neural networks can learn accurate models and give good non-linear control when model equations are not known.
Model predictive combustion control based on neural nets
Energy Technology Data Exchange (ETDEWEB)
Schmidt, D. [Powitec Intelligent Technologies GmbH, Essen (Germany); Kampschreuer, T. [AVR Afvalverwerking B.V., Duiven/Arnheim (Netherlands)
2008-07-01
The first closed-loop Neural Net combustion controller in the Netherlands has been installed at the HVC plant in Alkmaar. During the summer 2006 the first of the 'old' three lines was equipped with an individually controllable primary air distribution. As 'fire controller' the combustion optimiser from Powitec, the PiT Navigator, was selected, a system using digital image processing and neural nets. This paper shows the results from operating the plant with and without the NMPC optimiser and from the performance tests. (orig.)
Model-based Locomotion Control of Underactuated Snake Robots
Rezapour, Ehsan
2015-01-01
Snake robots are a class of biologically inspired robots which are built to emulate the features of biological snakes. These robots are underactuated, i.e. they have fewer control inputs than degrees of freedom, and are hyper redundant, i.e. they have many degrees of freedom. Furthermore, snake robots utilize complex motion patterns and possess a complicated but highly flexible physical structure. These properties make locomotion control of snake robots a complicated and cha...
Multi-model-based Access Control in Construction Projects
Hilbert, Frank; Araujo, Larissa; 10.4204/EPTCS.83.1
2012-01-01
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.
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.
Modeling and Stability Analysis for Non-linear Network Control System Based on T-S Fuzzy Model
Institute of Scientific and Technical Information of China (English)
ZHANG Hong; FANG Huajing
2007-01-01
Based on the T-S fuzzy model, this paper presents a new model of non-linear network control system with stochastic transfer delay. Sufficient criterion is proposed to guarantee globally asymptotically stability of this two-levels T-S fuzzy model. Also a T-S fuzzy observer of NCS is designed base on this two-levels T-S fuzzy model. All these results present a new approach for networked control system analysis and design.
Model-Based Torque Control of Piezoelectric Ultrasonic Motors Project
National Aeronautics and Space Administration — Piezoelectric ultrasonic motors (PUMs) are ideal actuators for a variety of spaced-based robotics applications. These motors replace conventional drive systems...
Directory of Open Access Journals (Sweden)
Koichi Kobayashi
2016-01-01
Full Text Available A networked control system (NCS is a control system where components such as plants and controllers are connected through communication networks. Self-triggered control is well known as one of the control methods in NCSs and is a control method that for sampled-data control systems both the control input and the aperiodic sampling interval (i.e., the transmission interval are computed simultaneously. In this paper, a self-triggered model predictive control (MPC method for discrete-time linear systems with disturbances is proposed. In the conventional MPC method, the first one of the control input sequence obtained by solving the finite-time optimal control problem is sent and applied to the plant. In the proposed method, the first some elements of the control input sequence obtained are sent to the plant, and each element is sequentially applied to the plant. The number of elements is decided according to the effect of disturbances. In other words, transmission intervals can be controlled. Finally, the effectiveness of the proposed method is shown by numerical simulations.
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.
Institute of Scientific and Technical Information of China (English)
RU Chang-hai; SUN Li-ning; RONG Wei-bin
2008-01-01
Aiming at the limitation of control accuracy caused by hysteresis and creep for a piezoelectric actuator, the hysteresis phenomenon is explained based on the microscopic polarization mechanism and domain wall theory. Then a control model based on polarization is established, which can reduce the hysteresis and creep remarkablely. The experimental results show that the polarization control method is with more linearity and less hysteresis compared with the voltage control method.
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...
Model based monitoring for industrial and traffic noise control
Eerden, F.J.M. van der; Binnerts, B.; Graafland, F.
2015-01-01
Noise control starts by understanding the actual noise situation. Especially for situations where the distance between industrial and traffic noise sources and a local community is in the order of one kilometer or more, it may not be clear what sources are the main contributors to annoyance. Then a
Gain Scheduling Control of Nonlinear Systems Based on Neural State Space Models
DEFF Research Database (Denmark)
Bendtsen, Jan Dimon; Stoustrup, Jakob
2003-01-01
This paper presents a novel method for gain scheduling control of nonlinear systems based on extraction of local linear state space models from neural networks with direct application to robust control. A neural state space model of the system is first trained based on in- and output training...... samples from the system, after which linearized state space models are extracted from the neural network in a number of operating points according to a simple and computationally cheap scheme. Robust observer-based controllers can then be designed in each of these operating points,and gain scheduling...
A Generic Role Based Access Control Model for Wind Power Systems
DEFF Research Database (Denmark)
Nagarajan, Anand; Jensen, Christian D.
2010-01-01
infrastructure in a software domain in a manufacturer independent manner as well as establishing secure communication and authenticating the other parties in electrical power infrastructures, but they do not address the problem of access control. We therefore propose a generic model for access control in wind...... power systems, which is based on the widely used role-based access control model. The proposed model is tested using a prototype designed in conformance with the standards that are in use in modern wind power infrastructure and the results are presented to determine the overhead in communication caused...... while adhering to the proposed access model....
Artificial intelligence in process control: Knowledge base for the shuttle ECS model
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.
Study on Model Based Combustion Control of Diesel Engine with Multi Fuel Injection
Ikemura, R.; Yamasaki, Y.; Kaneko, S.
2016-09-01
A controller for model-based control of diesel engine with triple injection were developed with a combustion model. In the combustion model, an engine cycle is discretized into several representative points in order to improve calculation speed, while physical equations are employed to expand the versatility. The combustion model can predict in-cylinder pressure and temperature in these discrete points. Prediction accuracy of the combustion model was evaluated by comparison with experimental result. A controller was designed with the combustion model in order to calculate optimal fuel injection pattern for controlling in-cylinder pressure peak timing. The controller's performance was evaluated through simulation in which the combustion model was used as a plant model.
Study of Super-Twisting sliding mode control for U model based nonlinear system
Zhang, Jianhua; Li, Yang; Xueli WU; Jianan HUO; Shenyang ZHUANG
2016-01-01
The Super-Twisting control algorithm is adopted to analyze the U model based nonlinear control system in order to solve the controller design problems of non-affine nonlinear systems. The non-affine nonlinear systems are studied, the neural network approximation of the nonlinear function is performed, and the Super-Twisting control algorithm is used to control. The convergence of the Super-Twisting algorithm is proved by selecting an appropriate Lyapunov function. The Matlab simulation is car...
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.
International Workshop on Advanced Dynamics and Model Based Control of Structures and Machines
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).
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...
Controlling reuse in pattern-based model-to-model transformations
Guerra, Esther,; De Lara, Juan,; Orejas, Fernando
2010-01-01
Model-to-model transformation is a central activity in Model-Driven Engineering that consists of transforming models from a source to a target language. Pattern-based model-to-model transformation is our approach for specifying transformations in a declarative, relational and formal style. The approach relies on patterns describing allowed or forbidden relations between two models. These patterns are compiled into operational mechanisms to perform forward and backward transformations. Inspire...
A Modelica-based Model Library for Building Energy and Control Systems
Energy Technology Data Exchange (ETDEWEB)
Wetter, Michael
2009-04-07
This paper describes an open-source library with component models for building energy and control systems that is based on Modelica, an equation-based objectoriented language that is well positioned to become the standard for modeling of dynamic systems in various industrial sectors. The library is currently developed to support computational science and engineering for innovative building energy and control systems. Early applications will include controls design and analysis, rapid prototyping to support innovation of new building systems and the use of models during operation for controls, fault detection and diagnostics. This paper discusses the motivation for selecting an equation-based object-oriented language. It presents the architecture of the library and explains how base models can be used to rapidly implement new models. To demonstrate the capability of analyzing novel energy and control systems, the paper closes with an example where we compare the dynamic performance of a conventional hydronic heating system with thermostatic radiator valves to an innovative heating system. In the new system, instead of a centralized circulation pump, each of the 18 radiators has a pump whose speed is controlled using a room temperature feedback loop, and the temperature of the boiler is controlled based on the speed of the radiator pump. All flows are computed by solving for the pressure distribution in the piping network, and the controls include continuous and discrete time controls.
Intelligent control using multiple models based on on-line learning
Institute of Scientific and Technical Information of China (English)
Junyong ZHAI; Shumin FEI; Feipeng DA
2006-01-01
In this paper we deal with the problem of plants with large parameter variations under different operating modes. A novel intelligent control algorithm based on multiple models is proposed to improve the dynamical response performance. At the same time adaptive model bank is applied to establish models without prior system information.Multiple models and corresponding controllers are automatically established on-line by a conventionally adaptive model and a re-initialized one. A best controller is chosen by the performance function at every instant. The closed-loop system's stability and asymptotical convergence of tracking error can be guaranteed. Simulation results have confirmed the validity of the proposed method.
Model Based Predictive Control of Thermal Comfort for Integrated Building System
Georgiev, Tz.; Jonkov, T.; Yonchev, E.; Tsankov, D.
2011-12-01
This article deals with the indoor thermal control problem in HVAC (heating, ventilation and air conditioning) systems. Important outdoor and indoor variables in these systems are: air temperature, global and diffuse radiations, wind speed and direction, temperature, relative humidity, mean radiant temperature, and so on. The aim of this article is to obtain the thermal comfort optimisation by model based predictive control algorithms (MBPC) of an integrated building system. The control law is given by a quadratic programming problem and the obtained control action is applied to the process. The derived models and model based predictive control algorithms are investigated based on real—live data. All researches are derived in MATLAB environment. The further research will focus on synthesis of robust energy saving control algorithms.
Experimental Model Based Feedback Control for Flutter Suppression and Gust Load Alleviation Project
National Aeronautics and Space Administration — ZONA Technology, Inc. (ZONA) proposes an R&D effort to develop an Experimental Model Based Feedback Control (EMBFC) Framework for the flutter suppression and...
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.
Model-based beam control for illumination of remote objects
Chandler, Susan M.; Lukesh, Gordon W.; Voelz, David; Basu, Santasri; Sjogren, Jon A.
2004-11-01
On September 1, 2003, Nukove Scientific Consulting, together with partner New Mexico State University, began work on a Phase 1 Small Business Technology TRansfer (STTR) grant from the United States Air Force Office of Scientific Research (AFOSR). The purpose of the grant was to show the feasibility of taking Nukove's pointing estimation technique from a post-processing tool for estimation of laser system characteristics to a real-time tool usable in the field. Nukove's techniques for pointing, shape, and OCS estimation do not require an imaging sensor nor a target board, thus estimates may be made very quickly. To prove feasibility, Nukove developed an analysis tool RHINO (Real-time Histogram Interpretation of Numerical Observations) and successfully demonstrated the emulation of real-time, frame-by-frame estimation of laser system characteristics, with data streamed into the tool and the estimates displayed as they are made. The eventual objective will be to use the frame-by-frame estimates to allow for feedback to a fielded system. Closely associated with this, NMSU developed a laboratory testbed to illuminate test objects, collect the received photons, and stream the data into RHINO. The two coupled efforts clearly demonstrate the feasibility of real-time pointing control of a laser system.
Synthesis of Model Based Robust Stabilizing Reactor Power Controller for Nuclear Power Plant
Directory of Open Access Journals (Sweden)
Arshad Habib Malik
2011-04-01
Full Text Available In this paper, a nominal SISO (Single Input Single Output model of PHWR (Pressurized Heavy Water Reactor type nuclear power plant is developed based on normal moderator pump-up rate capturing the moderator level dynamics using system identification technique. As the plant model is not exact, therefore additive and multiplicative uncertainty modeling is required. A robust perturbed plant model is derived based on worst case model capturing slowest moderator pump-up rate dynamics and moderator control valve opening delay. Both nominal and worst case models of PHWR-type nuclear power plant have ARX (An Autoregressive Exogenous structures and the parameters of both models are estimated using recursive LMS (Least Mean Square optimization algorithm. Nominal and worst case discrete plant models are transformed into frequency domain for robust controller design purpose. The closed loop system is configured into two port model form and H? robust controller is synthesized. The H?controller is designed based on singular value loop shaping and desired magnitude of control input. The selection of desired disturbance attenuation factor and size of the largest anticipated multiplicative plant perturbation for loop shaping of H? robust controller form a constrained multi-objective optimization problem. The performance and robustness of the proposed controller is tested under transient condition of a nuclear power plant in Pakistan and found satisfactory.
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...... diagnosis methods, often viewed as the classical or deterministic ones. Emphasis is placed on the algorithms suitable for ship automation, unmanned underwater vehicles, and other systems of automatic control....
Adaptive switching control of discrete time nonlinear systems based on multiple models
Institute of Scientific and Technical Information of China (English)
Rui KAN
2004-01-01
We use the approach of "optimal" switching to design the adaptive control because the design among multiple models is intuitively more practically feasible than the traditional adaptive control in improving the performances. We prove that for a typical class of nonlinear systems disturbed by random noise, the multiple model adaptive switching control based on WLS(Weighted Least Squares) or projected-LS (Least Squares) is stable and convergent.
State Estimation and Model-Based Control of a Pilot Anaerobic Digestion Reactor
Directory of Open Access Journals (Sweden)
Finn Haugen
2014-01-01
Full Text Available A state estimator and various model-based control systems have been designed for a real anaerobic digestion (AD pilot reactor fed with dairy manure. The model used is a modified Hill model which is a relatively simple dynamical AD process model. The state estimator is an Unscented Kalman Filter (UKF which uses only methane gas flow measurement to update its states. The model and the state estimates are used in different control systems. One of the control systems aims at controlling the methane gas flow to a setpoint. Simulations indicate that the setpoint tracking performance of a predictive control system is considerably better comparing with PI control, while disturbance compensation is not much better. Consequently, assuming the setpoint is constant, the PI controller competes well with the predictive controller. A successful application of predictive control of the real reactor is presented. Also, three different control systems aiming at retaining the reactor at an operating point where the volatile fatty acids (VFA concentration has a maximum, safe value are designed. A simulation study indicates that the best control solution among the three alternatives is PI control based on feedback from estimated VFA.
Nonlinear model predictive control with guaraneed stability based on pesudolinear neural networks
Institute of Scientific and Technical Information of China (English)
WANG Yongji; WANG Hong
2004-01-01
A nonlinear model predictive control problem based on pseudo-linear neural network (PNN) is discussed, in which the second order on-line optimization method is adopted. The recursive computation of Jacobian matrix is investigated. The stability of the closed loop model predictive control system is analyzed based on Lyapunov theory to obtain the sufficient condition for the asymptotical stability of the neural predictive control system. A simulation was carried out for an exothermic first-order reaction in a continuous stirred tank reactor. It is demonstrated that the proposed control strategy is applicable to some of nonlinear systems.
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...
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....
Institute of Scientific and Technical Information of China (English)
Qi Zhidong; Zhu Xinjian; Cao Guangyi
2006-01-01
Aiming at on-line controlling of Direct Methanol Fuel Cell (DMFC) stack, an adaptive neural fuzzy inference technology is adopted in the modeling and control of DMFC temperature system. In the modeling process, an Adaptive Neural Fuzzy Inference System (ANFIS) identification model of DMFC stack temperature is developed based on the input-output sampled data, which can avoid the internal complexity of DMFC stack. In the controlling process, with the network model trained well as the reference model of the DMFC control system, a novel fuzzy genetic algorithm is used to regulate the parameters and fuzzy rules of a neural fuzzy controller. In the simulation, compared with the nonlinear Proportional Integral Derivative (PID) and traditional fuzzy algorithm, the improved neural fuzzy controller designed in this paper gets better performance, as demonstrated by the simulation results.
A New Flatness Pattern Recognition Model Based on Cerebellar Model Articulation Controllers Network
Institute of Scientific and Technical Information of China (English)
HE Hai-tao; LI Yan
2008-01-01
In the traditional flatness pattern recognition neural network,the topologic configurations need to be rebuilt with a changing width of cold strip.Furthermore,the large learning assignment,slow convergence,and local minimum in the network are observed.Moreover,going by the structure of the tradtional neural network,according to experience,the model is time-consuming and complex.Thus,a new approach of flatness pattern recognition is proposed based on the CMAC (cerebellar model articulation controllers) neural network.The difference in fuzzy distances between samples and the basic patterns is introduced as the input of the CMAC network.Simultaneously,the adequate learning rate is improved in the error correction algorithm of this neural network.The new approach with advantages,such as high learning speed,good generalization,and easy implementation,is efficient and intelligent.The simulation results show that the speed and accuracy of the flatness pattern recognition model are obviously improved.
Model-based Sliding Mode Controller of Anti-lock Braking System
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.
Neural model-based adaptive control for systems with unknown Preisach-type hysteresis
Institute of Scientific and Technical Information of China (English)
Chuntao LI; Yonghong TAN
2004-01-01
An adaptive control scheme is presented for systems with unknown hysteresis. In order to handle the case where the hysteresis output is unmeasurale, a novel model is firstly developed to describe the characteristic of hysteresis. This model is motivated by Preisach model but implemented by using neural networks (NN). The main advantage is that it is easily used for controller design. Then, the adaptive controller based on the proposed model is presented for a class of SISO nonlinear systems preceded by unknown hysteresis, which is estimated by the proposed model. The laws for model updating and the control laws for the neural adaptive controller are derived from Lyapunov stability theorem, therefore the semi- global stability of the closed-loop system is guaranteed. At last, the simulation results are illustrated.
Huang, Qingjiu; Fukuhara, Yasuyuki; Chen, Xuedong
In this paper, we proposed a robust control method based on the virtual suspension model for keeping the posture stability and decreasing the tiny vibration of the robot body when it is walking on irregular terrain. Firstly, we developed a six-legged walking robot for this study based on stable theory of wave gaits and CAD dynamic model. Secondly, in order to keep the posture stability of body when robot walks, we designed a virtual suspension model with one degree of freedom, which has virtual spring and damper, for the direction of the center of gravity, the pitch angle, and the roll angle of body respectively. And then, in order to decrease the tiny vibration of body when robot walks, we proposed an active suspension control by using sliding mode control based on a virtual suspension model. These proposed methods are discussed using the walking experimental results of the developed six-legged walking robot.
Adaptive Control of MEMS Gyroscope Based on T-S Fuzzy Model
Directory of Open Access Journals (Sweden)
Yunmei Fang
2015-01-01
Full Text Available A multi-input multioutput (MIMO Takagi-Sugeno (T-S fuzzy model is built on the basis of a nonlinear model of MEMS gyroscope. A reference model is adjusted so that a local linear state feedback controller could be designed for each T-S fuzzy submodel based on a parallel distributed compensation (PDC method. A parameter estimation scheme for updating the parameters of the T-S fuzzy models is designed and analyzed based on the Lyapunov theory. A new adaptive law can be selected to be the former adaptive law plus a nonnegative in variable to guarantee that the derivative of the Lyapunov function is smaller than zero. The controller output is implemented on the nonlinear model and T-S fuzzy model, respectively, for the purpose of comparison. Numerical simulations are investigated to verify the effectiveness of the proposed control scheme and the correctness of the T-S fuzzy model.
Neural-networks-based Modelling and a Fuzzy Neural Networks Controller of MCFC
Institute of Scientific and Technical Information of China (English)
无
2002-01-01
Molten Carbonate Fuel Cells (MCFC) are produced with a highly efficient and clean power generation technology which will soon be widely utilized. The temperature characters of MCFC stack are briefly analyzed. A radial basis function (RBF) neural networks identification technology is applied to set up the temperature nonlinear model of MCFC stack, and the identification structure, algorithm and modeling training process are given in detail. A fuzzy controller of MCFC stack is designed. In order to improve its online control ability, a neural network trained by the I/O data of a fuzzy controller is designed. The neural networks can memorize and expand the inference rules of the fuzzy controller and substitute for the fuzzy controller to control MCFC stack online. A detailed design of the controller is given. The validity of MCFC stack modelling based on neural networks and the superior performance of the fuzzy neural networks controller are proved by Simulations.
Fuzzy Shape Control Based on Elman Dynamic Recursion Network Prediction Model
Institute of Scientific and Technical Information of China (English)
JIA Chun-yu; LIU Hong-min
2006-01-01
In the strip rolling process, shape control system possesses the characteristics of nonlinearity, strong coupling, time delay and time variation. Based on self-adapting Elman dynamic recursion network prediction model, the fuzzy control method was used to control the shape on four-high cold mill. The simulation results showed that the system can be applied to real time on line control of the shape.
A Component-Based Conference Control Model and Implementation for Loosely Coupled Sessions
Institute of Scientific and Technical Information of China (English)
无
2002-01-01
Conference control is a very important core part to compose a complete Internet multimedia conference system and has been a hot research area over the years, but there are currently no widely accepted robust and scalable solutions and standards. This paper proposes a component-based conference control model for loosely coupled sessions in which media applications can collaborate with a Session Controller(SC) to provide the conference control. A SC prototype has been built.
Data Analytics Based Dual-Optimized Adaptive Model Predictive Control for the Power Plant Boiler
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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.
High-speed tracking control of piezoelectric actuators using an ellipse-based hysteresis model.
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.
DEFF Research Database (Denmark)
Yang, Z.; Izadi-Zamanabadi, Roozbeh; Blanke, M.
2000-01-01
Based on the model-matching strategy, an adaptive control reconfiguration method for a class of nonlinear control systems is proposed by using the multiple-model scheme. Instead of requiring the nominal and faulty nonlinear systems to match each other directly in some proper sense, three sets...... 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...
DEFF Research Database (Denmark)
Yang, Z.; Izadi-Zamanabadi, Roozbeh; Blanke, M.
2000-01-01
Based on the model-matching strategy, an adaptive control reconfiguration method for a class of nonlinear control systems is proposed by using the multiple-model scheme. Instead of requiring the nominal and faulty nonlinear systems to match each other directly in some proper sense, three sets of ...... 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...
Neuro-Sliding-Mode Control of Flexible-Link Manipulators Based on Singularly Perturbed Model
Institute of Scientific and Technical Information of China (English)
ZHANG Yu; YANG Tangwen; SUN Zengqi
2009-01-01
A neuro-sliding-mode control (NSMC) strategy was developed to handle the complex nonlinear dynamics and model uncertainties of flexible-link manipulators. A composite controller was designed based on a singularly perturbed model of flexible-link manipulators when the rigid motion and flexible motion are decoupled. The NSMC is employed to control the slow subsystem to track a desired trajectory with a traditional sliding mode controller to stabilize the fast subsystem which represents the link vibrations. A stability analysis of the flexible modes is also given. Simulations confirm that the NSMC performs better than the tra-ditional sliding-mode control for controlling flexible-link manipulators. The control strategy not only gives good tracking performance for the joint angle, but also effectively suppresses endpoint vibrations. The simulations also show that the control strategy has a strong self-adaptive ability for controlling manipulators with different parameters.
Davijani, Nafiseh Zare; Jahanfarnia, Gholamreza; Abharian, Amir Esmaeili
2017-01-01
One of the most important issues with respect to nuclear reactors is power control. In this study, we designed a fractional-order sliding mode controller based on a nonlinear fractional-order model of the reactor system in order to track the reference power trajectory and overcome uncertainties and external disturbances. Since not all of the variables in an operating reactor are measurable or specified in the control law, we propose a reduced-order fractional neutron point kinetic (ROFNPK) model based on measurable variables. In the design, we assume the differences between the approximated model and the real system is limited. We use the obtained model in the controller design process and use the Lyapunov method to perform a stability analysis of the closed-loop system. We simulate the proposed reduced-order fractional-order sliding mode controller (ROFOSMC) using Matlab/Simulink, and its performance is compared with that of a reduced order integer-order sliding mode controller (ROIOSMC). Our simulation results indicate an acceptable performance of the proposed approach in tracking the reference power trajectory with respect to ROIOSMC because of faster response of control effort signal and the smaller tracking error. Moreover, the results illustrate the capability of the controller in rejection of the disturbance and the noise signals and the robustness of controller against uncertainty.
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.
H∞ tracking control of coupled spatiotemporal chaos based on fuzzy models
Institute of Scientific and Technical Information of China (English)
Dou Chun-Xia
2005-01-01
Due to the interactions among coupled spatiotemporal subsystems, it is difficult to achieve the tracking control of the coupled spatiotemporal chaos. However, every subsystem of the coupled spatiotemporal chaos can be approximated by a set of fuzzy models, of which each represents a linearized model of the subsystem corresponding to the operating point of the controlled system. Based on these fuzzy models, an H∞ fuzzy tracking control scheme is suggested,where a linear matrix inequalities (LMI) is employed to represent the feedback controller. The parameters of controller are obtained by using convex optimization techniques of LMI. The model reference tracking control of the coupled spatiotemporal chaos is achieved, and the stability of the system is also guaranteed. The tracking performance is tested by simulation as an example.
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...
Advanced Dynamics and Model-Based Control of Structures and Machines
Krommer, Michael; Belyaev, Alexander
2012-01-01
The book contains 26 scientific contributions by leading experts from Russia, Austria, Italy, Japan and Taiwan. It presents an overview on recent developments in Advanced Dynamics and Model Based Control of Structures and Machines. Main topics are nonlinear control of structures and systems, sensing and actuation, active and passive damping, nano- and micromechanics, vibrations and waves.
Autopilot Design Method for the Blended Missile Based on Model Predictive Control
Directory of Open Access Journals (Sweden)
Baoqing Yang
2015-01-01
Full Text Available This paper develops a novel autopilot design method for blended missiles with aerodynamic control surfaces and lateral jets. Firstly, the nonlinear model of blended missiles is reduced into a piecewise affine (PWA model according to the aerodynamics properties. Secondly, based on the equivalence between the PWA model and mixed logical dynamical (MLD model, the MLD model of blended missiles is proposed taking into account the on-off constraints of lateral pulse jets. Thirdly, a hybrid model predictive control (MPC method is employed to design autopilot. Finally, simulation results under different conditions are presented to show the effectiveness of the proposed method, which demonstrate that control allocation between aerodynamic control surfaces and lateral jets is realized by adjusting the weighting matrix in an index function.
Csank, Jeffrey T.; Stueber, Thomas J.
2013-01-01
A dual flow-path inlet system is being tested to evaluate methodologies for a Turbine Based Combined Cycle (TBCC) propulsion system to perform a controlled inlet mode transition. Prior to experimental testing, simulation models are used to test, debug, and validate potential control algorithms. One simulation package being used for testing is the High Mach Transient Engine Cycle Code simulation, known as HiTECC. This paper discusses the closed loop control system, which utilizes a shock location sensor to improve inlet performance and operability. Even though the shock location feedback has a coarse resolution, the feedback allows for a reduction in steady state error and, in some cases, better performance than with previous proposed pressure ratio based methods. This paper demonstrates the design and benefit with the implementation of a proportional-integral controller, an H-Infinity based controller, and a disturbance observer based controller.
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.
Quasilinear Extreme Learning Machine Model Based Internal Model Control for Nonlinear Process
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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.
Shapiro, Carl R.; Meyers, Johan; Meneveau, Charles; Gayme, Dennice F.
2016-09-01
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.
Model and controller reduction of large-scale structures based on projection methods
Gildin, Eduardo
The design of low-order controllers for high-order plants is a challenging problem theoretically as well as from a computational point of view. Frequently, robust controller design techniques result in high-order controllers. It is then interesting to achieve reduced-order models and controllers while maintaining robustness properties. Controller designed for large structures based on models obtained by finite element techniques yield large state-space dimensions. In this case, problems related to storage, accuracy and computational speed may arise. Thus, model reduction methods capable of addressing controller reduction problems are of primary importance to allow the practical applicability of advanced controller design methods for high-order systems. A challenging large-scale control problem that has emerged recently is the protection of civil structures, such as high-rise buildings and long-span bridges, from dynamic loadings such as earthquakes, high wind, heavy traffic, and deliberate attacks. Even though significant effort has been spent in the application of control theory to the design of civil structures in order increase their safety and reliability, several challenging issues are open problems for real-time implementation. This dissertation addresses with the development of methodologies for controller reduction for real-time implementation in seismic protection of civil structures using projection methods. Three classes of schemes are analyzed for model and controller reduction: nodal truncation, singular value decomposition methods and Krylov-based methods. A family of benchmark problems for structural control are used as a framework for a comparative study of model and controller reduction techniques. It is shown that classical model and controller reduction techniques, such as balanced truncation, modal truncation and moment matching by Krylov techniques, yield reduced-order controllers that do not guarantee stability of the closed-loop system, that
Roy, Prasanta; Roy, Binoy Krishna
2016-07-01
The Quadruple Tank Process (QTP) is a well-known benchmark of a nonlinear coupled complex MIMO process having both minimum and nonminimum phase characteristics. This paper presents a novel self tuning type Dual Mode Adaptive Fractional Order PI controller along with an Adaptive Feedforward controller for the QTP. The controllers are designed based on a novel Variable Parameter Transfer Function model. The effectiveness of the proposed model and controllers is tested through numerical simulation and experimentation. Results reveal that the proposed controllers work successfully to track the reference signals in all ranges of output. A brief comparison with some of the earlier reported similar works is presented to show that the proposed control scheme has some advantages and better performances than several other similar works.
Study on Super-Twisting synchronization control of chaotic system based on U model
Directory of Open Access Journals (Sweden)
Jianhua ZHANG
2016-06-01
Full Text Available A U model based Super-Twisting synchronization control method for chaotic systems is proposed. The chaos control of chaotic systems is prescribed, then, based on the current research status of chaotic systems and some useful research results in nonlinear system design, some new methods for chaos control and synchronization are provided, and the controller is designed to achieve the finite time chaos synchronization. The numerical simulations are carried out for Lorenz system and Chen system, and the result proves the effectiveness of the method.
Automatic Gauge Control in Rolling Process Based on Multiple Smith Predictor Models
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Jiangyun Li
2014-01-01
Full Text Available Automatic rolling process is a high-speed system which always requires high-speed control and communication capabilities. Meanwhile, it is also a typical complex electromechanical system; distributed control has become the mainstream of computer control system for rolling mill. Generally, the control system adopts the 2-level control structure—basic automation (Level 1 and process control (Level 2—to achieve the automatic gauge control. In Level 1, there is always a certain distance between the roll gap of each stand and the thickness testing point, leading to the time delay of gauge control. Smith predictor is a method to cope with time-delay system, but the practical feedback control based on traditional Smith predictor cannot get the ideal control result, because the time delay is hard to be measured precisely and in some situations it may vary in a certain range. In this paper, based on adaptive Smith predictor, we employ multiple models to cover the uncertainties of time delay. The optimal model will be selected by the proposed switch mechanism. Simulations show that the proposed multiple Smith model method exhibits excellent performance in improving the control result even for system with jumping time delay.
Predictive-model-based dynamic coordination control strategy for power-split hybrid electric bus
Zeng, Xiaohua; Yang, Nannan; Wang, Junnian; Song, Dafeng; Zhang, Nong; Shang, Mingli; Liu, Jianxin
2015-08-01
Parameter-matching methods and optimal control strategies of the top-selling hybrid electric vehicle (HEV), namely, power-split HEV, are widely studied. In particular, extant research on control strategy focuses on the steady-state energy management strategy to obtain better fuel economy. However, given that multi-power sources are highly coupled in power-split HEVs and influence one another during mode shifting, conducting research on dynamic coordination control strategy (DCCS) to achieve riding comfort is also important. This paper proposes a predictive-model-based DCCS. First, the dynamic model of the objective power-split HEV is built and the mode shifting process is analyzed based on the developed model to determine the reason for the system shock generated. Engine torque estimation algorithm is then designed according to the principle of the nonlinear observer, and the prediction model of the degree of shock is established based on the theory of model predictive control. Finally, the DCCS with adaptation for a complex driving cycle is realized by combining the feedback control and the predictive model. The presented DCCS is validated on the co-simulation platform of AMESim and Simulink. Results show that the shock during mode shifting is well controlled, thereby improving riding comfort.
2009-09-01
actuators) as well as control logic and new architectures . Also, control engineers will have to work closely with hardware designers to take advantage of...Similarly, within engine systems themselves, it is becoming necessary to shift toward distributed control architectures to enable weight-neutral...Paulitsch, Michael, “Model-Based Development And The Implications To Design Assurance And Certification”, 0- 7803-9307, IEEE, 2005. MVC , PSC, MPC 7
Boyer, Mark D.; Barton, Justin; Schuster, Eugenio; Luce, Tim C.; Ferron, John R.; Walker, Michael L.; Humphreys, David A.; Penaflor, Ben G.; Johnson, Robert D.
2013-10-01
In tokamak fusion plasmas, control of the spatial distribution profile of the toroidal plasma current plays an important role in realizing certain advanced operating scenarios. These scenarios, characterized by improved confinement, magnetohydrodynamic stability, and a high fraction of non-inductively driven plasma current, could enable steady-state reactor operation with high fusion gain. Current profile control experiments at the DIII-D tokamak focus on using a combination of feedforward and feedback control to achieve a targeted current profile during the ramp-up and early flat-top phases of the shot and then to actively maintain this profile during the rest of the discharge. The dynamic evolution of the current profile is nonlinearly coupled with several plasma parameters, motivating the design of model-based control algorithms that can exploit knowledge of the system to achieve desired performance. In this work, we use a first-principles-driven, control-oriented model of the current profile evolution in low confinement mode (L-mode) discharges in DIII-D to design a feedback control law for regulating the profile around a desired trajectory. The model combines the magnetic diffusion equations with empirical correlations for the electron temperature, resistivity, and non-inductive current drive. To improve tracking performance of the system, a nonlinear input transformation is combined with a linear-quadratic-integral (LQI) optimal controller designed to minimize a weighted combination of the tracking error and controller effort. The resulting control law utilizes the total plasma current, total external heating power, and line averaged plasma density as actuators. A simulation study was used to test the controller's performance and ensure correct implementation in the DIII-D plasma control system prior to experimental testing. Experimental results are presented that show the first-principles-driven model-based control scheme's successful rejection of input
Silicon controlled rectifier (SCR) compact modeling based on VBIC and Gummel-Poon models
Lou, Lifang; Liou, Juin J.; Dong, Shurong; Han, Yan
2009-02-01
Silicon controlled rectifier (SCR) is frequently used for electrostatic discharge (ESD) protection applications. For computer-aided design purposes, a macromodel can be constructed for such a device, but a model for the NPN and PNP bipolar transistors imbedded in the SCR is required in the macromodel development. In the paper, we use both the Vertical Bipolar Inter-Company (VBIC) and SPICE Gummel-Poon (SGP) models for these bipolar transistors and compare the perspective macromodel results. Measurements obtained from the transmission line pulsing (TLP) tester are also included to assess the suitability and pros and cons of the VBIC and SGP models for the SCR ESD modeling.
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)
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.
Liu, Kailong; Li, Kang; Zhang, Cheng
2017-04-01
Battery temperature is a primary factor affecting the battery performance, and suitable battery temperature control in particular internal temperature control can not only guarantee battery safety but also improve its efficiency. This is however challenging as current controller designs for battery charging have no mechanisms to incorporate such information. This paper proposes a novel battery charging control strategy which applies the constrained generalized predictive control (GPC) to charge a LiFePO4 battery based on a newly developed coupled thermoelectric model. The control target primarily aims to maintain the battery cell internal temperature within a desirable range while delivering fast charging. To achieve this, the coupled thermoelectric model is firstly introduced to capture the battery behaviours in particular SOC and internal temperature which are not directly measurable in practice. Then a controlled auto-regressive integrated moving average (CARIMA) model whose parameters are identified by the recursive least squares (RLS) algorithm is developed as an online self-tuning predictive model for a GPC controller. Then the constrained generalized predictive controller is developed to control the charging current. Experiment results confirm the effectiveness of the proposed control strategy. Further, the best region of heat dissipation rate and proper internal temperature set-points are also investigated and analysed.
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.
Nonlinear Dynamic Model-Based Adaptive Control of a Solenoid-Valve System
Directory of Open Access Journals (Sweden)
DongBin Lee
2012-01-01
Full Text Available In this paper, a nonlinear model-based adaptive control approach is proposed for a solenoid-valve system. The challenge is that solenoids and butterfly valves have uncertainties in multiple parameters in the nonlinear model; various kinds of physical appearance such as size and stroke, dynamic parameters including inertia, damping, and torque coefficients, and operational parameters especially, pipe diameters and flow velocities. These uncertainties are making the system not only difficult to adjust to the environment, but also further complicated to develop the appropriate control approach for meeting the system objectives. The main contribution of this research is the application of adaptive control theory and Lyapunov-type stability approach to design a controller for a dynamic model of the solenoid-valve system in the presence of those uncertainties. The control objectives such as set-point regulation, parameter compensation, and stability are supposed to be simultaneously accomplished. The error signals are first formulated based on the nonlinear dynamic models and then the control input is developed using the Lyapunov stability-type analysis to obtain the error bounded while overcoming the uncertainties. The parameter groups are updated by adaptation laws using a projection algorithm. Numerical simulation results are shown to demonstrate good performance of the proposed nonlinear model-based adaptive approach and to compare the performance of the same solenoid-valve system with a non-adaptive method as well.
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.
Chaos and Control of Game Model Based on Heterogeneous Expectations in Electric Power Triopoly
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Weizhuo Ji
2009-01-01
Full Text Available A dynamic repeated game model has been established based on heterogeneous expectations in electric power triopoly. Theoretical analysis and numerical simulation show the complexity of this model; suppose that the producers make decisions with naive expectation and bounded rationality. The straight-line stabilization chaos control method was successfully applied to the dynamic repeated game model. The results have important practical value for the producers in the electric power oligopoly.
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.
Directory of Open Access Journals (Sweden)
Huanyin Zhou
2015-07-01
Full Text Available This manuscript presents an improved control algorithm, called Dynamic Sliding Mode Control based on Multiple Models Switching Laws (DSMC-MMSL, for the control of the depth of the studied Autonomous Underwater Vehicle (AUV system, the diving plane controller of which faces disturbances arising from the coupled states. The diving plane model is strongly coupled with the state variables, such as surge speeds and course angles. To achieve the desired dynamic performance, the proposed algorithm consists of two parts: the diving plane control part and the pitch control part, which is used to avoid large pitch angles. Some direct switching control laws are used for the two parts to avoid some impulse phenomena on the control executions. The error-states exponential decay is recommended to eliminate the chattering on the sliding surface. The DSMC-MMSL controller was successfully implemented and experimentally validated with the studied AUV system designed and built by Shenyang Institute of Automation. The results of some lake trials demonstrated that the depth control performances of the AUV system were as desired, and that the AUV system was robust enough for the coupled state variables under the DSMCMMSL algorithm control.
Directory of Open Access Journals (Sweden)
Huanyin Zhou
2015-07-01
Full Text Available This manuscript presents an improved control algorithm, called Dynamic Sliding Mode Control based on Multiple Models Switching Laws (DSMC-MMSL, for the control of the depth of the studied Autonomous Underwater Vehicle (AUV system, the diving plane controller of which faces disturbances arising from the coupled states. The diving plane model is strongly coupled with the state variables, such as surge speeds and course angles. To achieve the desired dynamic performance, the proposed algorithm consists of two parts: the diving plane control part and the pitch control part, which is used to avoid large pitch angles. Some direct switching control laws are used for the two parts to avoid some impulse phenomena on the control executions. The error-states exponential decay is recommended to eliminate the chattering on the sliding surface. The DSMC-MMSL controller was successfully implemented and experimentally validated with the studied AUV system designed and built by Shenyang Institute of Automation. The results of some lake trials demonstrated that the depth control performances of the AUV system were as desired, and that the AUV system was robust enough for the coupled state variables under the DSMC-MMSL algorithm control.
Energy Technology Data Exchange (ETDEWEB)
Sandvig, J.
2009-11-15
The project's overall objective has been to use methods in model-based control and online optimization to increase industrial energy efficiency. Model-based regulation is a relatively new technology that combines knowledge of processes and systems, theoretical methods and computer processing power in intelligent, advanced control solutions and methods. The methods have so far been successfully applied in some of the largest process industries, but virtually not in small and medium-sized industries. A major reason for this is that no standard solutions have existed, and therefore it has required significant resources to develop and implement. The goal of this project is to contribute to model-based control being disseminated among the SMEs. This can be done by finding out whether it is possible to adjust and standardize the methods so that they are suitable for deployment in these segments. (ln)
Offset-Free Model Predictive Control of Open Water Channel Based on Moving Horizon Estimation
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.
Directory of Open Access Journals (Sweden)
Farzin Piltan
2013-08-01
Full Text Available This research involved developing a surgical robot assistant using an articulated PUMA robot running on a linear or nonlinear axis. The research concentrated on studying the artificial intelligence based switching computed torque controller to localization of an endoscopic tool. Results show that the switching artificial nonlinear control algorithm is capable to design a stable controller. For this system, error was used as the performance metric. Positioning of the endoscopic manipulator relative to the world coordinate frame was possible to within 0.05 inch. Error in maintaining a constant point in space is evident during repositioning however this was caused by limitations in the robot arm.
Institute of Scientific and Technical Information of China (English)
LIU Hongyi; WANG Lei; WANG Fei
2007-01-01
To precisely implement the force control of robot manipulators in an unknown environment,a control strategy based on fuzzy prediction of the reference trajectory in the impedance model is developed.The force tracking experiments are executed in an open-architecture control system with different tracking velocities,different desired forces,different contact stiffnesses and different surface figurations.The corresponding force control results are compared and analyzed.The influences of unknown parameters of the environment on the contact force are analyzed based on experimental data,and the tunings of predictive scale factors are illustrated.The experimental results show that the desired trajectory in the impedance model is predicted exactly and rapidly in the cases that the contact surface is unknown,the contact stiffness changes,and the fuzzy force control algorithm has high adaptability to the unknown environment.
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.
GOBF-ARMA based model predictive control for an ideal reactive distillation column.
Seban, Lalu; Kirubakaran, V; Roy, B K; Radhakrishnan, T K
2015-11-01
This paper discusses the control of an ideal reactive distillation column (RDC) using model predictive control (MPC) based on a combination of deterministic generalized orthonormal basis filter (GOBF) and stochastic autoregressive moving average (ARMA) models. Reactive distillation (RD) integrates reaction and distillation in a single process resulting in process and energy integration promoting green chemistry principles. Improved selectivity of products, increased conversion, better utilization and control of reaction heat, scope for difficult separations and the avoidance of azeotropes are some of the advantages that reactive distillation offers over conventional technique of distillation column after reactor. The introduction of an in situ separation in the reaction zone leads to complex interactions between vapor-liquid equilibrium, mass transfer rates, diffusion and chemical kinetics. RD with its high order and nonlinear dynamics, and multiple steady states is a good candidate for testing and verification of new control schemes. Here a combination of GOBF-ARMA models is used to catch and represent the dynamics of the RDC. This GOBF-ARMA model is then used to design an MPC scheme for the control of product purity of RDC under different operating constraints and conditions. The performance of proposed modeling and control using GOBF-ARMA based MPC is simulated and analyzed. The proposed controller is found to perform satisfactorily for reference tracking and disturbance rejection in RDC.
Runge-Kutta model-based nonlinear observer for synchronization and control of chaotic systems.
Beyhan, Selami
2013-07-01
This paper proposes a novel nonlinear gradient-based observer for synchronization and observer-based control of chaotic systems. The model is based on a Runge-Kutta model of the chaotic system where the evolution of the states or parameters is derived based on the error-square minimization. The stability and convergence conditions of observer and control methods are analyzed using a Lyapunov stability approach. In numerical simulations, the proposed observer and well-known sliding-mode observer are compared for the synchronization of a Lü chaotic system and observer-based stabilization of a Chen chaotic system. The noisy case for synchronization and parameter uncertainty case for stabilization are also considered for both observer-based methods. Copyright © 2013 ISA. Published by Elsevier Ltd. All rights reserved.
Model-based control of vortex shedding at low Reynolds numbers
Illingworth, Simon J.
2016-10-01
Model-based feedback control of vortex shedding at low Reynolds numbers is considered. The feedback signal is provided by velocity measurements in the wake, and actuation is achieved using blowing and suction on the cylinder's surface. Using two-dimensional direct numerical simulations and reduced-order modelling techniques, linear models of the wake are formed at Reynolds numbers between 45 and 110. These models are used to design feedback controllers using {H}_∞ loop-shaping. Complete suppression of shedding is demonstrated up to Re = 110—both for a single-sensor arrangement and for a three-sensor arrangement. The robustness of the feedback controllers is also investigated by applying them over a range of off-design Reynolds numbers, and good robustness properties are seen. It is also observed that it becomes increasingly difficult to achieve acceptable control performance—measured in a suitable way—as Reynolds number increases.
Design of a dynamic positioning system using model-based control
Directory of Open Access Journals (Sweden)
Asgeir J. Sørensen
1996-04-01
Full Text Available A dynamic positioning (DP system includes different control functions for automatic positioning and guidance of marine vessels by means of thruster and propeller actions. This paper describes the control functions which provide station-keeping and tracking. The DP controller is designed using model-based control, where a new modified LQG feedback controller and a model reference feedforward controller are applied. A reference model calculates appropriate reference trajectories. Since it is not desirable nor even possible to counteract the wave-frequency movement caused by first-order wave loads, the control action of the propulsion system should be produced by the low frequency part of the vessel movement caused by current, wind and second-order mean and slowly varying wave loads. A Kalman filter based state estimator and a Luenberger observer are used to compute the low-frequency feedback and feedforward control signals. Full-scale experiments with a supply vessel demonstrate the performance of the proposed controller.
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)
Study of Super-Twisting sliding mode control for U model based nonlinear system
Directory of Open Access Journals (Sweden)
Jianhua ZHANG
2016-08-01
Full Text Available The Super-Twisting control algorithm is adopted to analyze the U model based nonlinear control system in order to solve the controller design problems of non-affine nonlinear systems. The non-affine nonlinear systems are studied, the neural network approximation of the nonlinear function is performed, and the Super-Twisting control algorithm is used to control. The convergence of the Super-Twisting algorithm is proved by selecting an appropriate Lyapunov function. The Matlab simulation is carried out to verify the feasibility and effectiveness of the described method. The result shows that the output of the controlled system can be tracked in a very short time by using the designed Super-Twisting controller, and the robustness of the controlled system is significantly improved as well.
Directory of Open Access Journals (Sweden)
Abhra Roy Chowdhury
2015-05-01
Full Text Available Fish swimming demonstrates impressive speeds and exceptional characteristics in the fluid environment. The objective of this paper is to mimic undulatory swimming behaviour and its control of a body caudal fin (BCF carangiform fish in a robotic counterpart. Based on fish biology kinematics study, a 2-level behavior based distributed control scheme is proposed. The high-level control is modeled by robotic fish swimming behavior. It uses a Lighthill (LH body wave to generate desired joint trajectory patterns. Generated LH body wave is influenced by intrinsic kinematic parameters Tail-beat frequency (TBF and Caudal amplitude (CA which can be modulated to change the trajectory pattern. Parameter information is retrieved from a fish memory (cerebellum inspired brain map. This map stores operating region information on TBF and CA parameters obtained from yellow fin tuna kinematics study. Based on an environment based error feedback signal, robotic fish map selects the right parameters value showing adaptive behaviour. A finite state machine methodology has been used to model this brain-kinematic-map control. The low-level control is implemented using inverse dynamics based computed torque method (CTM with dynamic PD compensation. It tracks high-level generated and encoded patterns (trajectory for fish-tail undulation. Three types of parameter adaptation for the two chosen parameters have been shown to successfully emulate robotic fish swimming behavior. Based on the proposed control strategy joint-position and velocity tracking results are discussed. They are found to be satisfactory with error magnitudes within permissible bounds.
Gu, Guo-Ying; Gupta, Ujjaval; Zhu, Jian; Zhu, Li-Min; Zhu, Xiang-Yang
2015-07-01
In the practical applications of actuators, the control of their deformation or driving force is a key issue. Most of recent studies on dielectric elastomer actuators (DEAs) focus on issues of mechanics, physics, and material science, whereas less importance is given to the control of these soft actuators. In this paper, we underline the importance of a nonlinear dynamic model as the basis for a feedforward deformation control approach of a rubber-based DEA. Experimental evidence shows the effectiveness of the feedforward controller. The present study confirms that a DEA's trajectory can be finely controlled with a solid nonlinear dynamic model despite the presence of material nonlinearities and electromechanical coupling. The effective control of DEAs may pave the way for extensive emerging applications to soft robots.
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.
Modeling and Backstepping-based Nonlinear Control Strategy for a 6 DOF Quadrotor Helicopter
Institute of Scientific and Technical Information of China (English)
Ashfaq Ahmad Mian; Wang Daobo
2008-01-01
In this article,a nonlinear model of an underactuated six degrees of freedom (6 DOF) quadrotor helicopter is derived on the basis of the Newton-Euler formalism.The derivation comprises determining equations of the motion of the quadrotor in three dimensions andapproximating the actuation forces through the modeling of aerodynamic coefficients and electric motor dynamics.The derived modelcomposed of translatioual and rotational subsystems is dynamically unstable,so a sequential nonlinear control strategy is used.The con-trol strategy includes feedback linearization coupled with a PD controller for the translational subsystem and a backstepping-based PID nonlinear controller for the rotational subsystem of the quadrotor.The performances of the nonlinear control method are evaluated by nonlinear simulation and the results demonstrate the effectiveness of the proposed control strategy for the quadrotor helicopter inquasi-stationary flights.
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.
Model Based Control System Design Using SysML, Simulink, and Computer Algebra System
Directory of Open Access Journals (Sweden)
Takashi Sakairi
2013-01-01
Full Text Available The Systems Modeling Language (SysML is a standard, general-purpose, modeling language for model-based systems engineering (MBSE. SysML supports the specification, analysis, and design of a broad range of complex systems such as control systems. The authors demonstrate how they can integrate a SysML modeling tool (IBM Rational Rhapsody with a proprietary simulation tool (MathWorks Simulink and a Computer Algebra System (CAS to validate system specification. The integration with Simulink enables users to perform systems engineering process in a SysML model, while designing continuous control algorithms and plant behavior in Simulink, and to validate the behavior by simulating the overall composition in Simulink. The integration with a CAS enables the evaluation of mathematical constraints defined in SysML parametric diagrams. The authors also show the overall approach using a Dual Clutch Transmission (DCT and a Cruise Control System as examples.
Model-Based Control of an Aircraft Engine using an Optimal Tuner Approach
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.
Power System Stabilizer Design Based on Model Reference Robust Fuzzy Control
Directory of Open Access Journals (Sweden)
Mohammad Reza Yazdchi
2012-04-01
Full Text Available Power System Stabilizers (PSS are used to generate supplementary damping control signals for the excitation system in order to damp the Low Frequency Oscillations (LFO of the electric power system. The PSS is usually designed based on classical control approaches but this Conventional PSS (CPSS has some problems in power system control and stability enhancement. To overcome the drawbacks of CPSS, numerous techniques have been proposed in literatures. In this study a new method based on Model Reference Robust Fuzzy Control (MRRFC is considered to design PSS. In this new approach, in first an optimal PSS is designed in the nominal operating condition and then power system identification is used to obtain model reference of power system including optimal PSS. With changing system operating condition from the nominal condition, the error between obtained model reference and power system response in sent to a fuzzy controller and this fuzzy controller provides the stabilizing signal for damping power system oscillations just like PSS. In order to model reference identification a PID type PSS (PID-PSS is considered for damping electric power system oscillations. The parameters of this PID-PSS are tuned based on hybrid Genetic Algorithms (GA optimization method. The proposed MRRFC is evaluated against the CPSS at a single machine infinite bus power system considering system parametric uncertainties. The simulation results clearly indicate the effectiveness and validity of the proposed method.
Simulation and Modelling of Passivity Based Control of PMSM Under Controlled Voltage
Belabbes, Baghdad; Lousdad, Abdelkader; Meroufel, Abdelkader; Larbaoui, Ahmed
2013-09-01
The aim of the present paper is the study of the behaviour of passivity based control and difficulties due to synthesis for various operating conditions of a synchronous motor with a permanent magnets. The study takes into account the guarantee of satisfactory static and dynamic performance. It also allows the system to be insensitive to disturbances and uncertainties on the parameters. A number of estimation techniques have been developed to achieve speed and position sensorless permanent magnet synchronous motor (PMSM) drives. Most of them suffer from variation of motor parameters such as the stator resistance, stator inductance and torque constant. Also it is known that conventional linear estimators are not adaptive variations of the operating point in a nonlinear system.
Modeling and Capacitors Voltage Balancing Control of STATCOM Based on Modular Multilevel Converter
Directory of Open Access Journals (Sweden)
Milad Samady Shadlu
2016-12-01
Full Text Available Modular multilevel converter (MMC provides a new concept in a wide range of applications due to its simple topology and high reliability. In this paper, a three phase four legs modular multilevel converter is used as a compensator in a four-wire network which feeds an unbalanced and distorted custom load. The purpose is to compensate this unbalance load currents by injection suitable currents besides the capacitors voltage balancing control in individual legs. In this paper, designing of compensator current controller will be done based on a composite control model (CCM combined of average model and predictive control method. Also an independent controller has been proposed for capacitors voltage balancing whose task is to eliminate the circulating current oscillations in each leg. In order to control total energy stored in converter and also to remove the zero sequence current, two simple control schemes have been presented based on PI controller and closed loop controller, respectively. Finally simulation results have been presented in MATLAB/Simulink to confirm effectiveness and accuracy of proposed controller.
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.
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.
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.
Cheng, Longlong; Zhang, Guangju; Wan, Baikun; Hao, Linlin; Qi, Hongzhi; Ming, Dong
2009-01-01
Functional electrical stimulation (FES) has been widely used in the area of neural engineering. It utilizes electrical current to activate nerves innervating extremities affected by paralysis. An effective combination of a traditional PID controller and a neural network, being capable of nonlinear expression and adaptive learning property, supply a more reliable approach to construct FES controller that help the paraplegia complete the action they want. A FES system tuned by Radial Basis Function (RBF) Neural Network-based Proportional-Integral-Derivative (PID) model was designed to control the knee joint according to the desired trajectory through stimulation of lower limbs muscles in this paper. Experiment result shows that the FES system with RBF Neural Network-based PID model get a better performance when tracking the preset trajectory of knee angle comparing with the system adjusted by Ziegler- Nichols tuning PID model.
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.
Linear Model-Based Predictive Control of the LHC 1.8 K Cryogenic Loop
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...
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.
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.
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...
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.
Barrier Lyapunov function-based model-free constraint position control for mechanical systems
Energy Technology Data Exchange (ETDEWEB)
Han, Seong Ik; Ha, Hyun Uk; Lee, Jang Myung [Pusan National University, Busan (Korea, Republic of)
2016-07-15
In this article, a motion constraint control scheme is presented for mechanical systems without a modeling process by introducing a barrier Lyapunov function technique and adaptive estimation laws. The transformed error and filtered error surfaces are defined to constrain the motion tracking error in the prescribed boundary layers. Unknown parameters of mechanical systems are estimated using adaptive laws derived from the Lyapunov function. Then, robust control used the conventional sliding mode control, which give rise to excessive chattering, is changed to finite time-based control to alleviate undesirable chattering in the control action and to ensure finite-time error convergence. Finally, the constraint controller from the barrier Lyapunov function is designed and applied to the constraint of the position tracking error of the mechanical system. Two experimental examples for the XY table and articulated manipulator are shown to evaluate the proposed control scheme.
Model-based Robotic Dynamic Motion Control for the Robonaut 2 Humanoid Robot
Badger, Julia M.; Hulse, Aaron M.; Taylor, Ross C.; Curtis, Andrew W.; Gooding, Dustin R.; Thackston, Allison
2013-01-01
Robonaut 2 (R2), an upper-body dexterous humanoid robot, has been undergoing experimental trials on board the International Space Station (ISS) for more than a year. R2 will soon be upgraded with two climbing appendages, or legs, as well as a new integrated model-based control system. This control system satisfies two important requirements; first, that the robot can allow humans to enter its workspace during operation and second, that the robot can move its large inertia with enough precision to attach to handrails and seat track while climbing around the ISS. This is achieved by a novel control architecture that features an embedded impedance control law on the motor drivers called Multi-Loop control which is tightly interfaced with a kinematic and dynamic coordinated control system nicknamed RoboDyn that resides on centralized processors. This paper presents the integrated control algorithm as well as several test results that illustrate R2's safety features and performance.
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
present MPC for SISO systems based on ARX models combined with the first order filter. We derive expressions for the closed-loop variance of the unconstrained MPC based on a state space representation in innovation form and use these expressions to develop a tuning procedure for the regulator. We...... establish formal equivalence between GPC and state space based off-set free MPC. By simulation we demonstrate this procedure for a third order system. The offset-free ARX MPC demonstrates satisfactory set point tracking and rejection of an unmeasured step disturbance for a simulated furnace with a long time...
A general U-block model-based design procedure for nonlinear polynomial control systems
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.
Modeling and control of a flexible rotor system with AMB-based sustentation.
Arredondo, I; Jugo, J; Etxebarria, V
2008-01-01
In this work the modeling and basic control design process of a rotary flexible spindle hovered by Active Magnetic Bearings (AMB) whose good capabilities for machine-tool industry extensively treated in the literature is presented. The modeling takes into account the three main behavioral characteristics of such magnetically-levitated rotor: the rigid dynamics, the flexible dynamics and the rotating unbalanced motion. Besides, the gyroscopic coupling is also studied proving that in this case, its effects are not significant and can be neglected. Using this model, a stabilizing controller based on symmetry properties is successfully designed for the system and a complete experimental analysis of its performance is carried out. Also, the predictions of the model are compared with the actual measured experimental results on a laboratory set-up based on the MBC500 Rotor Dynamics. Afterwards, a brief study about some nonlinear behavior observed in the system and its effect over the system stability at the critical speed is included.
LMI-Based Generation of Feedback Laws for a Robust Model Predictive Control Algorithm
Acikmese, Behcet; Carson, John M., III
2007-01-01
This technical note provides a mathematical proof of Corollary 1 from the paper 'A Nonlinear Model Predictive Control Algorithm with Proven Robustness and Resolvability' that appeared in the 2006 Proceedings of the American Control Conference. The proof was omitted for brevity in the publication. The paper was based on algorithms developed for the FY2005 R&TD (Research and Technology Development) project for Small-body Guidance, Navigation, and Control [2].The framework established by the Corollary is for a robustly stabilizing MPC (model predictive control) algorithm for uncertain nonlinear systems that guarantees the resolvability of the associated nite-horizon optimal control problem in a receding-horizon implementation. Additional details of the framework are available in the publication.
An Efficient Constrained Model Predictive Control Algorithm Based on Approximate Computation
Institute of Scientific and Technical Information of China (English)
无
2002-01-01
The on-line computational burden related to model predictive control (MPC) of large-scale constrained systems hampers its real-time applications and limits it to slow dynamic process with moderate number of inputs. To avoid this, an efficient and fast algorithm based on aggregation optimization is proposed in this paper. It only optimizes the current control action at time instant k, while other future control sequences in the optimization horizon are approximated off-line by the linear feedback control sequence, so the on-line optimization can be converted into a low dimensional quadratic programming problem. Input constraints can be well handled in this scheme. The comparable performance is achieved with existing standard model predictive control algorithm. Simulation results well demonstrate its effectiveness.
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.
Nonlinear Model Predictive Control Based on a Self-Organizing Recurrent Neural Network.
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.
The control structure of team-based organizations : A diagnostic model for empowerment
Kuipers, Benjamin; de Witte, M.C.
2005-01-01
This article describes a diagnostic model for empowerment in team-based organizations that portrays four dimensions of the organization's control structure: the level of routine, the nature of expertise, the level of dependence and the line of command. The combined positions of the set of job
College Students Coping with Interpersonal Stress: Examining a Control-Based Model of Coping
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.…
Approximate queueing models for capacitated multi-stage inventory systems under base-stock control
Avsar, Zeynep Müge; Zijm, Willem H.M.
2014-01-01
A queueing analysis is presented for base-stock controlled multi-stage production-inventory systems with capacity constraints. The exact queueing model is approximated by replacing some state-dependent conditional probabilities (that are used to express the transition rates) by constants. Two
The control structure of team-based organizations : A diagnostic model for empowerment
Kuipers, Benjamin; de Witte, M.C.
2005-01-01
This article describes a diagnostic model for empowerment in team-based organizations that portrays four dimensions of the organization's control structure: the level of routine, the nature of expertise, the level of dependence and the line of command. The combined positions of the set of job regula
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.
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.
Model-based control of the temporal patterns of intracellular signaling in silico
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
Economic policy optimization based on both one stochastic model and the parametric control theory
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)
Tu, Jianwei; Lin, Xiaofeng; Tu, Bo; Xu, Jiayun; Tan, Dongmei
2014-09-01
In the process of sudden natural disasters (such as earthquake or typhoon), the active mass damper (AMD) system can reduce the structural vibration response optimally, which serves as a frequently applied but less mature vibration-reducing technology in wind and earthquake resistance of high-rise buildings. As the core of this technology, the selection of control algorithm is extremely challenging due to the uncertainty of structural parameters and the randomness of external loads. It is not necessary for the Model Reference Adaptive Control (MRAC) based on the Minimal Controller Synthesis (MCS) algorithm to know in advance the structural parameters, which produces special advantages in conditions of real-time change of system parameters, uncertain external disturbance, and the nonlinear dynamic system. This paper studies the application of the MRAC into the AMD active control system. The principle of MRAC algorithm is recommended and the dynamic model and the motion differential equation of AMD system based on MRAC is established under seismic excitation. The simulation analysis for linear and nonlinear structures when the structural stiffness is degenerated is performed under AMD system controlled by MRAC algorithm. To verify the validity of the MRAC over the AMD system, experimental tests are carried out on a linear structure and a structure with variable stiffness with the AMD system under seismic excitation on the shake table, and the experimental results are compared with those of the traditional pole assignment control algorithm.
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.
Directory of Open Access Journals (Sweden)
Cihan Turhan
2017-01-01
Full Text Available The paper presents the design and the implementation of different advanced control strategies that are applied to a nonlinear model of a thermal unit. A data-driven grey-box identification approach provided the physically–meaningful nonlinear continuous-time model, which represents the benchmark exploited in this work. The control problem of this thermal unit is important, since it constitutes the key element of passive air conditioning systems. The advanced control schemes analysed in this paper are used to regulate the outflow air temperature of the thermal unit by exploiting the inflow air speed, whilst the inflow air temperature is considered as an external disturbance. The reliability and robustness issues of the suggested control methodologies are verified with a Monte Carlo (MC analysis for simulating modelling uncertainty, disturbance and measurement errors. The achieved results serve to demonstrate the effectiveness and the viable application of the suggested control solutions to air conditioning systems. The benchmark model represents one of the key issues of this study, which is exploited for benchmarking different model-based and data-driven advanced control methodologies through extensive simulations. Moreover, this work highlights the main features of the proposed control schemes, while providing practitioners and heating, ventilating and air conditioning engineers with tools to design robust control strategies for air conditioning systems.
A new adaptive control scheme based on the interacting multiple model (IMM) estimation
Energy Technology Data Exchange (ETDEWEB)
Afshari, Hamed H.; Al-Ani, Dhafar; Habibi, Saeid [McMaster University, Hamilton (Canada)
2016-06-15
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.
Boz, Utku; Basdogan, Ipek
2015-12-01
Structural vibrations is a major cause for noise problems, discomfort and mechanical failures in aerospace, automotive and marine systems, which are mainly composed of plate-like structures. In order to reduce structural vibrations on these structures, active vibration control (AVC) is an effective approach. Adaptive filtering methodologies are preferred in AVC due to their ability to adjust themselves for varying dynamics of the structure during the operation. The filtered-X LMS (FXLMS) algorithm is a simple adaptive filtering algorithm widely implemented in active control applications. Proper implementation of FXLMS requires availability of a reference signal to mimic the disturbance and model of the dynamics between the control actuator and the error sensor, namely the secondary path. However, the controller output could interfere with the reference signal and the secondary path dynamics may change during the operation. This interference problem can be resolved by using an infinite impulse response (IIR) filter which considers feedback of the one or more previous control signals to the controller output and the changing secondary path dynamics can be updated using an online modeling technique. In this paper, IIR filtering based filtered-U LMS (FULMS) controller is combined with online secondary path modeling algorithm to suppress the vibrations of a plate-like structure. The results are validated through numerical and experimental studies. The results show that the FULMS with online secondary path modeling approach has more vibration rejection capabilities with higher convergence rate than the FXLMS counterpart.
Institute of Scientific and Technical Information of China (English)
Wu Kaiyuan; Huang Shisheng; Meng Yongmin
2005-01-01
According to the feature of arc voltage control in welding steel using pulsed MIG welding, a correction factor based double model fuzzy logic controller (FLC) was developed to realize the arc voltage control by means of arc voltage feedback.When the error of peak arc voltage was great, a coarse adjusting fuzzy logic control rules with correction factor was designed,in the controller, the peak arc voltage was controlled by the wire feeding speed by means of arc voltage feedback. When the error of peak arc voltage was small, a fine adjusting fuzzy logic control rules with correction factor was designed, in this controller, the peak arc voltage was controlled by the background time by means of arc voltage feedback. The FLC was realized in a Look-Up Table ( LUT) method. Experiments had been carried out aiming at implementing the control strategy to control the arc length change in welding process. Experimental results show that the controller proposed enables the consistency of arc length and the stabolity of arc voltage and welding process to be achieved in pulsed MIG welding process.
Design, modelling and control of a micro-positioning actuator based on magnetic shape memory alloys
Minorowicz, Bartosz; Leonetti, Giuseppe; Stefanski, Frederik; Binetti, Giulio; Naso, David
2016-07-01
This paper presents an actuator based on magnetic shape memory alloys (MSMAs) suitable for precise positioning in a wide range (up to 1 mm). The actuator is based on the spring returned operating mode and uses a Smalley wave spring to maintain the same operating parameters of a classical coil spring, while being characterized by a smaller dimension. The MSMA element inside the actuator provides a deformation when excited by an external magnetic field, but its behavior is characterized by an asymmetric and saturated hysteresis. Thus, two models are exploited in this work to represent such a non-linear behavior, i.e., the modified and generalized Prandtl-Ishlinskii models. These models are particularly suitable for control purposes due to the existence of their analytical inversion that can be easily exploited in real time control systems. To this aim, this paper investigates three closed-loop control strategies, namely a classical PID regulator, a PID regulator with direct hysteresis compensation, and a combined PID and feedforward compensation strategy. The effectiveness of both modelling and control strategies applied to the designed MSMA-based actuator is illustrated by means of experimental results.
Souza, André L. G.; Ishihara, João Y.; Ferreira, Henrique C.; Borges, Renato A.; Borges, Geovany A.
2016-12-01
The present work proposes a new approach for an antenna pointing system for satellite tracking. Such a system uses the received signal to estimate the beam pointing deviation and then adjusts the antenna pointing. The present work has two contributions. First, the estimation is performed by a Kalman filter based conical scan technique. This technique uses the Kalman filter avoiding the batch estimator and applies a mathematical manipulation avoiding the linearization approximations. Secondly, a control technique based on the model predictive control together with an explicit state feedback solution are obtained in order to reduce the computational burden. Numerical examples illustrate the results.
Neural Network Based Modeling and Analysis of LP Control Surface Allocation
Langari, Reza; Krishnakumar, Kalmanje; Gundy-Burlet, Karen
2003-01-01
This paper presents an approach to interpretive modeling of LP based control allocation in intelligent flight control. The emphasis is placed on a nonlinear interpretation of the LP allocation process as a static map to support analytical study of the resulting closed loop system, albeit in approximate form. The approach makes use of a bi-layer neural network to capture the essential functioning of the LP allocation process. It is further shown via Lyapunov based analysis that under certain relatively mild conditions the resulting closed loop system is stable. Some preliminary conclusions from a study at Ames are stated and directions for further research are given at the conclusion of the paper.
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.
Optimal control of an SIVRS epidemic spreading model with virus variation based on complex networks
Xu, Degang; Xu, Xiyang; Xie, Yongfang; Yang, Chunhua
2017-07-01
A novel SIVRS mathematical model for infectious diseases spreading is proposed and investigated in this paper. In this model virus variation factors are considered in the process of epidemic spreading based on complex networks, which can describe different contact status for different agents including the susceptible, the infectious, the variant and the recovered in a network. An optimal control problem is formulated to maximize the recovered agents with the limited resource allocation and optimal control strategies over the susceptible, the infected and the variant are investigated. Then the existence of a solution to the optimal control problem is given based on Pontryagin's Minimum Principle and modified forward backward sweep technique. Numerical simulations are provided to illustrate obtained theoretical results.
The Public Opinion Control Model Based on the Connecting Multi-Small-World-Network
Directory of Open Access Journals (Sweden)
Wen-Qi Zhong
2013-09-01
Full Text Available Based on the propagation mechanism of the rumor control, this study proposes a mode of propagation found on the information content to describe the dissemination of two opposite rumors on the same subject among crowds and sets up public opinion control model on the basis of this mode. Two opposite rumors on the same subject in our mode of propagation can respectively represent rumor and truth, so we investigate their interactions during the dissemination among crowd and simulate it in the connecting multi-small-world-network. Finally, by adjusting the factors which can affect the control effect of the model, we propose a corresponding rumor immunization strategy. Based on that, we conduct the analogy analysis of interactions of many opposite rumors on the same subject when they spread among crowds.
Directory of Open Access Journals (Sweden)
Mohammad Shahzad
2016-05-01
Full Text Available This study deals with the control of chaotic dynamics of tumor cells, healthy host cells, and effector immune cells in a chaotic Three Dimensional Cancer Model (TDCM by State Space Exact Linearization (SSEL technique based on Lie algebra. A non-linear feedback control law is designed which induces a coordinate transformation thereby changing the original chaotic TDCM system into a controlled one linear system. Numerical simulation has been carried using Mathematica that witness the robustness of the technique implemented on the chosen chaotic system.
Neural-network-based speed controller for induction motors using inverse dynamics model
Ahmed, Hassanein S.; Mohamed, Kamel
2016-08-01
Artificial Neural Networks (ANNs) are excellent tools for controller design. ANNs have many advantages compared to traditional control methods. These advantages include simple architecture, training and generalization and distortion insensitivity to nonlinear approximations and nonexact input data. Induction motors have many excellent features, such as simple and rugged construction, high reliability, high robustness, low cost, minimum maintenance, high efficiency, and good self-starting capabilities. In this paper, we propose a neural-network-based inverse model for speed controllers for induction motors. Simulation results show that the ANNs have a high tracing capability.
Imprecise Computation Based Real-time Fault Tolerant Implementation for Model Predictive Control
Institute of Scientific and Technical Information of China (English)
无
2006-01-01
Model predictive control (MPC) could not be deployed in real-time control systems for its computation time is not well defined. A real-time fault tolerant implementation algorithm based on imprecise computation is proposed for MPC,according to the solving process of quadratic programming (QP) problem. In this algorithm, system stability is guaranteed even when computation resource is not enough to finish optimization completely. By this kind of graceful degradation, the behavior of real-time control systems is still predictable and determinate. The algorithm is demonstrated by experiments on servomotor, and the simulation results show its effectiveness.
Hierarchical model-based predictive control of a power plant portfolio
DEFF Research Database (Denmark)
Edlund, Kristian; Bendtsen, Jan Dimon; Jørgensen, John Bagterp
2011-01-01
control” – becomes increasingly important as the ratio of renewable energy in a power system grows. As a consequence, tomorrow's “smart grids” require highly flexible and scalable control systems compared to conventional power systems. This paper proposes a hierarchical model-based predictive control...... design for power system portfolio control, which aims specifically at meeting these demands.The design involves a two-layer hierarchical structure with clearly defined interfaces that facilitate an object-oriented implementation approach. The same hierarchical structure is reflected in the underlying...
Visual Trajectory-Tracking Model-Based Control for Mobile Robots
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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
Green's function-based control-oriented modeling of electric field for dielectrophoresis
Gurtner, Martin; Hengster-Movric, Kristian; Hurák, Zdeněk
2017-08-01
In this paper, we propose a novel approach to obtain a reliable and simple mathematical model of dielectrophoretic force for model-based feedback micromanipulation. Any such model is expected to sufficiently accurately relate the voltages (electric potentials) applied to the electrodes to the resulting forces exerted on microparticles at given locations in the workspace. This model also has to be computationally simple enough to be used in real time as required by model-based feedback control. Most existing models involve solving two- or three-dimensional mixed boundary value problems. As such, they are usually analytically intractable and have to be solved numerically instead. A numerical solution is, however, infeasible in real time, hence such models are not suitable for feedback control. We present a novel approximation of the boundary value data for which a closed-form analytical solution is feasible; we solve a mixed boundary value problem numerically off-line only once, and based on this solution, we approximate the mixed boundary conditions by Dirichlet boundary conditions. This way, we get an approximated boundary value problem allowing the application of the analytical framework of Green's functions. The thus obtained closed-form analytical solution is amenable to real-time use and closely matches the numerical solution of the original exact problem.
Characteristics-based model predictive control of a catalytic flow reversal reactor
Energy Technology Data Exchange (ETDEWEB)
Fuxman, A.M.; Forbes, J.F.; Hayes, R.E. [Alberta Univ., Edmonton, AB (Canada). Dept. of Chemical and Materials Engineering
2007-08-15
A model-based controller for a catalytic flow reversal reactor (CFRR) was presented. The characteristics-based model predictive control (CBMPC) was used to provide greater accuracy in the prediction of process output variables as well as to ensure the maintenance of safe operating temperatures. Performance of the CBMPC was simulated in order to evaluate combustion of lean methane streams for the reduction of greenhouse gas (GHG) emissions. Dynamics of the CFRR were described using partial differential equations (PDEs) derived from mass and energy balances. The PDEs were then transformed into an equivalent lumped parameter model, which was in turn used to design the non-linear predictive controller. The prediction horizon was divided into Hp intervals during each half cycle. A constrained quadratic program was then solved to obtain an optimal input sequence. The strategy was then evaluated by applying it to a simple CFRR plant, as well as a more complex plant modelled by a dynamical-dimensional heterogenous model that incorporated the effect of a large insulation layer needed to reduce heat loss from the reactor. Results of the simulations suggested that mass extraction in a CBMPC scheme can be used to maintain safe operating conditions. It was concluded that the strategy provided good control performance for regulation and set point tracking in the presence of inlet disturbances and other changes in operating conditions. 18 refs., 1 tab., 10 figs.
Nonlinear model-based control algorithm for a distillation column using software sensor.
Jana, Amiya Kumar; Samanta, Amar Nath; Ganguly, Saibal
2005-04-01
This paper presents the design of model-based globally linearizing control (GLC) structure for a distillation process within the differential geometric framework. The model of a nonideal binary distillation column, whose characteristics were highly nonlinear and strongly interactive, is used as a real process. The classical GLC law is comprised of a transformer (input-output linearizing state feedback), a nonlinear state observer, and an external PI controller. The tray temperature based short-cut observer (TTBSCO) has been used as a state estimator within the control structure, in which all tray temperatures were considered to be measured. Accordingly, the liquid phase composition of each tray was calculated online using the derived temperature-composition correlation. In the simulation experiment, the proposed GLC coupled with TTBSCO (GLC-TTBSCO) outperformed a conventional PI controller based on servo performances with and without measurement noise as well as on regulatory behaviors. In the subsequent part, the GLC law has been synthesized in conjunction with tray temperature based reduced-order observer (GLC-TTBROO) where the distillate and bottom compositions of the distillation process have been inferred from top and bottom product temperatures respectively, which were measured online. Finally, the comparative performance of the GLC-TTBSCO and the GLC-TTBROO has been addressed under parametric uncertainty and the GLC-TTBSCO algorithm provided slightly better performance than the GLC-TTBROO. The resulting control laws are rather general and can be easily adopted for other binary distillation columns.
Constrained predictive control based on T-S fuzzy model for nonlinear systems
Institute of Scientific and Technical Information of China (English)
Su Baili; Chen Zengqiang; Yuan Zhuzhi
2007-01-01
A constrained generalized predictive control (GPC) algorithm based on the T-S fuzzy model is presented for the nonlinear system. First, a Takagi-Sugeno (T-S) fuzzy model based on the fuzzy cluster algorithm and the orthogonal least square method is constructed to approach the nonlinear system. Since its consequence is linear, it can divide the nonlinear system into a number of linear or nearly linear subsystems. For this T-S fuzzy model, a GPC algorithm with input constraints is presented.This strategy takes into account all the constraints of the control signal and its increment, and does not require the calculation of the Diophantine equations. So it needs only a small computer memory and the computational speed is high. The simulation results show a good performance for the nonlinear systems.
Petri Nets Based Modelling of Control Flow for Memory-Aid Interactive Programs in Telemedicine
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.
DEFF Research Database (Denmark)
Pierart Vásquez, Fabián Gonzalo
Gas journal bearings have been increasingly adopted in modern turbo-machinery due to their numerous indisputable advantages. They can operate at higher speed than most bearing designs, almost without noise or heat generation and in most cases, as in this work, the gas used is air which is cheap...... work, the control signal design is based on a theoretical model. This approach enables easy modifications of any of the numerous physical parameters in the system if needed. The theoretical model used is based on a modifed version of Reynolds equation where an extra term is added in order to include...... frequencies and damping ratios of the rotor-bearing system) is performed and finally to design controllers that allows improvement of the dynamic properties of the rotor-active gas bearings system and lets the systemto safely cross the critical speeds, using the theoretical model as a design tool. The results...
A 4D-Role Based Access Control Model for Multitenancy Cloud Platform
Directory of Open Access Journals (Sweden)
Jiangfeng Li
2016-01-01
Full Text Available Since more and more applications and services have been transferred from servers in the B/S architecture to cloud, user access control has become a significant part in a multitenancy cloud platform. Role based access control model makes users participate in an enterprise system as particular identities. However, in a multitenancy cloud environment, it has a high probability that the information of tenants has been leaked by using existing role based access control (RBAC model. Moreover, management problems may emerge in the multitenancy platform with the increment of the number of tenants. In this paper, a novel concept of 4D-role is presented. With a detailed definition on the concept of 4D-role, a 4D-role based multitenancy model is proposed for running various applications and services in the multitenancy cloud platform. A theoretical analysis indicates that the model has the characters of tenant isolation, role hierarchy, and administration independence. The three characters are also verified by experimental evaluation. Moreover, the evaluation results indicate that the model has a good performance in using cloud resources when large-scale users are operating in the cloud platform simultaneously.
Toward Model-Based Control of Non-linear Hydraulic Networks
DEFF Research Database (Denmark)
Tahavori, Maryamsadat; Jensen, Tom Nørgaard; Kallesøe, Carsten;
2013-01-01
consumption. To have a better understanding of leakage in WSSs, to control pressure and leakage effectively, and for optimal design of WSSs, suitable modeling is an important prerequisite. In this paper a model with the main objective of pressure control and consequently leakage reduction is presented......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...
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...... the control application. The physical system dynamics are often defined within mechanical and electrical engineering domains, with the control application residing in software and control engineering domains. Therefore, such a system can be considered multi-domain. With the constant increase in the complexity...... of such systems, caused by technological advances in all domains, new ways of approaching multi- domain system development are needed. One methodology, which excels in complexity management, is model-based development. Multidomain systems require collaborative modeling, where the physical system dynamics...
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.
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.
Comparative Study of SSVEP- and P300-Based Models for the Telepresence Control of Humanoid Robots.
Zhao, Jing; Li, Wei; Li, Mengfan
2015-01-01
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.
Li, Jian-ning; Su, Hong-ye; Wu, Zheng-guang; Chu, Jian
2013-06-01
A new stochastic switched linear model is established to describe the Zigbee-based wireless networked control system (WNCS) with both network-induced delay and packet dropout. The network-induced delay can be less or longer than one sampling period. A sufficient condition is presented for the exponentially mean square stability of the closed-loop WNCS, and corresponding state feedback controller is designed by using the augmenting technique and multi-Lyapunov approach. Then, combined with carrier sense multiple access with collision avoidance (CSMA-CA) algorithm, a method is given to choose proper parameter values. Finally, a numerical example is provided to demonstrate the effectiveness of the proposed method.
角色访问控制%Role based Access Control Model
Institute of Scientific and Technical Information of China (English)
毛碧波; 孙玉芳
2003-01-01
Role based access control (RBAC)was proposed in 70's, and prevailed in 90's, and then Sandhu etc pro-posed formal RBAC model. Now RBAC is attracting increasing attention, and many governmental and commercial or-ganizations have adopted it, its importance is more and more apparent. In this paper we illuminates the distinctionsand similarities of role and user groups, and based the model that was proposed by Sandhu, we examine the relation-ship of role hierarchies and role constraints and formally describes that, and explain the most important part of roleconstraints ,which is separation of duties.
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.
Rajapakse, G.; Jayasinghe, S. G.; Fleming, A.; Shahnia, F.
2017-07-01
Australia’s extended coastline asserts abundance of wave and tidal power. The predictability of these energy sources and their proximity to cities and towns make them more desirable. Several tidal current turbine and ocean wave energy conversion projects have already been planned in the coastline of southern Australia. Some of these projects use air turbine technology with air driven turbines to harvest the energy from an oscillating water column. This study focuses on the power take-off control of a single stage unidirectional oscillating water column air turbine generator system, and proposes a model predictive control-based speed controller for the generator-turbine assembly. The proposed method is verified with simulation results that show the efficacy of the controller in extracting power from the turbine while maintaining the speed at the desired level.
Directory of Open Access Journals (Sweden)
Abhra Roy Chowdhury
2015-05-01
Full Text Available Fish swimming demonstrates impressive speeds and exceptional characteristics in the fluid environment. The objective of this paper is to mimic undulatory swimming behaviour and its control of a body caudal fin (BCF carangiform fish in a robotic counterpart. Based on fish biology kinematics study, a 2-level behavior based distributed control scheme is proposed. The high-level control is modeled by robotic fish swimming behavior. It uses a Lighthill (LH body wave to generate desired joint trajectory patterns. Generated LH body wave is influenced by intrinsic kinematic parameters Tail-beat frequency (TBF and Caudal amplitude (CA which can be modulated to change the trajectory pattern. Parameter information is retrieved from a fish memory (cerebellum inspired brain map. This map stores operating region information on TBF and CA parameters obtained from yellow fin tuna kinematics study. Based on an environment based error feedback signal, robotic fish map selects the right parameter/s value showing adaptive behaviour. A finite state machine methodology has been used to model this brain-kinematic-map control. The low-level control is implemented using inverse dynamics based computed torque method (CTM with dynamic PD compensation. It tracks high-level generated and encoded patterns (trajectory for fish-tail undulation. Three types of parameter adaptation for the two chosen parameters have been shown to successfully emulate robotic fish swimming behavior. Based on the proposed control strategy joint-position and velocity tracking results are discussed. They are found to be satisfactory with error magnitudes within permissible bounds.
Shock Position Control for Mode Transition in a Turbine Based Combined Cycle Engine Inlet Model
Csank, Jeffrey T.; Stueber, Thomas J.
2013-01-01
A dual flow-path inlet for a turbine based combined cycle (TBCC) propulsion system is to be tested in order to evaluate methodologies for performing a controlled inlet mode transition. Prior to experimental testing, simulation models are used to test, debug, and validate potential control algorithms which are designed to maintain shock position during inlet disturbances. One simulation package being used for testing is the High Mach Transient Engine Cycle Code simulation, known as HiTECC. This paper discusses the development of a mode transition schedule for the HiTECC simulation that is analogous to the development of inlet performance maps. Inlet performance maps, derived through experimental means, describe the performance and operability of the inlet as the splitter closes, switching power production from the turbine engine to the Dual Mode Scram Jet. With knowledge of the operability and performance tradeoffs, a closed loop system can be designed to optimize the performance of the inlet. This paper demonstrates the design of the closed loop control system and benefit with the implementation of a Proportional-Integral controller, an H-Infinity based controller, and a disturbance observer based controller; all of which avoid inlet unstart during a mode transition with a simulated disturbance that would lead to inlet unstart without closed loop control.
Directory of Open Access Journals (Sweden)
Xiaoyi Wang
2015-01-01
Full Text Available In wastewater treatment plants (WWTPs, the dissolved oxygen is the key variable to be controlled in bioreactors. In this paper, linear active disturbance rejection control (LADRC is utilized to track the dissolved oxygen concentration based on benchmark simulation model number 1 (BSM1. Optimal LADRC parameters tuning approach for wastewater treatment processes is obtained by analyzing and simulations on BSM1. Moreover, by analyzing the estimation capacity of linear extended state observer (LESO in the control of dissolved oxygen, the parameter range of LESO is acquired, which is a valuable guidance for parameter tuning in simulation and even in practice. The simulation results show that LADRC can overcome the disturbance existing in the control of wastewater and improve the tracking accuracy of dissolved oxygen. LADRC provides another practical solution to the control of WWTPs.
Feedback Scheduling of Model-based Networked Control Systems with Flexible Workload
Institute of Scientific and Technical Information of China (English)
Xian-Ming Tang; Jin-Shou Yu
2008-01-01
In this paper, a novel control structure called feedback scheduling of model-based networked control systems is proposed to cope with a flexible network load and resource constraints. The state update time is adjusted according to the real-time network congestion situation. State observer is used under the situation where the state of the controlled plant could not be acquired. The stability criterion of the proposed structure is proved with time-varying state update time. On the basis of the stability of the novel system structure, the compromise between the control performance and the network utilization is realized by using feedback scheduler.Examples are provided to show the advantage of the proposed control structure.
Energy Technology Data Exchange (ETDEWEB)
Uchida, Hiroaki [Kisarazu National College of Technology, Kisarazu, Chiba (Japan); Nonami, Kenzo; Yanai, Takaaki [Chiba Univ. (Japan). Faculty of Engineering; Iguchi, Yoshihiko; Huang Qing Jiu [Chiba Univ. (Japan)
2000-06-01
It is considered that locomotion robots are aggressive under the circumstances where human hardly work, for example, in the nuclear power plant, in the bottom of the sea and on a planet. The injury and the fault of the robot might occur frequently under those circumstances. It is very important problem that the robot can realize the walking with the fault. This is very difficult problem for biped and quadruped robot to realize a stable walking in the case that actuator or sensor is broken. And, in walking of mammal, gait pattern is generated by neural oscillator existing in the spinal cord. In the case that a lower neural system is injured, mammal realize a walking by a higher neural system. Thus, mammal has a self renovation function. In this study, in order to realize the stable walking of the quadruped robot with fault, we discuss the control method with self renovation function for the fault of the decentralized controller and the angular sensor. First, we design the centralized controller of one leg by sliding mode control for the fault of decentralized controller. Second, Sky Hook Suspension Control is applied for the fault of the angular sensor. The proposed methods are verified by 3D simulations by CAD and experiments. (author)
Pressure Model of Control Valve Based on LS-SVM with the Fruit Fly Algorithm
Directory of Open Access Journals (Sweden)
Huang Aiqin
2014-07-01
Full Text Available Control valve is a kind of essential terminal control component which is hard to model by traditional methodologies because of its complexity and nonlinearity. This paper proposes a new modeling method for the upstream pressure of control valve using the least squares support vector machine (LS-SVM, which has been successfully used to identify nonlinear system. In order to improve the modeling performance, the fruit fly optimization algorithm (FOA is used to optimize two critical parameters of LS-SVM. As an example, a set of actual production data from a controlling system of chlorine in a salt chemistry industry is applied. The validity of LS-SVM modeling method using FOA is verified by comparing the predicted results with the actual data with a value of MSE 2.474 × 10−3. Moreover, it is demonstrated that the initial position of FOA does not affect its optimal ability. By comparison, simulation experiments based on PSO algorithm and the grid search method are also carried out. The results show that LS-SVM based on FOA has equal performance in prediction accuracy. However, from the respect of calculation time, FOA has a significant advantage and is more suitable for the online prediction.
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.
Flatness-based adaptive fuzzy control of an autonomous submarine model
Rigatos, Gerasimos; Siano, Pierluigi; Raffo, Guilherme
2015-12-01
The article presents a differential flatness theory-based method for adaptive control of autonomous submarines. A proof is provided about the differential flatness properties of the submarine's model (having as state variables the vessel's depth and its pitch angle). This also means that all its state variables and its control inputs can be written as differential functions of the flat output. Making use of its differential flatness features, the submarine's dynamic model is transformed into the multivariable linear canonical (Brunovsky) form. In the transformed model, the control inputs consist of unknown nonlinear parts, which are identified with the use of neurofuzzy approximators. The learning rate for these estimators is determined by the requirement the first derivative of the closed-loop's Lyapunov function to be a negative one. Furthermore, with the use of Lyapunov stability analysis it is proven that an H-infinity tracking performance is succeeded for the feedback control loop. This implies enhanced robustness to model uncertainty and to external perturbations. Simulation experiments are carried out to further confirm the efficiency of the proposed adaptive fuzzy control scheme.
Bilinear Approximate Model-Based Robust Lyapunov Control for Parabolic Distributed Collectors
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.
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.
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...... 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...
Quality Control of ARGO Data Based on Climatological T-S Models
Institute of Scientific and Technical Information of China (English)
纪风颖; 林绍花
2004-01-01
By implementing the ARGO program, a large number of T-S profiles can be observed in the world ocean. However, it is very difficult to examine changes of the sensitivity of the sensors equipped at the ARGO floats, because it is difficult to understand their condition in the sea and the reliability of the data. Quality control must be done in order to avoid the wrong conclusion deduced from the wrong data.One of the realistic methods for quality control of the ARGO data is the comparison with the local climatology. High quality climatological T-S models in northwest Pacific have been built based on the Nansen bottle data and CTD data for the quality control in NMDIS. The models are used to check the ARGO data in this area and have got good result.
Quality Prediction and Control of Reducing Pipe Based on EOS-ELM-RPLS Mathematics Modeling Method
Directory of Open Access Journals (Sweden)
Dong Xiao
2014-01-01
Full Text Available The inspection of inhomogeneous transverse and longitudinal wall thicknesses, which determines the quality of reducing pipe during the production of seamless steel reducing pipe, is lags and difficult to establish its mechanism model. Aiming at the problems, we proposed the quality prediction model of reducing pipe based on EOS-ELM-RPLS algorithm, which taking into account the production characteristics of its time-varying, nonlinearity, rapid intermission, and data echelon distribution. Key contents such as analysis of data time interval, solving of mean value, establishment of regression model, and model online prediction were introduced and the established prediction model was used in the quality prediction and iteration control of reducing pipe. It is shown through experiment and simulation that the prediction and iteration control method based on EOS-ELM-RPLS model can effectively improve the quality of steel reducing pipe, and, moreover, its maintenance cost was low and it has good characteristics of real time, reliability, and high accuracy.
Feedback control scheme of traffic jams based on the coupled map car-following model
Zhou, Tong; Sun, Di-Hua; Zhao, Min; Li, Hua-Min
2013-09-01
Based on the pioneering work of Konishi et al. [Phys. Rev. E (1999) 60 4000], a new feedback control scheme is presented to suppress traffic jams based on the coupled map car-following model under the open boundary condition. The effect of the safe headway on the traffic system is considered. According to the control theory, the condition under which traffic jams can be suppressed is analyzed. The results are compared with the previous results concerning congestion control. The simulations show that the suppression performance of our scheme on traffic jams is better than those of the previous schemes, although all the schemes can suppress traffic jams. The simulation results are consistent with theoretical analyses.
Energy Technology Data Exchange (ETDEWEB)
Kohler, Christian [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
2012-04-01
Complex glazing systems such as venetian blinds, fritted glass and woven shades require more detailed optical and thermal input data for their components than specular non light-redirecting glazing systems. Various methods for measuring these data sets are described in this paper. These data sets are used in multiple simulation tools to model the thermal and optical properties of complex glazing systems. The output from these tools can be used to generate simplified rating values or as an input to other simulation tools such as whole building annual energy programs, or lighting analysis tools. I also describe some of the challenges of creating a rating system for these products and which factors affect this rating. A potential future direction of simulation and building operations is model based predictive controls, where detailed computer models are run in real-time, receiving data for an actual building and providing control input to building elements such as shades.
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.
Controlling chaos in ecology: from deterministic to individual-based models.
Solé, R V; Gamarra, J G; Ginovart, M; López, D
1999-11-01
The possibility of chaos control in biological systems has been stimulated by recent advances in the study of heart and brain tissue dynamics. More recently, some authors have conjectured that such a method might be applied to population dynamics and even play a nontrivial evolutionary role in ecology. In this paper we explore this idea by means of both mathematical and individual-based simulation models. Because of the intrinsic noise linked to individual behavior, controlling a noisy system becomes more difficult but, as shown here, it is a feasible task allowed to be experimentally tested.
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.
Characteristic model based control of the X-34 reusable launch vehicle in its climbing phase
Institute of Scientific and Technical Information of China (English)
MENG Bin; WU HongXin; LIN ZongLi; LI Guo
2009-01-01
In this paper,a characteristic model based longitudinal control design for the trans-aerosphere vehicle X-34 In its transonic and hypersonic climbing phase is proposed.The design is based on the dynamic characteristics of the vehicle and the curves it is to track in this climbing phase.Through a detailed analysis of the aerodynamics and vehicle dynamics during this climbing phase,an explicit description of the tracking curve for the flight path angle is derived.On the basis of this tracking curve,the tracking curves for the two short-period variables,the angle of attack and the pitch rate,are designed.An all-coefficient adaptive controller is then designed,based on the characteristic modeling,to cause these two short-period variables to follow their respective tracking curves.The proposed design does not require multiple working points,making the design procedure simple.Numerical simulation is performed to validate the performance of the controller.The simulation results Indicate that the resulting control law ensures that the vehicle climbs up successfully under the restrictions on the pitch angle and overloading.
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.
PERFORMANCE EVALUATION FOR DAMPING CONTROLLERS OF POWER SYSTEMS BASED ON MULTI-AGENT MODELS
Institute of Scientific and Technical Information of China (English)
Ancheng XUE; Yiguang HONG
2009-01-01
This paper proposes a multi-layer multi-agent model for the performance evaluation of power systems, which is different from the existing multi-agent ones. To describe the impact of the structure of the networked power system, .the proposed model consists of three kinds of agents that form three layers: control agents such as the generators and associated controllers, information agents to exchange the information based on the wide area measurement system (WAMS) or transmit control signals to the power system stabilizers (PSSs), and network-node agents such as the generation nodes and load nodes connected with transmission lines. An optimal index is presented to evaluate the performance of damping controllers to the system's inter-area oscillation with respect to the information-layer topology.Then, the authors show that the inter-area information exchange is more powerful than the exchange within a given area to control the inter-area low frequency oscillation based on simulation analysis.
Performance-based parameter tuning method of model-driven PID control systems.
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.
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.
Feedback control for car following model based on two-lane traffic flow
Ge, Hong-xia; Meng, Xiang-pei; Zhu, Hui-bing; Li, Zhi-Peng
2014-08-01
In the paper, two-lane traffic flow considering lane changing behaviors has been discussed based on the control theory, and the friction interference which is from the neighbor lane has been taken into account. By using the control method, the stability condition is derived. The feedback signals, which include vehicular information from both lanes, acting on the two-lane traffic system have been introduced into the Full Velocity Difference car-following model. In the end, simulations are conducted to examine the validity and reasonability of the control method. It is proven that lane changing behaviors can aggravate the traffic perturbation. The traffic flow congestion could be suppressed by using the control method and the simulation results are in good agreement with the theoretical analysis.
Neuro-fuzzy and model-based motion control for mobile manipulator among dynamic obstacles
Institute of Scientific and Technical Information of China (English)
无
2003-01-01
This paper focuses on autonomous motion control of a nonholonomic platform with a robotic arm, which is called mobile manipulator. It serves in transportation of loads in imperfectly known industrial environments with unknown dynamic obstacles. A union of both procedures is used to solve the general problems of collision-free motion. The problem of collision-free motion for mobile manipulators has been approached from two directions, Planning and Reactive Control. The dynamic path planning can be used to solve the problem of locomotion of mobile platform, and reactive approaches can be employed to solve the motion planning of the arm. The execution can generate the commands for the servo-systems of the robot so as to follow a given nominal trajectory while reacting in real-time to unexpected events. The execution can be designed as an Adaptive Fuzzy Neural Controller. In real world systems, sensor-based motion control becomes essential to deal with model uncertainties and unexpected obstacles.
Model-based evaluation of an on-line control strategy for SBRs based on OUR and ORP measurements.
Corominas, Ll; Sin, G; Puig, S; Traore, A; Balaguer, M; Colprim, J; Vanrolleghem, P A
2006-01-01
Application of control strategies for existing wastewater treatment technologies becomes necessary to meet ever-stricter effluent legislations and reduce the associated treatment costs. In the case of SBR technology, controlling the phase scheduling is one of the key aspects of SBR operation. In this study a calibrated mechanistic model based on the ASM1 was used to evaluate an on-line control strategy for the SBR phase-scheduling and compare it with the SBR's performance using no control strategy. To evaluate the performance, reference indices relating to the effluent quality, the required energy for aeration and the treated wastewater volume were used. The results showed that it is possible to maintain optimal SBR performance in the studied system at minimal costs by on-line control of the length of the aerobic and anoxic phases.
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...
The Stability Analysis for an Extended Car Following Model Based on Control Theory
Ge, Hong-Xia; Meng, Xiang-Pei; Zhu, Ke-Qiang; Cheng, Rong-Jun
2014-08-01
A new method is proposed to study the stability of the car-following model considering traffic interruption probability. The stability condition for the extended car-following model is obtained by using the Lyapunov function and the condition for no traffic jam is also given based on the control theory. Numerical simulations are conducted to demonstrate and verify the analytical results. Moreover, numerical simulations show that the traffic interruption probability has an influence on driving behavior and confirm the effectiveness of the method on the stability of traffic flow.
Model-Based Control using Model and Mechanization Fusion Techniques for Image-Aided Navigation
2009-03-01
sized helicopter, LQG control has also been utilized in controlling the same type of vehicle. Zhe Jiang, Jianda Han, Yuechao Wang , and Qi Song, from the...Han J. Wang Y., Z. and Q. Song. “Enhanced LQR Control for Unmanned Helicopter in Hover”. Proceedings of Systems and Control in Aerospace and As
Takagi-Sugeno fuzzy-model-based fault detection for networked control systems with Markov delays.
Zheng, Ying; Fang, Huajing; Wang, Hua O
2006-08-01
A Takagi-Sugeno (T-S) model is employed to represent a networked control system (NCS) with different network-induced delays. Comparing with existing NCS modeling methods, this approach does not require the knowledge of exact values of network-induced delays. Instead, it addresses situations involving all possible network-induced delays. Moreover, this approach also handles data-packet loss. As an application of the T-S-based modeling method, a parity-equation approach and a fuzzy-observer-based approach for fault detection of an NCS were developed. An example of a two-link inverted pendulum is used to illustrate the utility and viability of the proposed approaches.
A model for family-based case–control studies of genetic imprinting and epistasis
Li, Xin; Sui, Yihan; Liu, Tian; Wang, Jianxin; Li, Yongci; Lin, Zhenwu; Hegarty, John; Koltun, Walter A.; Wang, Zuoheng
2014-01-01
Genetic imprinting, or called the parent-of-origin effect, has been recognized to play an important role in the formation and pathogenesis of human diseases. Although the epigenetic mechanisms that establish genetic imprinting have been a focus of many genetic studies, our knowledge about the number of imprinting genes and their chromosomal locations and interactions with other genes is still scarce, limiting precise inference of the genetic architecture of complex diseases. In this article, we present a statistical model for testing and estimating the effects of genetic imprinting on complex diseases using a commonly used case–control design with family structure. For each subject sampled from a case and control population, we not only genotype its own single nucleotide polymorphisms (SNPs) but also collect its parents’ genotypes. By tracing the transmission pattern of SNP alleles from parental to offspring generation, the model allows the characterization of genetic imprinting effects based on Pearson tests of a 2 × 2 contingency table. The model is expanded to test the interactions between imprinting effects and additive, dominant and epistatic effects in a complex web of genetic interactions. Statistical properties of the model are investigated, and its practical usefulness is validated by a real data analysis. The model will provide a useful tool for genome-wide association studies aimed to elucidate the picture of genetic control over complex human diseases. PMID:23887693
Directory of Open Access Journals (Sweden)
Naohiro eTakemura
2015-12-01
Full Text Available In human reach-to-grasp movement, visual occlusion of a target object leads to a larger peak grip aperture compared to conditions where online vision is available. However, no previous computational and neural network models for reach-to-grasp movement explain the mechanism of this effect. We simulated the effect of online vision on the reach-to-grasp movement by proposing a computational control model based on the hypothesis that the grip aperture is controlled to compensate for both motor variability and sensory uncertainty. In this model, the aperture is formed to achieve a target aperture size that is sufficiently large to accommodate the actual target; it also includes a margin to ensure proper grasping despite sensory and motor variability. To this end, the model considers: i the variability of the grip aperture, which is predicted by the Kalman filter, and ii the uncertainty of the object size, which is affected by visual noise. Using this model, we simulated experiments in which the effect of the duration of visual occlusion was investigated. The simulation replicated the experimental result wherein the peak grip aperture increased when the target object was occluded, especially in the early phase of the movement. Both predicted motor variability and sensory uncertainty play important roles in the online visuomotor process responsible for grip aperture control.
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.
A model of quality control based on recycling economy and sustainable manufacture
Institute of Scientific and Technical Information of China (English)
Chen Xiangyu; Liang Gongqian; Ma Shining
2006-01-01
People currently pay attention to a hotspot problem that how industrial production is evaluated and controlled based on sustainable development theory. Quality is one of the important indexes. Two mainstream theories guide us to realize the industrial sustainable development,: mainly the circular economy and sustainable manufacturing are introduced.The basic characteristics of the sustainable manufacturing are introduced, and that quality management is important contents of sustainable development is indicated. Based on circular economy and sustainable manufacture theories, the drawbacks in the existing quality management models are analyzed. The requests that satisfy the big system "environment - society - economy" are summarized to build up a model. A Chinese traditional cultural principle is applied and the relevant contents are sublimated as the platform to set up the model. The new quality management concept models are put forward "T- D- R" three-dimensional structures and "ecological quality loop" model, from which the new quality concepts are formed. The paper elaborates the contents and the process of setting up the models. The big quality problems of the system can be handled by the new quality concept and model that are validated in practice.
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
Directory of Open Access Journals (Sweden)
Wang Fei
2017-01-01
Full Text Available To achieve rapid automatic grinding of workpieces’ inner-surface by industrial robot, a rapid translational detection strategy of workpieces’ inner-surface and fuzzy force control algorithm of grinding are proposed in this paper. The rapid translational detection strategy introduces a way to establish an inner-surface’s model quickly by recording key points of the axial section contour which reflects big curvature changes of the contour. The established model is feasible but imprecision. The force control algorithm is based on impedance model. To promote adaptability to the imprecision of the established inner-surface’s model, a fuzzy adjusting strategy is introduced in the force control algorithm. By adopting an adjusting factor, which determined by force response and a fuzzy logic, the strategy can adjust the reference trajectory of impedance model in time. Taking advantage of proposed detection and force control method, grinding experiments shows that the contact normal force maintains approximately constant, the relative mean error is within 6.5%, and the material removal thickness of the inner-surface is approximately consistent. The proposed strategy’s feasibility is verified.
Computer-Aided Design Methods for Model-Based Nonlinear Engine Control Systems Project
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...
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.
A Model-based Framework for Risk Assessment in Human-Computer Controlled Systems
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.
Energy efficient model based algorithm for control of building HVAC systems.
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.
Linear Parameter Varying Model Identification for Control of Rotorcraft-based UAV
Budiyono, Agus
2008-01-01
A rotorcraft-based unmanned aerial vehicle exhibits more complex properties compared to its full-size counterparts due to its increased sensitivity to control inputs and disturbances and higher bandwidth of its dynamics. As an aerial vehicle with vertical take-off and landing capability, the helicopter specifically poses a difficult problem of transition between forward flight and unstable hover and vice versa. The LPV control technique explicitly takes into account the change in performance due to the real-time parameter variations. The technique therefore theoretically guarantees the performance and robustness over the entire operating envelope. In this study, we investigate a new approach implementing model identification for use in the LPV control framework. The identification scheme employs recursive least square technique implemented on the LPV system represented by dynamics of helicopter during a transition. The airspeed as the scheduling of parameter trajectory is not assumed to vary slowly. The exclu...
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.
Reference model based consensus control of second-order multi-agent systems
Institute of Scientific and Technical Information of China (English)
Li Jian-Zhen
2011-01-01
This paper deals with the consensus problem of multi-agent systems with second-order dynamics. The objective is to design algorithms such that all agents will have same positions and velocities. First, a reference model based consensus algorithm is proposed. It is proved that the consensus can be achieved if the communication graph has a spanning tree. Different from most of the consensus algorithms proposed in the literature, the parameters of the control laws are different among agents. Therefore, each agent can design its control law independently. Secondly, it gives a consensus algorithm for the case that the velocities of the agents are not available. Thirdly, the effectiveness of the input delay and the communication delay is considered. It shows that consensus can be achieved if the input delay of every agent is smaller than a bound related to parameters in its control law. Finally, some numerical examples are given to illustrate the proposed results.
DEFF Research Database (Denmark)
Abd.Hamid, Mohd-Kamaruddin; Sin, Gürkan; Gani, Rafiqul
2010-01-01
In this paper, a novel systematic model-based methodology for performing integrated process design and controller design (IPDC) for chemical processes is presented. The methodology uses a decomposition method to solve the IPDC typically formulated as a mathematical programming (optimization...... with constraints) problem. Accordingly the optimization problem is decomposed into four sub-problems: (i) pre-analysis, (ii) design analysis, (iii) controller design analysis, and (iv) final selection and verification, which are relatively easier to solve. The methodology makes use of thermodynamic-process...... insights and the reverse design approach to arrive at the final process design–controller design decisions. The developed methodology is illustrated through the design of: (a) a single reactor, (b) a single separator, and (c) a reactor–separator-recycle system and shown to provide effective solutions...
Directory of Open Access Journals (Sweden)
Özgü CAN
2010-02-01
Full Text Available As computer technologies become pervasive, the need for access control mechanisms grow. The purpose of an access control is to limit the operations that a computer system user can perform. Thus, access control ensures to prevent an activity which can lead to a security breach. For the success of Semantic Web, that allows machines to share and reuse the information by using formal semantics for machines to communicate with other machines, access control mechanisms are needed. Access control mechanism indicates certain constraints which must be achieved by the user before performing an operation to provide a secure Semantic Web. In this work, unlike traditional access control mechanisms, an "Ontology Based Access Control" mechanism has been developed by using Semantic Web based policies. In this mechanism, ontologies are used to model the access control knowledge and domain knowledge is used to create policy ontologies.
CystiSim – An Agent-Based Model for Taenia solium Transmission and Control
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
CystiSim - An Agent-Based Model for Taenia solium Transmission and Control.
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
Application of Nonlinear Predictive Control Based on RBF Network Predictive Model in MCFC Plant
Institute of Scientific and Technical Information of China (English)
CHEN Yue-hua; CAO Guang-yi; ZHU Xin-jian
2007-01-01
This paper described a nonlinear model predictive controller for regulating a molten carbonate fuel cell (MCFC). A detailed mechanism model of output voltage of a MCFC was presented at first. However, this model was too complicated to be used in a control system. Consequently, an off line radial basis function (RBF) network was introduced to build a nonlinear predictive model. And then, the optimal control sequences were obtained by applying golden mean method. The models and controller have been realized in the MATLAB environment. Simulation results indicate the proposed algorithm exhibits satisfying control effect even when the current densities vary largely.
T-S Fuzzy Model Based Control Strategy for the Networked Suspension Control System of Maglev Train
2015-01-01
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 netwo...
Shaviv, Avi; Raban, Smadar; Zaidel, Elina
2003-05-15
A statistically based model for describing the release from a population of polymer coated controlled release fertilizer (CRF) granules by the diffusion mechanism was constructed. The model is based on a mathematical-mechanistic description of the release from a single granule of a coated CRF accounting for its complex and nonlinear nature. The large variation within populations of coated CRFs poses the need for a statistically based approach to integrate over the release from the individual granules within a given population for which the distribution and range of granule radii and coating thickness are known. The model was constructed and verified using experimentally determined parameters and release curves of polymer-coated CRFs. A sensitivity analysis indicated the importance of water permeability in controlling the lag period and that of solute permeability in governing the rate of linear release and the total duration of the release. Increasing the mean values of normally distributed granule radii or coating thickness, increases the lag period and the period of linear release. The variation of radii and coating thickness, within realistic ranges, affects the release only when the standard deviation is very large or when water permeability is reduced without affecting solute permeability. The model provides an effective tool for designing and improving agronomic and environmental effectiveness of polymer-coated CRFs.
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.
Adaptive and model-based control theory applied to convectively unstable flows
Fabbiane, N; Bagheri, S; Henningson, D S
2014-01-01
Research on active control for the delay of laminar-turbulent transition in boundary layers has made a significant progress in the last two decades, but the employed strategies have been many and dispersed. Using one framework, we review model-based techniques, such as linear-quadratic regulators, and model-free adaptive methods, such as least-mean square filters. The former are supported by a elegant and powerful theoretical basis, whereas the latter may provide a more practical approach in the presence of complex disturbance environments, that are difficult to model. We compare the methods with a particular focus on efficiency, practicability and robustness to uncertainties. Each step is exemplified on the one-dimensional linearized Kuramoto-Sivashinsky equation, that shows many similarities with the initial linear stages of the transition process of the flow over a flat plate. Also, the source code for the examples are provided.
Directory of Open Access Journals (Sweden)
D. C. Tsamatsoulis
2014-03-01
Full Text Available Based on a dynamical model of the grinding process in closed circuit mills, efficient efforts have been made to optimize PID controllers of cement milling. The process simulation is combined with an autoregressive model of the errors between the actual process values and the computed ones. Long term industrial data have been used to determine the model parameters. The data include grinding of various cement types. The M - Constrained Integral Gain Optimization (MIGO loop shaping method is utilized to determine PID sets satisfying a certain robustness constraint. The maximum sensitivity is considered as such a criterion. Both dynamical parameters and PID sets constitute the inputs of a detailed simulator which involves all the main process characteristics. The simulation is applied over all the PID sets aiming to find the parameter region that provides the minimum integral of absolute error, which functions as a performance criterion. For each cement type a PID set is selected and put in operation in a closed circuit cement mill. The performance of the regulation is evaluated after a sufficient time period, concluding that the developed design combining criteria of both robustness and performance leads to PID controllers of high efficiency.
Temperature-based control of an anaerobic reactor using a multi-model observer-based estimator.
Morel, Emmanuel; Tartakovsky, Boris; Perrier, Michel; Guiot, Serge R
2007-02-01
This study presents a temperature-based control strategy for the stabilization of an anaerobic reactor during organic overloads. To prove feasibility of the proposed approach the rate of methane production was followed in batch activity tests and reactor runs during mesophilic-thermophilic transitions. Within the first 0.25-6 h of temperature augmentation, an increase in the rate of methane production was observed with higher rates measured under thermophilic (above 40 degrees C) conditions. However, 24 h after startup both in batch tests and reactor runs, the rate of methane production under thermophilic conditions was inferior to that under optimal mesophilic conditions (35 degrees C). Following these results, a control strategy based on short-term augmentation of the reactor temperature was proposed and tested in a 10 L UASB reactor. The control strategy employed a multi-model observer-based estimator to stabilize the effluent COD concentration during organic overloads. The temperature-based control resulted in an increased methanization rate and improved reactor stability overall.
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...
Institute of Scientific and Technical Information of China (English)
无
2010-01-01
In this paper,a new model with a total amount control target of allowable water withdrawal based on initial water right is built for the implementation of initial water right allocation scheme as well as unified allocation for allowable water withdrawal and sewage discharge.The model couples the water allocation simulation model and the computational model of permissible pol-lution bearing capacity.In view of the model complexity,a new technology which synthesizes system simulation,iterative reservoir turns and intelligent computation is proposed to improve the operability of allocation scheme and computational efficiency.Taking the Beijiang River Basin in the Pearl River Basin as an example,the study explains the model establishment,solution and application,and draws an optimized operation graph of large-scale reservoirs.The study also obtains a long-term operation strategy of river basin water resources system,the allocation schemes of allowable water withdrawal and sewage discharge in a typical year and the flow hydrographs of trans-boundary sections.The validity of the model and the allocation rationality are analyzed as well.
Energy Technology Data Exchange (ETDEWEB)
Xue, Yaosuo [ORNL
2016-01-01
The matrix converter solid state transformer (MC-SST), formed from the back-to-back connection of two three-to-single-phase matrix converters, is studied for use in the interconnection of two ac grids. The matrix converter topology provides a light weight and low volume single-stage bidirectional ac-ac power conversion without the need for a dc link. Thus, the lifetime limitations of dc-bus storage capacitors are avoided. However, space vector modulation of this type of MC-SST requires to compute vectors for each of the two MCs, which must be carefully coordinated to avoid commutation failure. An additional controller is also required to control power exchange between the two ac grids. In this paper, model predictive control (MPC) is proposed for an MC-SST connecting two different ac power grids. The proposed MPC predicts the circuit variables based on the discrete model of MC-SST system and the cost function is formulated so that the optimal switch vector for the next sample period is selected, thereby generating the required grid currents for the SST. Simulation and experimental studies are carried out to demonstrate the effectiveness and simplicity of the proposed MPC for such MC-SST-based grid interfacing systems.
A new model of the harmonic control based on Hadamard product
Institute of Scientific and Technical Information of China (English)
Xinjin LIU; Yun ZOU; Xiefei YAN
2009-01-01
In terms of Hadamard product, a new model is proposed for the control of connection coefficients of the state variables of the systems. The control law to stabilize the systems via the regulations of connection coefficients is obtained via a Hadamard product involved bilinear matrix inequalities. This new control model may be of significant applications in many fields, especially may be of some special sense in the emergency control such as isolation and obstruction control.
Robust State Feedback H∞Control for Dynamic Biped Robot Based on T-S Fuzzy Model
Institute of Scientific and Technical Information of China (English)
HUAI Chuangfeng; FANG Yuefa
2006-01-01
T-S fuzzy model was applied to describe nonlinear system and global fuzzy model was expressed by the form of uncertain system. Based on robust state feedback H∞control strategy, designed a global asymptotic steady fuzzy model. This control system can use the experimental input-output data pairs for the biped robot learning and walking with dynamic balance. It is proved by simulation result that robust state feedback H∞ control method based on T-S fuzzy model can effectively restrain the effect of model uncertainties and external disturbance acting on biped robot. From these works, we showed the satisfactory performance of joint tracking without any chattering.
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.
Real-Time, Model-Based Spray-Cooling Control System for Steel Continuous Casting
Petrus, Bryan; Zheng, Kai; Zhou, X.; Thomas, Brian G.; Bentsman, Joseph
2011-02-01
This article presents a new system to control secondary cooling water sprays in continuous casting of thin steel slabs (CONONLINE). It uses real-time numerical simulation of heat transfer and solidification within the strand as a software sensor in place of unreliable temperature measurements. The one-dimensional finite-difference model, CON1D, is adapted to create the real-time predictor of the slab temperature and solidification state. During operation, the model is updated with data collected by the caster automation systems. A decentralized controller configuration based on a bank of proportional-integral controllers with antiwindup is developed to maintain the shell surface-temperature profile at a desired set point. A new method of set-point generation is proposed to account for measured mold heat flux variations. A user-friendly monitor visualizes the results and accepts set-point changes from the caster operator. Example simulations demonstrate how a significantly better shell surface-temperature control is achieved.
Passivity-based model predictive control for mobile vehicle motion planning
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...
A Study of Electric Vehicle Suspension Control System Based on an Improved Half-vehicle Model
Institute of Scientific and Technical Information of China (English)
Jiang-Tao Cao; Hong-Hai Liu; Ping Li; David J.Brown; Georgi Dimirovski
2007-01-01
An improved half-vehicle model has been proposed for active suspension control systems, in contrast to existing models, it allows to explore the nature of the effect of vehicle speed changes by introducing a state vector of vehicle pitch angle. Three control strategies of linear quadratic control (LQ), improved LQ (ILQ) and wheelbase preview LQ (WLQ) have been implemented into the proposed model. ILQ has integrated an additional control parameter into LQ by concerning the correlation between acceleration values and their corresponding pitch angles. Simulation results have showed the effectiveness of the proposed model in terms of LQ, ILQ and WLQ control strategies.
Adaptive Call Admission Control Based on Reward-Penalty Model in Wireless/Mobile Network
Institute of Scientific and Technical Information of China (English)
Jian-Hui Huang; De-Pei Qian; Sheng-Ling Wang
2007-01-01
A dynamic threshold-based Call Admission Control (CAC) scheme used in wireless/mobile network for multi- class services is proposed. In the scheme, each class's CAC thresholds are solved through establishing a reward-penalty model which strives to maximize network's revenue. In order to lower Handoff Dropping Probability (HDP), the scheme joints packet and connection levels Quality of Service constraints, designing a bandwidth degradation algorithm to accept handoff calls by degrading existing calls' bandwidth during network congestion. Analyses show that the CAC thresholds change adaptively with the average call arrival rate. The performance comparison shows that the proposed scheme outperforms the Mobile IP Reservation scheme.
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
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.
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...
1991-12-01
Proc. IEEE Conf. on Robotics and Automation, pages 1520-1531, 1986. Vol. 3. 12. P. Khosla and T. Kanade. Parameters Identification of Robot Dynamics . In...Manipulator Control: A Case Study. In Proc. of IEEE Int. Conf. on Robotics and Automation, pages 1392-1400, 1987. 26. Mark W. Spong and M. Vidyasagar. Robot ... Dynamics and Control. John Wiley and Sons, 1989. 27. T.J. Tan and A.K. Beiczy. Dynamic Equations for PUMA-560 Robot Arm. Technical Report SSM-RL-85-02
Bonne, F.; Bonnay, P.; Hoa, C.; Mahoudeau, G.; Rousset, B.
2017-02-01
This papers deals with the Japan Torus-60 Super Advanced fusion experiment JT-60SA cryogenic system. A presentation of the JT-60SA cryogenic system model, from 300K to 4.4K -using the Matlab/Simulink/Simscape Simcryogenics library- will be given. As a first validation of our modelling strategy, the obtained operating point will be compared with the one obtained from HYSYS simulations. In the JT60-SA tokamak, pulsed heat loads are expected to be coming from the plasma and must be handled properly, using both appropriate refrigerator architecture and appropriate control model, to smooth the heat load. This paper presents model-based designed PID control schemes to control the helium mass inside the phase separator. The helium mass inside the phase separator as been chosen to be the variable of interest in the phase separator since it is independent of the pressure which can vary from 1 bar to 1.8 bar during load smoothing. Dynamics simulations will be shown to assess the legitimacy of the proposed strategy. This work is partially supported through the French National Research Agency (ANR), task agreement ANR-13-SEED-0005.
Modelling and Control of the Qball X4 Quadrotor System based on Pid and Fuzzy Logic Structure
Bodrumlu, Tolga; Turan Soylemez, Mehmet; Mutlu, Ilhan
2017-01-01
This work focuses on a quadrocopter model, which was developed by QuanserTM and named as Qball X4. First, mathematical model of the Qball X4 is obtained. Then, a conventional PID control technique is presented. This PID control parameters come from Qball user manual. After the presentation of conventional PID control, as an extension of the conventional PID control theory, a different fuzzy controller structure is given. The proposed fuzzy controller structure is based on fuzzy logic and its name is PID type fuzzy controller. All of the simulations are done in MATLABTM environment.
A pH-control model for heterotrophic and hydrogen-based autotrophic denitrification.
Tang, Youneng; Zhou, Chen; Ziv-El, Michal; Rittmann, Bruce E
2011-01-01
This work presents a model to predict the alkalinity, pH, and Langelier Saturation Index (LSI) in heterotrophic and H(2)-based autotrophic denitrification systems. The model can also be used to estimate the amount of acid, e.g. HCl, added to the influent (method 1) or the pH set point in the reactor (method 2: pH can be maintained stable by CO(2)-sparge using a pH-control loop) to prevent the pH from exceeding the optimal range for denitrification and to prevent precipitation from occurring. The model was tested with two pilot plants carrying out denitrification of groundwater with high hardness: a heterotrophic system using ethanol as the electron donor and an H(2)-based autotrophic system. The measured alkalinity, pH, and LSI were consistent with the model for both systems. This work also quantifies: (1) how the alkalinity and pH in Stage-1 significantly differ from those in Stage-2; (2) how the pH and LSI differ significantly in the two denitrification systems while the alkalinity increase is about the same; and (3) why CO(2) addition is the preferred method for autotrophic system, while HCl addition is the preferred method for the heterotrophic system.
Model-Based Engine Control Architecture with an Extended Kalman Filter
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.
Han, Xiang-Lei; Larrieu, Guilhem; Krzeminski, Christophe
2013-12-01
Silicon nanostructure patterning with tight geometry control is an important challenge at the bottom level. In that context, stress based controlled oxidation appears to be an efficient tool for precise nanofabrication. Here, we investigate the stress-retarded oxidation phenomenon in various silicon nanostructures (nanobeams, nanorings and nanowires) at both the experimental and the theoretical levels. Different silicon nanostructures have been fabricated by a top-down approach. Complex dependence of the stress build-up on the nano-object’s dimension, shape and size has been demonstrated experimentally and physically explained by modelling. For the oxidation of a two-dimensional nanostructure (nanobeam), relative independence to size effects has been observed. On the other hand, radial stress increase with geometry downscaling of a one-dimensional nanostructure (nanowire) has been carefully emphasized. The study of shape engineering by retarded oxidation effects for vertical silicon nanowires is finally discussed.
Iterated non-linear model predictive control based on tubes and contractive constraints.
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.
TayyebTaher, M.; Esmaeilzadeh, S. Majid
2017-07-01
This article presents an application of Model Predictive Controller (MPC) to the attitude control of a geostationary flexible satellite. SIMO model has been used for the geostationary satellite, using the Lagrange equations. Flexibility is also included in the modelling equations. The state space equations are expressed in order to simplify the controller. Naturally there is no specific tuning rule to find the best parameters of an MPC controller which fits the desired controller. Being an intelligence method for optimizing problem, Genetic Algorithm has been used for optimizing the performance of MPC controller by tuning the controller parameter due to minimum rise time, settling time, overshoot of the target point of the flexible structure and its mode shape amplitudes to make large attitude maneuvers possible. The model included geosynchronous orbit environment and geostationary satellite parameters. The simulation results of the flexible satellite with attitude maneuver shows the efficiency of proposed optimization method in comparison with LQR optimal controller.
2015-08-21
compute carbon monoxide (CO) and carbon dioxide (CO2) concentrations as well. Both pollutants are regulated by the UN Kyoto Protocol as well as by...combustion control. 1993. [16] I Culjak, A Sikanic, and V Koroman. Renewable energy sources in compliance of kyoto protocol targets: Case study of 42 mw
van der Lee, J H; Svrcek, W Y; Young, B R
2008-01-01
Model Predictive Control is a valuable tool for the process control engineer in a wide variety of applications. Because of this the structure of an MPC can vary dramatically from application to application. There have been a number of works dedicated to MPC tuning for specific cases. Since MPCs can differ significantly, this means that these tuning methods become inapplicable and a trial and error tuning approach must be used. This can be quite time consuming and can result in non-optimum tuning. In an attempt to resolve this, a generalized automated tuning algorithm for MPCs was developed. This approach is numerically based and combines a genetic algorithm with multi-objective fuzzy decision-making. The key advantages to this approach are that genetic algorithms are not problem specific and only need to be adapted to account for the number and ranges of tuning parameters for a given MPC. As well, multi-objective fuzzy decision-making can handle qualitative statements of what optimum control is, in addition to being able to use multiple inputs to determine tuning parameters that best match the desired results. This is particularly useful for multi-input, multi-output (MIMO) cases where the definition of "optimum" control is subject to the opinion of the control engineer tuning the system. A case study will be presented in order to illustrate the use of the tuning algorithm. This will include how different definitions of "optimum" control can arise, and how they are accounted for in the multi-objective decision making algorithm. The resulting tuning parameters from each of the definition sets will be compared, and in doing so show that the tuning parameters vary in order to meet each definition of optimum control, thus showing the generalized automated tuning algorithm approach for tuning MPCs is feasible.
Dubay, Rickey; Hassan, Marwan; Li, Chunying; Charest, Meaghan
2014-09-01
This paper presents a unique approach for active vibration control of a one-link flexible manipulator. The method combines a finite element model of the manipulator and an advanced model predictive controller to suppress vibration at its tip. This hybrid methodology improves significantly over the standard application of a predictive controller for vibration control. The finite element model used in place of standard modelling in the control algorithm provides a more accurate prediction of dynamic behavior, resulting in enhanced control. Closed loop control experiments were performed using the flexible manipulator, instrumented with strain gauges and piezoelectric actuators. In all instances, experimental and simulation results demonstrate that the finite element based predictive controller provides improved active vibration suppression in comparison with using a standard predictive control strategy. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.
Scellato, Salvatore; Musolesi, Mirco; Latora, Vito
2007-01-01
Epidemics-inspired techniques have received huge attention in recent years from the distributed systems and networking communities. These algorithms and protocols rely on probabilistic message replication and redundancy to ensure reliable communication. Moreover, they have been successfully exploited to support group communication in distributed systems, broadcasting, multicasting and information dissemination in fixed and mobile networks. However, in most of the existing work, the probability of infection is determined heuristically, without relying on any analytical model. This often leads to unnecessarily high transmission overheads. In this paper we show that models of epidemic spreading in complex networks can be applied to the problem of tuning and controlling the dissemination of information in wireless ad hoc networks composed of devices carried by individuals, i.e., human-based networks. The novelty of our idea resides in the evaluation and exploitation of the structure of the underlying human networ...
HOW TO BUILD TESTS IN THE IMITATION MODEL FOR TEST-BASED KNOWLEDGE CONTROL
Directory of Open Access Journals (Sweden)
Oleksandr M. Aleksieiev
2011-02-01
Full Text Available The principles of imitation model for knowledge test control, specifically on the perfection of the procedure of constructing a test, are developed in this model. The authors suggest taking into account the difficulty of the question when one is making a decision about including a given test question into the test. They also suggest using iterational calculations in order to create a test with the help of optimization algorithms that are used for the process of random searching. The sum of task complexity indices for such test will meet the criteria of joint value and difficulty. Detailed explanation of mathematical apparatus that is used for decision-making during the test-building process is given in the article as well as an example that demonstrates main steps of iterational calculations and mechanisms for achieving optimal test structure based on the criteria of joint value and difficulty.
Controller design of uncertain nonlinear systems based on T-S fuzzy model
Institute of Scientific and Technical Information of China (English)
Songtao ZHANG; Shizhen BAI
2009-01-01
A robust control for uncertain nonlinear systems based on T-S fuzzy model is discussed in this paper. First, a T-S fuzzy system is adopted to model the uncertain nonlinear systems. Then, for the system with input variables adopting standard fuzzy partitions, the efficient maximal overlapped-rules group (EMORG) is presented, and a new sufficient condition to check the stability of T-S fuzzy system with uncertainty is derived, which is expressed in terms of Linear Matrix Inequalities. The derived stability condition, which only requires a local common positive definite matrix in each EMORG, can reduce the conservatism and difficulty in existing stability conditions. Finally, a simulation example shows the proposed approach is effective.
Model-Based Design of Brushless DC Motor Control and Motion Control Modelling for RoboCup SSL Robots
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...
Identification and Control of a Cylindrical Tank Based on System Identification Models
Directory of Open Access Journals (Sweden)
Mary Mol Paul
2013-06-01
Full Text Available Advancements in the process control industry has made difficulties in controlling processes which are highly complex in nature. System identification provides a better solution for this problem with the help of identification models. In this paper ARX,ARMAX,BJ and OE models were used for the identification of a cylindrical tank and Ziegler Nichols tuning method to develop the controller for controlling the level of the tank. The proposed method provides simple and accurate models and thereby improving the efficency of identification process. MATLAB and LABView softwares were used here for identification and controlling.
A PID Positioning Controller with a Curve Fitting Model Based on RFID Technology
Directory of Open Access Journals (Sweden)
Young-Long Chen
2013-04-01
Full Text Available The global positioning system (GPS is an important research topic to solve outdoor positioning problems, but GPS is unable to locate objects accurately and precisely indoors. Some available systems apply ultrasound or optical tracking. This paper presents an efficient proportional-integral-derivative (PID controller with curve fitting model for mobile robot localization and position estimation which adopts passive radio frequency identification (RFID tags in a space. This scheme is based on a mobile robot carries an RFID reader module which reads the installed low-cost passive tags under the floor in a grid-like pattern. The PID controllers increase the efficiency of captured RFID tags and the curve fitting model is used to systematically identify the revolutions per minute (RPM of the motor. We control and monitor the position of the robot from a remote location through a mobile phone via Wi-Fi and Bluetooth network. Experiment results present that the number of captured RFID tags of our proposed scheme outperforms that of the previous scheme.
Lattice hydrodynamic model based traffic control: A transportation cyber-physical system approach
Liu, Hui; Sun, Dihua; Liu, Weining
2016-11-01
Lattice hydrodynamic model is a typical continuum traffic flow model, which describes the jamming transition of traffic flow properly. Previous studies in lattice hydrodynamic model have shown that the use of control method has the potential to improve traffic conditions. In this paper, a new control method is applied in lattice hydrodynamic model from a transportation cyber-physical system approach, in which only one lattice site needs to be controlled in this control scheme. The simulation verifies the feasibility and validity of this method, which can ensure the efficient and smooth operation of the traffic flow.
Modeling, control, and dispatch of photovoltaic-based power distribution systems
Carrasco, Miguel
Small-scale generators, also called distributed generators (DGs), are primed to play a central role in future distribution systems. If properly integrated, DGs present two main advantages: (i) they help decongest existing transmission grids; and (ii) CO2 emissions are reduced since most DGs are based on renewables like wind and solar. Their integration into distribution systems is one of the main challenges the power industry will be facing in the coming years. Photovoltaic (PV) power generation represents a key technology for realizing the DG concept. In this dissertation, technical solutions are developed that enable an increased penetration of PV systems, while improving the efficiency, reliability, and power quality of power distribution grids. The presented research spans from PV array modeling, parameter identification and estimation methods, through advanced control strategies for the power electronic interfaces, to system--level optimal dispatch strategies. Simulation-based and experimental validation results show the performance of the proposed techniques.
Energy Technology Data Exchange (ETDEWEB)
Delavari, H. Hamid, E-mail: Hamid.delavari@gmail.com [Institute for Nanoscience and Nanotechnology, Sharif University of Technology, Azadi Avenue, 145888-9694 Tehran (Iran, Islamic Republic of); Department of Physics and Astronomy, Uppsala University, Box 516, SE-75120 Uppsala (Sweden); Madaah Hosseini, Hamid R. [Institute for Nanoscience and Nanotechnology, Sharif University of Technology, Azadi Avenue, 145888-9694 Tehran (Iran, Islamic Republic of); Department of Materials Science and Engineering, Sharif University of Technology, Azadi Avenue, 145888-9694 Tehran (Iran, Islamic Republic of); Wolff, Max, E-mail: Max.wolff@physics.uu.se [Department of Physics and Astronomy, Uppsala University, Box 516, SE-75120 Uppsala (Sweden)
2013-06-15
In order to provide sufficient heat without overheating healthy tissue in magnetic fluid hyperthermia (MFH), a careful design of the magnetic properties of nanoparticles is essential. We perform a systematic calculation of magnetic properties of Ni-alloy nanoparticles. Stoner–Wohlfarth model based theories (SWMBTs) are considered and the linear response theory (LRT) is used to extract the hysteresis loop of nickel alloy nanoparticles in alternating magnetic fields. It is demonstrated that in the safe range of magnetic field intensity and frequency the LRT cannot be used for the calculation of the area in the hysteresis for magnetic fields relevant for hyperthermia. The best composition and particle size for self-controlling hyperthermia with nickel alloys is determined based on SWMBTs. It is concluded that Ni–V and Ni–Zn are good candidates for self-controlling hyperthermia. - Highlights: ► Systematic calculation of magnetic properties of Ni-alloy NPs with composition has been performed. ► Optimum composition and particle size for self-controlling hyperthermia (SCH) have been determined. ► Ni–V and Ni–Zn nanoparticles are more appropriate candidates for SCH.
The optimal dynamic immunization under a controlled heterogeneous node-based SIRS model
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.
A New Interpretation of Spontaneous Sway Measures Based on a Simple Model of Human Postural Control
National Research Council Canada - National Science Library
Maurer, Christoph; Peterka, Robert J
...) traces that closely resemble physiologically measured COP functions can be produced by an appropriate selection of model parameters in a simple feedback model of the human postural control system...
Flatness-based model inverse for feed-forward braking control
de Vries, Edwin; Fehn, Achim; Rixen, Daniel
2010-12-01
For modern cars an increasing number of driver assistance systems have been developed. Some of these systems interfere/assist with the braking of a car. Here, a brake actuation algorithm for each individual wheel that can respond to both driver inputs and artificial vehicle deceleration set points is developed. The algorithm consists of a feed-forward control that ensures, within the modelled system plant, the optimal behaviour of the vehicle. For the quarter-car model with LuGre-tyre behavioural model, an inverse model can be derived using v x as the 'flat output', that is, the input for the inverse model. A number of time derivatives of the flat output are required to calculate the model input, brake torque. Polynomial trajectory planning provides the needed time derivatives of the deceleration request. The transition time of the planning can be adjusted to meet actuator constraints. It is shown that the output of the trajectory planning would ripple and introduce a time delay when a gradual continuous increase of deceleration is requested by the driver. Derivative filters are then considered: the Bessel filter provides the best symmetry in its step response. A filter of same order and with negative real-poles is also used, exhibiting no overshoot nor ringing. For these reasons, the 'real-poles' filter would be preferred over the Bessel filter. The half-car model can be used to predict the change in normal load on the front and rear axle due to the pitching of the vehicle. The anticipated dynamic variation of the wheel load can be included in the inverse model, even though it is based on a quarter-car. Brake force distribution proportional to normal load is established. It provides more natural and simpler equations than a fixed force ratio strategy.
Simulation and analysis of a Truck Model's ride comfort based on fuzzy adaptive control theory
Institute of Scientific and Technical Information of China (English)
JIANG Li-biao; WANG Deng-feng; NI Qiang; TAN Wei-ming
2007-01-01
This paper tried to analyse and verify the fuzzy adaptive control strategy of electronic control air suspension system for heavy truck. Created the seven-freedoms vehicle suspension model, and the road input model; with Matlab/Simulink toolboxes and modules, built dynamical system simulation model for heavy truck with air suspension, fuzzy adaptive control model, height control model for air spring, and intelligent control and analyse on root mean square value of acceleration of gravity center of the vehicle under excitation of road. Results show that the fuzzy control had less help to the body vibration on the better pavement, but had the better benefit on the bad road, and the vehicle's root mean square value of acceleration of gravity center is less than passive suspension's obviously.
The applications of model-based geostatistics in helminth epidemiology and control.
Magalhães, Ricardo J Soares; Clements, Archie C A; Patil, Anand P; Gething, Peter W; Brooker, Simon
2011-01-01
Funding agencies are dedicating substantial resources to tackle helminth infections. Reliable maps of the distribution of helminth infection can assist these efforts by targeting control resources to areas of greatest need. The ability to define the distribution of infection at regional, national and subnational levels has been enhanced greatly by the increased availability of good quality survey data and the use of model-based geostatistics (MBG), enabling spatial prediction in unsampled locations. A major advantage of MBG risk mapping approaches is that they provide a flexible statistical platform for handling and representing different sources of uncertainty, providing plausible and robust information on the spatial distribution of infections to inform the design and implementation of control programmes. Focussing on schistosomiasis and soil-transmitted helminthiasis, with additional examples for lymphatic filariasis and onchocerciasis, we review the progress made to date with the application of MBG tools in large-scale, real-world control programmes and propose a general framework for their application to inform integrative spatial planning of helminth disease control programmes.
Control of a powered ankle-foot prosthesis based on a neuromuscular model.
Eilenberg, Michael F; Geyer, Hartmut; Herr, Hugh
2010-04-01
Control schemes for powered ankle-foot prostheses rely upon fixed torque-ankle state relationships obtained from measurements of intact humans walking at target speeds and across known terrains. Although effective at their intended gait speed and terrain, these controllers do not allow for adaptation to environmental disturbances such as speed transients and terrain variation. Here we present an adaptive muscle-reflex controller, based on simulation studies, that utilizes an ankle plantar flexor comprising a Hill-type muscle with a positive force feedback reflex. The model's parameters were fitted to match the human ankle's torque-angle profile as obtained from level-ground walking measurements of a weight and height-matched intact subject walking at 1 m/s. Using this single parameter set, clinical trials were conducted with a transtibial amputee walking on level ground, ramp ascent, and ramp descent conditions. During these trials, an adaptation of prosthetic ankle work was observed in response to ground slope variation, in a manner comparable to intact subjects, without the difficulties of explicit terrain sensing. Specifically, the energy provided by the prosthesis was directly correlated to the ground slope angle. This study highlights the importance of neuromuscular controllers for enhancing the adaptiveness of powered prosthetic devices across varied terrain surfaces.
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.
Adjoint LMS (ALMS Algorithm Based Active Noise Control with Feedback Path Modeling
Directory of Open Access Journals (Sweden)
U Ramachandraiah,
2010-12-01
Full Text Available In active noise control (ANC systems, there exists an inherent feedback from the loudspeaker to the primary microphone. Adjoint least mean square (ALMS algorithm is known to be an alternative to the widely used filtered x LMS (FxLMS for reducing the computational complexity and memory requirements, especially in the case of multi-channel systems. Further FxLMS algorithm is based on the assumptionthat the order of the weighing filter and secondary path can be commuted which is not always true in practice. Though ALMS do not make such an assumption, neither FxLMS nor the ALMS algorithms onsider the feedback path effect that is inherent in ANC systems.We propose a feedback ANC system based on ALMS algorithm which is analogous to the system based on FxLMS. Detailed computational complexity analysis for addition and multiplication requirements ispresented and are compared with those of its counterpart to establish its usefulness. Simulation results show the convergence characteristics of the ALMS based ANC with feedback path modeling is on par with that based on FxLMS.
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
Toward Model-Based Control of Non-linear Hydraulic Networks
DEFF Research Database (Denmark)
Tahavori, Maryamsadat; Jensen, Tom Nørgaard; Kallesøe, Carsten
2013-01-01
consumption. To have a better understanding of leakage in WSSs, to control pressure and leakage effectively, and for optimal design of WSSs, suitable modeling is an important prerequisite. In this paper a model with the main objective of pressure control and consequently leakage reduction is presented...
Learning-based Nonlinear Model Predictive Control to Improve Vision-based Mobile Robot Path Tracking
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
Modelling and control of Base Plate Loading subsystem for The Motorized Adjustable Vertical Platform
Norsahperi, N. M. H.; Ahmad, S.; Fuad, A. F. M.; Mahmood, I. A.; Toha, S. F.; Akmeliawati, R.; Darsivan, F. J.
2017-03-01
Malaysia National Space Agency, ANGKASA is an organization that intensively undergoes many researches especially on space. On 2011, ANGKASA had built Satellite Assembly, Integration and Test Centre (AITC) for spacecraft development and test. Satellite will undergo numerous tests and one of it is Thermal test in Thermal Vacuum Chamber (TVC). In fact, TVC is located in cleanroom and on a platform. The only available facilities for loading and unloading the satellite is overhead crane. By utilizing the overhead crane can jeopardize the safety of the satellite. Therefore, Motorized vertical platform (MAVeP) for transferring the satellite into the TVC with capability to operate under cleanroom condition and limited space is proposed to facilitate the test. MAVeP is the combination of several mechanisms to produce horizontal and vertical motions with the ability to transfer the satellite from loading bay into TVC. The integration of both motions to elevate and transfer heavy loads with high precision capability will deliver major contributions in various industries such as aerospace and automotive. Base plate subsystem is capable to translate the horizontal motion by converting the angular motion from motor to linear motion by using rack and pinion mechanism. Generally a system can be modelled by performing physical modelling from schematic diagram or through system identification techniques. Both techniques are time consuming and required comprehensive understanding about the system, which may expose to error prone especially for complex mechanism. Therefore, a 3D virtual modelling technique has been implemented to represent the system in real world environment i.e. gravity to simulate control performance. The main purpose of this technique is to provide better model to analyse the system performance and capable to evaluate the dynamic behaviour of the system with visualization of the system performance, where a 3D prototype was designed and assembled in Solidworks
Robust Quasi-LPV Control Based on Neural State Space Models
DEFF Research Database (Denmark)
Bendtsen, Jan Dimon; Trangbæk, Klaus
2000-01-01
In this paper we derive a synthesis result for robust LPV output feedback controllers for nonlinear systems modelled by neural state space models. This result is achieved by writing the neural state space model on a linear fractional transformation form in a non-conservative way, separating...... the system description into a linear part and a nonlinear part. Linear parameter-varying control synthesis methods are then applied to design a nonlinear control law for this system. Since the model is assumed to have been identified from input-output measurement data only, it must be expected...
Directory of Open Access Journals (Sweden)
Jing Sun
2015-01-01
Full Text Available The torque coordination control during mode transition is a very important task for hybrid electric vehicle (HEV with a clutch serving as the key enabling actuator element. Poor coordination will deteriorate the drivability of the driver and lead to excessive wearing to the clutch friction plates. In this paper, a novel torque coordination control strategy for a single-shaft parallel hybrid electric vehicle is presented to coordinate the motor torque, engine torque, and clutch torque so that the seamless mode switching can be achieved. Different to the existing model predictive control (MPC methods, only one model predictive controller is needed and the clutch torque is taken as an optimized variable rather than a known parameter. Furthermore, the successful idea of model reference control (MRC is also used for reference to generate the set-point signal required by MPC. The parameter sensitivity is studied for better performance of the proposed model predictive controller. The simulation results validate that the proposed novel torque coordination control strategy has less vehicle jerk, less torque interruption, and smaller clutch frictional losses, compared with the baseline method. In addition, the sensitivity and adaptiveness of the proposed novel torque coordination control strategy are evaluated.
A PID Positioning Controller with a Curve Fitting Model Based on RFID Technology
Directory of Open Access Journals (Sweden)
Young-Long Chen
2013-03-01
Full Text Available The global positioning system (GPS is an important research topic to solve outdoor positioning problems, but GPSis unable to locate objects accurately and precisely indoors. Some available systems apply ultrasound or opticaltracking. This paper presents an efficient proportional-integral-derivative (PID controller with curve fitting model formobile robot localization and position estimation which adopts passive radio frequency identification (RFID tags ina space. This scheme is based on a mobile robot carries an RFID reader module which reads the installed low-costpassive tags under the floor in a grid-like pattern. The PID controllers increase the efficiency of captured RFID tagsand the curve fitting model is used to systematically identify the revolutions per minute (RPM of the motor. Wecontrol and monitor the position of the robot from a remote location through a mobile phone via Wi-Fi and Bluetoothnetwork. Experiment results present that the number of captured RFID tags of our proposed scheme outperformsthat of the previous scheme.
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.
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.
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.
A semiparametric Wald statistic for testing logistic regression models based on case-control data
Institute of Scientific and Technical Information of China (English)
2008-01-01
We propose a semiparametric Wald statistic to test the validity of logistic regression models based on case-control data. The test statistic is constructed using a semiparametric ROC curve estimator and a nonparametric ROC curve estimator. The statistic has an asymptotic chi-squared distribution and is an alternative to the Kolmogorov-Smirnov-type statistic proposed by Qin and Zhang in 1997, the chi-squared-type statistic proposed by Zhang in 1999 and the information matrix test statistic proposed by Zhang in 2001. The statistic is easy to compute in the sense that it requires none of the following methods: using a bootstrap method to find its critical values, partitioning the sample data or inverting a high-dimensional matrix. We present some results on simulation and on analysis of two real examples. Moreover, we discuss how to extend our statistic to a family of statistics and how to construct its Kolmogorov-Smirnov counterpart.
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.
RESEARCH ON ACTIVE VIBRATION CONTROL BASED ON COMBINED MODEL FOR COUPLED SYSTEMS
Institute of Scientific and Technical Information of China (English)
Niu Junchuan; Zhao Guoqun; Song Kongjie
2004-01-01
A novel combined model of the vibration control for the coupled flexible system and its general mathematic description are developed. In presented model, active and passive controls as well as force and moment controls are combined into a single unit to achieve the efficient vibration control of the flexible structures by multi-approaches. Considering the complexity of the energy transmission in the vibrating system, the transmission channels of the power flow transmitted into the foundation are discussed, and the general forces and the corresponding velocities are combined into a single function, respectively. Under the control strategy of the minimum power flow, the transmission characteristics of the power flow are investigated. From the presented numerical examples, it is obvious that the analytical model is effective, and both force and moment controls are able to depress vibration energy substantially.
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.
Robust Quasi-LPV Control Based on Neural State Space Models
DEFF Research Database (Denmark)
Bendtsen, Jan Dimon; Trangbæk, Klaus
2002-01-01
In this paper we derive a synthesis result for robust LPV output feedback controllers for nonlinear systems modelled by neural state space models. This result is achieved by writing the neural state space model on a linear fractional transformation form in a non-conservative way, separating...... that there is some uncertainty on the identified nonlinearities. The control law is therefore made robust to noise perturbations. After formulating the controller synthesis as a set of LMIs with added constraints, some implementation issues are addressed and a simulation example is presented....
Analysis and Improvement of TCP Congestion Control Mechanism Based on Global Optimization Model
Institute of Scientific and Technical Information of China (English)
无
2001-01-01
Network flow control is formulated as a global optimization problem of user profit. A general global optimization flow control model is established. This model combined with the stochastic model of TCP is used to study the global rate allocation characteristic of TCP. Analysis shows when active queue manage ment is used in network TCP rates tend to be allocated to maximize the aggregate of a user utility function Us (called Us fairness). The TCP throughput formula is derived. An improved TCP congestion control mecha nism is proposed. Simulations show its throughput is TCP friendly when competing with existing TCP and its rate change is smoother. Therefore, it is suitable to carry multimedia applications.
DEFF Research Database (Denmark)
Christiansen, Søren; Tabatabaeipour, Seyed Mojtaba; Bak, Thomas;
2013-01-01
Floating wind turbines are considered as a new and promising solution for reaching higher wind resources beyond the water depth restriction of monopile wind turbines. But on a floating structure, the wave-induced loads significantly increase the oscillations of the structure. Furthermore, using...... a controller designed for an onshore wind turbine yields instability in the fore-aft rotation. In this paper, we propose a general framework, where a reference model models the desired closed-loop behavior of the system. Model predictive control combined with a state estimator finds the optimal rotor blade...... compared to a baseline floating wind turbine controller at the cost of more pitch action....
Goodwin, Graham. C.; Medioli, Adrian. M.
2013-08-01
Model predictive control has been a major success story in process control. More recently, the methodology has been used in other contexts, including automotive engine control, power electronics and telecommunications. Most applications focus on set-point tracking and use single-sequence optimisation. Here we consider an alternative class of problems motivated by the scheduling of emergency vehicles. Here disturbances are the dominant feature. We develop a novel closed-loop model predictive control strategy aimed at this class of problems. We motivate, and illustrate, the ideas via the problem of fluid deployment of ambulance resources.
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...
Rhoads, Lloyd A.
This thesis builds upon recent studies focusing on modeling, operation, and control of high temperature gas cooled reactors. A computer model was developed, based on mass, energy, and momentum balances of control volumes throughout the plant. Several simulations of the plant behavior were conducted and their results were compared with those from the literature. Proportional control was combined with optimal control to form a time varying, adjustable gain predictive controller which adjusts the proportional gains during transients. The controller was designed to utilize control rod motions and bypass control valves to maintain desired plant conditions. An optimization scheme was introduced to efficiently solve the optimization problem formulated as part of the predictive controller operation. Several additional transients were run to examine the full plant controller performance. Multiple predictive controllers were designed and their performance was compared with a proportional controller throughout each transient. The predictive controller results confirmed the importance of proper selection of the optimal controller parameters, in particular the controller time step size and the horizon time. The well-designed proportional controllers clearly demonstrated improvements in plant performance during short time scale transients, namely a loss of secondary heat transfer transient and a step change in desired power transient. Results from long time scale transients demonstrated the capabilities of the proposed bypass control system to control electrical power production without the need for storage vessels.
Comparative Results on 3D Navigation of Quadrotor using two Nonlinear Model based Controllers
Bouzid, Y.; Siguerdidjane, H.; Bestaoui, Y.
2017-01-01
Recently the quadrotors are being increasingly employed in both military and civilian areas where a broad range of nonlinear flight control techniques are successfully implemented. With this advancement, it has become necessary to investigate the efficiency of these flight controllers by studying theirs features and compare their performance. In this paper, the control of Unmanned Aerial Vehicle (UAV) quadrotor, using two different approaches, is presented. The first controller is Nonlinear PID (NLPID) whilst the second one is Nonlinear Internal Model Control (NLIMC) that are used for the stabilization as well as for the 3D trajectory tracking. The numerical simulations have shown satisfactory results using nominal system model or disturbed model for both of them. The obtained results are analyzed with respect to several criteria for the sake of comparison.
Modeling and Extended State Observer Based Dynamic Surface Control for Cold Rolling Mill System
Directory of Open Access Journals (Sweden)
Xu Li
2016-01-01
Full Text Available The modeling and control problems are investigated for cold rolling mill system. Firstly, we establish a monitor automatic gauge control (MAGC model for a practical cold rolling mill system. The new model is with mismatched uncertainties. Then, an extended state observer (ESO is developed to estimate uncertainties. In the general high-order systems, the ESO is also used to estimate states. By dynamic surface control method, we design the controller to guarantee stabilization of the cold rolling mill system. Furthermore, we extend proposed method to general high-order systems, in which we analyze the difference from cold rolling mill system. Finally, simulation results for MAGC system are presented to demonstrate the effectiveness of the proposed control strategy.
Integration of supervisory control synthesis in model-based systems engineering
J.C.M. Baeten (Jos); J.M. van de Mortel-Fronczak; J.E. Rooda
2011-01-01
htmlabstractDue to increasing system complexity, time-to-market and development costs reduction, there are higher demands on engineering processes. Model-based engineering processes can play a role here because they support system development by enabling the use of various model-based analysis
Sliding Mode Control for Nonlinear System Based on T-S Model
Institute of Scientific and Technical Information of China (English)
WU Zhong-qiang
2002-01-01
Using T-S model as an approximation for nonlinear system, the nonlinear system has been fuzzy into local linear model. The variable structure controller designed by using Lyapunov theory insures the stability of system. The sliding mode controller is designed by using unit vector style, and it suit the uncertain elements satisfying matching condition or do not satisfy matching condition. The effect of the scheme has been tasted with a simulation of an inverted pendulum.
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.
A Model-Based Study of Ecohydrological Controls in the Mojave Desert
Ng, G. C.; Bedford, D.; Miller, D. M.
2010-12-01
Desert ecosystems represent extreme conditions near the limits of viability for vegetation. Their dependence on scarce resources make them vulnerable to climate and land use change. Understanding how ecohydrological conditions impact plants in such regions is critical for ecological sustainability. Various relationships have been observed in the field between vegetation growth and meteorology, terrain, and plant physiology. Quantifying the complex interactions of those influences on vegetation dynamics can be facilitated with a physically-based ecohydrological model. To assess ecohydrological controls in the Mojave Desert, we employ the CLM4.0 land-surface model with the Carbon-Nitrogen model component to simulate vegetation dynamics [Olesen et al., 2010]. Using an ecohydrological model with fully prognostic vegetation variables is essential for representing the coupled dynamics between plants and soil moisture. We apply the CLM4.0-CN model to a study basin in the Mojave National Preserve that covers a variety of conditions. Soils range from coarse-textured wash sediments to low-permeability desert pavements. Higher elevations in the basin experience cooler and moister conditions than the lower wash areas. The dominant vegetation types in the basin include the evergreen shrub Larrea tridentata (creosote) and the drought-deciduous shrub Ambrosia dumosa. Simulations are conducted over a 50 year period to investigate both seasonal and interannual dynamics. Sensitivity tests indicate that high temporal resolution rainfall inputs (at least hourly) are important for properly resolving ecohydrological dynamics at the study site. As expected, preliminary results show that both coarser soils and milder climate facilitate vegetation growth in this moisture-limited region. However, results indicate that effects of soil texture variations become subordinate with milder climate. The model also reveals how drought-deciduous and evergreen shrub types respond differently to
Biomimetic control based on a model of chemotaxis in Escherichia coli.
Tsuji, Toshio; Suzuki, Michiyo; Takiguchi, Noboru; Ohtake, Hisao
2010-01-01
In the field of molecular biology, extending now to the more comprehensive area of systems biology, the development of computer models for synthetic cell simulation has accelerated extensively and has begun to be used for various purposes, such as biochemical analysis. These models, describing the highly efficient environmental searching mechanisms and adaptability of living organisms, can be used as machine-control algorithms in the field of systems engineering. To realize this biomimetic intelligent control, we require a stripped-down model that expresses a series of information-processing tasks from stimulation input to movement. Here we selected the bacterium Escherichia coli as a target organism because it has a relatively simple molecular and organizational structure, which can be characterized using biochemical and genetic analyses. We particularly focused on a motility response known as chemotaxis and developed a computer model that includes not only intracellular information processing but also motor control. After confirming the effectiveness and validity of the proposed model by a series of computer simulations, we applied it to a mobile robot control problem. This is probably the first study showing that a bacterial model can be used as an autonomous control algorithm. Our results suggest that many excellent models proposed thus far for biochemical purposes can be applied to problems in other fields.
Model based optimization of wind erosion control by tree shelterbelt for suitable land management
Bartus, M.; Farsang, A.; Szatmári, J.; Barta, K.
2012-04-01
The degradation of soil by wind erosion causes huge problem in many parts of the world. The wind erodes the upper, nutrition rich part of the soil, therefore erosion causes soil productivity loss. The length of tree shelterbelts was significantly reduced by the collectivisation (1960-1989) and the wind erosion affected areas expanded in Hungary. The tree shelterbelt is more than just a tool of wind erosion control; by good planning it can increase the yield. The tree shelterbelt reduces the wind speed and changes the microclimate providing better condition to plant growth. The aim of our work is to estimate wind erosion risk and to find the way to reduce it by tree shelterbelts. A GIS based model was created to calculate the risk and the optimal windbreak position was defined to reduce the wind erosion risk to the minimum. The model is based on the DIN 19706 (Ermitlung der Erosiongefährdung von Böden durch Wind, Estimation of Wind Erosion Risk) German standard. The model uses five input data: structure and carbon content of soil, average yearly wind speed at 10 meters height, the cultivated plants and the height and position of windbreak. The study field (16km2) was chosen near Szeged (SE Hungary). In our investigation, the cultivated plant species and the position and height of windbreaks were modified. Different scenarios were made using the data of the land management in the last few years. The best case scenario (zero wind erosion) and the worst case scenario (with no tree shelter belt and the worst land use) were made to find the optimal windbreak position. Finally, the research proved that the tree shelterbelts can provide proper protection against wind erosion, but for optimal land management the cultivated plant types should also controlled. As a result of the research, a land management plan was defined to reduce the wind erosion risk on the study field, which contains the positions of new tree shelterbelts planting and the optimal cultivation.
Interpretation of machine-learning-based disruption models for plasma control
Parsons, Matthew S.
2017-08-01
While machine learning techniques have been applied within the context of fusion for predicting plasma disruptions in tokamaks, they are typically interpreted with a simple ‘yes/no’ prediction or perhaps a probability forecast. These techniques take input signals, which could be real-time signals from machine diagnostics, to make a prediction of whether a transient event will occur. A major criticism of these methods is that, due to the nature of machine learning, there is no clear correlation between the input signals and the output prediction result. Here is proposed a simple method that could be applied to any existing prediction model to determine how sensitive the state of a plasma is at any given time with respect to the input signals. This is accomplished by computing the gradient of the decision function, which effectively identifies the quickest path away from a disruption as a function of the input signals and therefore could be used in a plasma control setting to avoid them. A numerical example is provided for illustration based on a support vector machine model, and the application to real data is left as an open opportunity.
Havas, K A; Boone, R B; Hill, A E; Salman, M D
2014-06-01
Brucellosis has been reported in livestock and humans in the country of Georgia with Brucella melitensis as the most common species causing disease. Georgia lacked sufficient data to assess effectiveness of the various potential control measures utilizing a reliable population-based simulation model of animal-to-human transmission of this infection. Therefore, an agent-based model was built using data from previous studies to evaluate the effect of an animal-level infection control programme on human incidence and sheep flock and cattle herd prevalence of brucellosis in the Kakheti region of Georgia. This model simulated the patterns of interaction of human-animal workers, sheep flocks and cattle herds with various infection control measures and returned population-based data. The model simulates the use of control measures needed for herd and flock prevalence to fall below 2%. As per the model output, shepherds had the greatest disease reduction as a result of the infection control programme. Cattle had the greatest influence on the incidence of human disease. Control strategies should include all susceptible animal species, sheep and cattle, identify the species of brucellosis present in the cattle population and should be conducted at the municipality level. This approach can be considered as a model to other countries and regions when assessment of control strategies is needed but data are scattered.
The Pugh Controlled Convergence method: model-based evaluation and implications for design theory
Frey, D.D.; Herder, P.M.; Wijnia, Y.; Saubrahmanian, E.; Katsikopoulos, K.; Clausing, D.P.
2008-01-01
This paper evaluates the Pugh Controlled Convergence method and its relationship to recent developments in design theory. Computer executable models are proposed simulating a team of people involved in iterated cycles of evaluation, ideation, and investigation. The models suggest that: (1) convergen
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......-based controller. The combined control approach allow to achieve higher load alleviations, furthermore, in the presence of e.g. deterioration of an actuator, it enables an online re-tuning of the workload distribution of blade pitch and trailing edge flaps, thus potentially increasing the smart rotor reliability....
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......-based controller. The combined control approach allow to achieve higher load alleviations, furthermore, in the presence of e.g. deterioration of an actuator, it enables an online re-tuning of the workload distribution of blade pitch and trailing edge flaps, thus potentially increasing the smart rotor reliability....
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...
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...
Lühr, Armin; Löck, Steffen; Jakobi, Annika; Stützer, Kristin; Bandurska-Luque, Anna; Vogelius, Ivan Richter; Enghardt, Wolfgang; Baumann, Michael; Krause, Mechthild
2017-07-01
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. The approach divides the target volume into sub-volumes according to retrospectively observed spatial failure patterns. The product of all sub-volume TCPi values reproduces the observed TCP for the total tumor. The derived formalism provides for each target sub-volume i the tumor control dose (D50,i) and slope (γ50,i) parameters at 50% TCPi. For a simultaneous integrated boost (SIB) prescription for 45 advanced head and neck cancer patients, TCP values for photon and proton irradiation were calculated and compared. The target volume was divided into gross tumor volume (GTV), surrounding clinical target volume (CTV), and elective CTV (CTVE). The risk of a local failure in each of these sub-volumes was taken from the literature. Convenient expressions for D50,i and γ50,i were provided for the Poisson and the logistic model. Comparable TCP estimates were obtained for photon and proton plans of the 45 patients using the sub-volume model, despite notably higher dose levels (on average +4.9%) in the low-risk CTVE for photon irradiation. In contrast, assuming a homogeneous dose response in the entire target volume resulted in TCP estimates contradicting clinical experience (the highest failure rate in the low-risk CTVE) and differing substantially between photon and proton irradiation. The presented method is of practical value for three reasons: It (a) is based on empirical clinical outcome data; (b) can be applied to non-uniform dose prescriptions as well as different tumor entities and dose-response models; and (c) is provided in a convenient compact form. The approach may be utilized to target spatial patterns of local failures observed in patient cohorts by prescribing different doses to
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
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...
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
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...
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.
Multiagent-Based Reactive Power Sharing and Control Model for Islanded Microgrids
DEFF Research Database (Denmark)
Chen, Feixiong; Chen, Minyou; Li, Qiang
2016-01-01
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...
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.
Benefit Evaluation Model of Small Watershed Control Based on Projection Pursuit
Institute of Scientific and Technical Information of China (English)
无
2001-01-01
A projection pursuit model is presented in this paper for comprehensive evaluation of benefits of small watershed control. By using the model ,small watershed control samples with many benefit evaluation indexes can be synthesized projective values with one dimension. The samples can be naturally evaluated according to the projective values. The parameters of the model is optimized by using real coding beased accelerating genetic aglrothm,which overcomes the shortcomings of large computation amount and difficulty of computer programming in traditional projection prusuit methods,and provides a new way for wide applications of projection pursuit technique to different evaluation problems in agricultural systems engineering.
DEFF Research Database (Denmark)
Xu, Fengda; Guo, Qinglai; Sun, Hongbin;
2015-01-01
to keep the voltage of the pilot bus tracking its set point considering the DC system’s transmission schedule change. The approach is inspired by model predictive control (MPC) to compensate for predictable voltage change affected by DC side transmission power flow and the potential capacitor switching...
Dynamic modeling and control of DFIG-based wind turbines under balanced network conditions
DEFF Research Database (Denmark)
Mehdipour, Cyrous; Hajizadeh, Amin; Mehdipour, Iman
2016-01-01
. Then dynamic modeling and simulation of a sample power system are carried out. The operation of a DFIG coupled with WT under balanced condition of a power grid is investigated and stationary reference frame is utilized for analysis of a wind energy conversion system. At the second step, a wind power station...... is connected to the power grid in order to test the performances of the wind power station controller. The control plan utilizes stator flux oriented control and grid voltage vector control for the rotor and the grid side converter, respectively. MATLAB simulations clearly confirm the effectiveness...
Model-based setting of inspiratory pressure and respiratory rate in pressure-controlled ventilation.
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.
Towards Zero Retraining for Myoelectric Control Based on Common Model Component Analysis.
Liu, Jianwei; Sheng, Xinjun; Zhang, Dingguo; Jiang, Ning; Zhu, Xiangyang
2016-04-01
In spite of several decades of intense research and development, the existing algorithms of myoelectric pattern recognition (MPR) are yet to satisfy the criteria that a practical upper extremity prostheses should fulfill. This study focuses on the criterion of the short, or even zero subject training. Due to the inherent nonstationarity in surface electromyography (sEMG) signals, current myoelectric control algorithms usually need to be retrained daily during a multiple days' usage. This study was conducted based on the hypothesis that there exist some invariant characteristics in the sEMG signals when a subject performs the same motion in different days. Therefore, given a set of classifiers (models) trained on several days, it is possible to find common characteristics among them. To this end, we proposed to use common model component analysis (CMCA) framework, in which an optimized projection was found to minimize the dissimilarity among multiple models of linear discriminant analysis (LDA) trained using data from different days. Five intact-limbed subjects and two transradial amputee subjects participated in an experiment including six sessions of sEMG data recording, which were performed in six different days, to simulate the application of MPR over multiple days. The results demonstrate that CMCA has a significant better generalization ability with unseen data (not included in the training data), leading to classification accuracy improvement and increase of completion rate in a motion test simulation, when comparing with the baseline reference method. The results indicate that CMCA holds a great potential in the effort of developing zero retraining of MPR.
Model-based Optimization and Feedback Control of the Current Density Profile Evolution in NSTX-U
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
A model-based production planning and control method supporting delivery of cast-in-place concrete
Norberg, Håkan; Jongeling, Rogier
2008-01-01
This paper combines model-based design and construction techniques with principles from location based planning methods. Both concepts are applied in a practical study in which a model-based method is developed for the planning and control of cast in place concrete deliveries to the building site. The overall aim of this paper is to show a method that can be used to make the planning and control of the delivery process for cast in place concrete more efficient. The paper shows examples of cha...
Institute of Scientific and Technical Information of China (English)
Guixiong LIU; Peiqiang ZHANG; Chen XU
2009-01-01
Magnetic fluid is first introduced into thetraditional cantileverbeam senor. Based on the property of the cantilever-beam and the novel controllable mag-viscosity of magnetic fluid, the output of cantilever-beam sensors is under control so that the controllable output of the sensors can be realized. The mathematical model of the sensors is established and analyzed. The dynamic control function and the following educational results, which include the two curves of the displacement ratio and phase function with the different damping ratio and frequency ratio, are obtained based on the model. The result shows that it is valid to realize the controllable output of the sensors by controlling the viscosity of the magnetic fluid,and finally the expanded measurement range can be realized.
A fuzzy model based adaptive PID controller design for nonlinear and uncertain processes.
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.
Tavakoli-Kakhki, Mahsan; Haeri, Mohammad
2011-07-01
Fractional order PI and PID controllers are the most common fractional order controllers used in practice. In this paper, a simple analytical method is proposed for tuning the parameters of these controllers. The proposed method is useful in designing fractional order PI and PID controllers for control of complicated fractional order systems. To achieve the goal, at first a reduction technique is presented for approximating complicated fractional order models. Then, based on the obtained reduced models some analytical rules are suggested to determine the parameters of fractional order PI and PID controllers. Finally, numerical results are given to show the efficiency of the proposed tuning algorithm.
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......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...... 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....
Smolders, K.; Volckaert, M.; Swevers, J.
2008-11-01
This paper presents a nonlinear model-based iterative learning control procedure to achieve accurate tracking control for nonlinear lumped mechanical continuous-time systems. The model structure used in this iterative learning control procedure is new and combines a linear state space model and a nonlinear feature space transformation. An intuitive two-step iterative algorithm to identify the model parameters is presented. It alternates between the estimation of the linear and the nonlinear model part. It is assumed that besides the input and output signals also the full state vector of the system is available for identification. A measurement and signal processing procedure to estimate these signals for lumped mechanical systems is presented. The iterative learning control procedure relies on the calculation of the input that generates a given model output, so-called offline model inversion. A new offline nonlinear model inversion method for continuous-time, nonlinear time-invariant, state space models based on Newton's method is presented and applied to the new model structure. This model inversion method is not restricted to minimum phase models. It requires only calculation of the first order derivatives of the state space model and is applicable to multivariable models. For periodic reference signals the method yields a compact implementation in the frequency domain. Moreover it is shown that a bandwidth can be specified up to which learning is allowed when using this inversion method in the iterative learning control procedure. Experimental results for a nonlinear single-input-single-output system corresponding to a quarter car on a hydraulic test rig are presented. It is shown that the new nonlinear approach outperforms the linear iterative learning control approach which is currently used in the automotive industry on durability test rigs.
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...... is independent from the wind farm size and is suitable for the real-time control of the wind farm with ESS....
Guaranteed Cost Control for Uncertain Nonlinear Time-Delay Neutral Systems Based on T-S Fuzzy Model
Institute of Scientific and Technical Information of China (English)
无
2005-01-01
The problem of guaranteed cost fuzzy controller is studied for a class of nonlinear time-delay neutral systems with norm-bounded uncertainty based on T-S model. The sufficient conditions are first derived for the existence of guaranteed cost fuzzy controllers. These sufficient conditions are equivalent to a kind of linear matrix inequalities. Furthermore, a convex optimization problem with LMI constraints is formulated to design the optimal guaranteed cost controller.
DEFF Research Database (Denmark)
Guo, Xiaoqiang; Lu, Zhigang; Wang, Baocheng
2014-01-01
System modeling and stability analysis is one of the most important issues of inverter-dominated microgrids. It is useful to determine the system stability and optimize the control parameters. The complete small signal models for the inverter-dominated microgrids have been developed which are very...... accurate and could be found in literature. However, the modeling procedure will become very complex when the number of inverters in microgrid is large. One possible solution is to use the reduced-order small signal models for the inverter-dominated microgrids. Unfortunately, the reduced-order small signal...... 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...
Modelling, controlling, predicting blackouts
Wang, Chengwei; Baptista, Murilo S
2016-01-01
The electric power system is one of the cornerstones of modern society. One of its most serious malfunctions is the blackout, a catastrophic event that may disrupt a substantial portion of the system, playing havoc to human life and causing great economic losses. Thus, understanding the mechanisms leading to blackouts and creating a reliable and resilient power grid has been a major issue, attracting the attention of scientists, engineers and stakeholders. In this paper, we study the blackout problem in power grids by considering a practical phase-oscillator model. This model allows one to simultaneously consider different types of power sources (e.g., traditional AC power plants and renewable power sources connected by DC/AC inverters) and different types of loads (e.g., consumers connected to distribution networks and consumers directly connected to power plants). We propose two new control strategies based on our model, one for traditional power grids, and another one for smart grids. The control strategie...
Model-based control structure design of a full-scale WWTP under the retrofitting process.
Machado, V C; Lafuente, J; Baeza, J A
2015-01-01
The anoxic-oxic (A/O) municipal wastewater treatment plant (WWTP) of Manresa (Catalonia, Spain) was studied for a possible conversion to an anaerobic/anoxic/oxic (A2/O) configuration to promote enhanced biological phosphorus removal. The control structure had to be redesigned to satisfy the new necessity to control phosphorus concentration, besides ammonium and nitrate concentrations (main pollutant concentrations). Thereby, decentralized control structures with proportional-integral-derivative (PID) controllers and centralized control structures with model-predictive controllers (MPC) were designed and tested. All the designed control structures had their performance systematically tested regarding effluent quality and operating costs. The centralized control structure, A2/O-3-MPC, achieved the lowest operating costs with the best effluent quality using the A2/O plant configuration for the Manresa WWTP. The controlled variables used in this control structure were ammonium in the effluent, nitrate at the end of the anoxic zone and phosphate at the end of the anaerobic zone, while the manipulated variables were the internal and external recycle flow rates and the dissolved oxygen setpoint in the aerobic reactors.
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.
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.
Evaluation of outbreak response immunization in the control of pertussis using agent-based modeling
Directory of Open Access Journals (Sweden)
Alexander Doroshenko
2016-08-01
Full Text Available Background Pertussis control remains a challenge due to recently observed effects of waning immunity to acellular vaccine and suboptimal vaccine coverage. Multiple outbreaks have been reported in different ages worldwide. For certain outbreaks, public health authorities can launch an outbreak response immunization (ORI campaign to control pertussis spread. We investigated effects of an outbreak response immunization targeting young adolescents in averting pertussis cases. Methods We developed an agent-based model for pertussis transmission representing disease mechanism, waning immunity, vaccination schedule and pathogen transmission in a spatially-explicit 500,000-person contact network representing a typical Canadian Public Health district. Parameters were derived from literature and calibration. We used published cumulative incidence and dose-specific vaccine coverage to calibrate the model’s epidemiological curves. We endogenized outbreak response by defining thresholds to trigger simulated immunization campaigns in the 10–14 age group offering 80% coverage. We ran paired simulations with and without outbreak response immunization and included those resulting in a single ORI within a 10-year span. We calculated the number of cases averted attributable to outbreak immunization campaign in all ages, in the 10–14 age group and in infants. The count of cases averted were tested using Mann–Whitney U test to determine statistical significance. Numbers needed to vaccinate during immunization campaign to prevent a single case in respective age groups were derived from the model. We varied adult vaccine coverage, waning immunity parameters, immunization campaign eligibility and tested stronger vaccination boosting effect in sensitivity analyses. Results 189 qualified paired-runs were analyzed. On average, ORI was triggered every 26 years. On a per-run basis, there were an average of 124, 243 and 429 pertussis cases averted across all age
Hou, Zhicheng; Fantoni, Isabelle; Zavala-Río, Arturo
2013-01-01
International audience; This paper concerns the leader-follower multiple agent formation with nonlinear and coupled individual dynamics. We address the problem of multi-agent formation control by proposing a decentralized control strategy. The agents in the formation are quad-rotors UAVs. By attributing the high-order nonlinear and unmodelled dynamics as uncertainties, we propose a switching singular system model to represent the formation of the multiple UAVs system with switching topology. ...
Agent-Based Models and Optimal Control in Biology: A Discrete Approach
2012-01-01
different parts of the human body to cure diseases such as hypertension, cancer, or heart disease. And we need to control microbes for the efficient...dynamics to remain the same, and how we can verify that this is indeed the case. Since we are using the model with a specific control objective in mind ...similar to the approach pioneered by Descartes and his introduction of a coordinate system. In the plane, for instance, a Cartesian coordinate system
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.
A semiparametric Wald statistic for testing logistic regression models based on case-control data
Institute of Scientific and Technical Information of China (English)
WAN ShuWen
2008-01-01
We propose a semiparametric Wald statistic to test the validity of logistic regression models based on case-control data.The test statistic is constructed using a semiparametric ROC curve estimator and a nonparametric ROC curve estimator.The statistic has an asymptotic chi-squared distribution and is an alternative to the Kolmogorov-Smirnov-type statistic proposed by Qin and Zhang in 1997,the chi-squared-type statistic proposed by Zhang in 1999 and the information matrix test statistic proposed by Zhang in 2001.The statistic is easy to compute in the sense that it requires none of the following methods:using a bootstrap method to find its critical values,partitioning the sample data or inverting a high-dimensional matrix.We present some results on simulation and on analysis of two real examples.Moreover,we discuss how to extend our statistic to a family of statistics and how to construct its Kolmogorov-Smirnov counterpart.
FORCE FEEDBACK MODEL OF ELECTRO-HYDRAULIC SERVO TELE-OPERATION ROBOT BASED ON VELOCITY CONTROL
Institute of Scientific and Technical Information of China (English)
无
2008-01-01
The tele-operation robotic system which consists of an excavator as the construction robot, and two joysticks for operating the robot from a safe place are useful for performing restoration in damaged areas. In order to accomplish a precise task, the operator needs to feel a realistic sense of task force brought about from a feedback force between the fork glove of slave robot and unfamiliar environment. A novel force feedback model is proposed based on velocity control of cylinder to determine environment force acting" on fork glove. Namely, the feedback force is formed by the error of displacement of joystick with velocity and driving force of piston, and the gain is calculated by the driving force and threshold of driving force of hydraulic cylinder. Moreover, the variable gain improved algorithm is developed to overcome the defect for grasping soft object. Experimental results for fork glove freedom of robotic system are provided to demonstrate the developed algorithm is available for grasping soft object.
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 th....... 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 been chosen as an application example of this modeling technique....
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.
A community-based thalassemia prevention and control model in northern Thailand.
Pansatiankul, Boonchian; Saisorn, Supachai
2003-08-01
To describe a community-based model for prevention and control of thalassemias and haemoglobinopathies in northern Thailand. Operational research composed of two components. First, a model to test whether thalassemic cases and carriers could be retrospectively detected from school children. Second, a model for prevention of prospective cases of thalassemic babies among pregnant women. Phan District of Chiang Rai Province in northern Thailand. Component one: 5,617 preschool children and 21,123 school children were screened during May and July 1997. Component two: 256 pregnant women, 16 weeks or less gestation were screened during January and December 1997. Component one: Sub-district public health officers and school teachers were trained to use pictures and simple clinical examination to detect suspected thalassemics among preschool and school children. Suspected cases were then referred for further clinical examination and blood testing. Blood smear examination was done at the Phan Community Hospital but Hb typing lusing on electrophoresis was done at the provincial hospital. The cellulose acetate was sent for re-reading at the Department of Medical Sciences. Component two: Osmotic fragility (OF) and dichlorophenol-indolephenol (DCIP) tests were abol in pregnant women (thalassemia diseases. Their parents were counseled. Forty couples were determined to need some form of family planning and 39 (97.5%) accepted. In Component two: 256 pregnant women were screened and 56 were found to be carriers. Only 45 husbands could be located and Hb typed. Five couples were determined to require prenatal diagnosis (PND). One happened to undergo therapeutic abortion because of HIV infection in the mother without PND. Of the four who underwent PND, one was found to have a fetus with major thalassemia. However, this couple refused therapeutic abortion because of religious reasons. This study combined both prospective and retrospective approaches and can be considered successful
Energy Technology Data Exchange (ETDEWEB)
Zheng Yongai, E-mail: zhengyongai@163.co [Department of Computer, Yangzhou University, Yangzhou, 225009 (China); Nian Yibei [School of Energy and Power Engineering, Yangzhou University, Yangzhou, 225009 (China); Wang Dejin [Department of Computer, Yangzhou University, Yangzhou, 225009 (China)
2010-12-01
In this Letter, a kind of novel model, called the generalized Takagi-Sugeno (T-S) fuzzy model, is first developed by extending the conventional T-S fuzzy model. Then, a simple but efficient method to control fractional order chaotic systems is proposed using the generalized T-S fuzzy model and adaptive adjustment mechanism (AAM). Sufficient conditions are derived to guarantee chaos control from the stability criterion of linear fractional order systems. The proposed approach offers a systematic design procedure for stabilizing a large class of fractional order chaotic systems from the literature about chaos research. The effectiveness of the approach is tested on fractional order Roessler system and fractional order Lorenz system.
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...
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
LMI-Based Fuzzy Optimal Variance Control of Airfoil Model Subject to Input Constraints
Swei, Sean S.M.; Ayoubi, Mohammad A.
2017-01-01
This paper presents a study of fuzzy optimal variance control problem for dynamical systems subject to actuator amplitude and rate constraints. Using Takagi-Sugeno fuzzy modeling and dynamic Parallel Distributed Compensation technique, the stability and the constraints can be cast as a multi-objective optimization problem in the form of Linear Matrix Inequalities. By utilizing the formulations and solutions for the input and output variance constraint problems, we develop a fuzzy full-state feedback controller. The stability and performance of the proposed controller is demonstrated through its application to the airfoil flutter suppression.
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...
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.
Nonlinear Model-Based Predictive Control applied to Large Scale Cryogenic Facilities
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....
Model-Based Self-Tuning Multiscale Method for Combustion Control
Le, Dzu, K.; DeLaat, John C.; Chang, Clarence T.; Vrnak, Daniel R.
2006-01-01
A multi-scale representation of the combustor dynamics was used to create a self-tuning, scalable controller to suppress multiple instability modes in a liquid-fueled aero engine-derived combustor operating at engine-like conditions. Its self-tuning features designed to handle the uncertainties in the combustor dynamics and time-delays are essential for control performance and robustness. The controller was implemented to modulate a high-frequency fuel valve with feedback from dynamic pressure sensors. This scalable algorithm suppressed pressure oscillations of different instability modes by as much as 90 percent without the peak-splitting effect. The self-tuning logic guided the adjustment of controller parameters and converged quickly toward phase-lock for optimal suppression of the instabilities. The forced-response characteristics of the control model compare well with those of the test rig on both the frequency-domain and the time-domain.
Srivastava, Priyaka; Kraus, Jeff; Murawski, Robert; Golden, Bertsel, Jr.
2015-01-01
NASAs Space Communications and Navigation (SCaN) program manages three active networks: the Near Earth Network, the Space Network, and the Deep Space Network. These networks simultaneously support NASA missions and provide communications services to customers worldwide. To efficiently manage these resources and their capabilities, a team of student interns at the NASA Glenn Research Center is developing a distributed system to model the SCaN networks. Once complete, the system shall provide a platform that enables users to perform capacity modeling of current and prospective missions with finer-grained control of information between several simulation and modeling tools. This will enable the SCaN program to access a holistic view of its networks and simulate the effects of modifications in order to provide NASA with decisional information. The development of this capacity modeling system is managed by NASAs Strategic Center for Education, Networking, Integration, and Communication (SCENIC). Three primary third-party software tools offer their unique abilities in different stages of the simulation process. MagicDraw provides UMLSysML modeling, AGIs Systems Tool Kit simulates the physical transmission parameters and de-conflicts scheduled communication, and Riverbed Modeler (formerly OPNET) simulates communication protocols and packet-based networking. SCENIC developers are building custom software extensions to integrate these components in an end-to-end space communications modeling platform. A central control module acts as the hub for report-based messaging between client wrappers. Backend databases provide information related to mission parameters and ground station configurations, while the end user defines scenario-specific attributes for the model. The eight SCENIC interns are working under the direction of their mentors to complete an initial version of this capacity modeling system during the summer of 2015. The intern team is composed of four students in
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
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.
Theory of agent-based market models with controlled levels of greed and anxiety
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.
GA-Based Model Predictive Control of Semi-Active Landing Gear
Institute of Scientific and Technical Information of China (English)
WU Dong-su; GU Hong-bin; LIU Hui
2007-01-01
Semi-active landing gear can provide good performance of both landing impact and taxi situation, and has the ability for adapting to various ground conditions and operational conditions. A kind of Nonlinear Model Predictive Control algorithm (NMPC) for semi-active landing gears is developed in this paper. The NMPC algorithm uses Genetic Algorithm (GA) as the optimization technique and chooses damping performance of landing gear at touch down to be the optimization object. The valve's rate and magnitude limitations are also considered in the controller's design. A simulation model is built for the semi-active landing gear's damping process at touchdown. Drop tests are carried out on an experimental passive landing gear systerm to validate the parameters of the simulation model. The result of numerical simulation shows that the isolation of impact load at touchdown can be significantly improved compared to other control algorithms. The strongly nonlinear dynamics of semi-active landing gear coupled with control valve's rate and magnitude limitations are handled well with the proposed controller.
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.
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.
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...
Directory of Open Access Journals (Sweden)
Liying Zhang
2013-11-01
Full Text Available Compared with the conventional control systems, networked control systems (NCSs are more open to the external network. As a result, they are more vulnerable to attacks from disgruntled insiders or malicious cyber-terrorist organizations. Therefore, the security issues of NCSs have been receiving a lot of attention recently. In this brief, we review the existing literature on security issues of NCSs and propose some security solutions for the DC motor networked control system. The typical Data Encryption Standard (DES algorithm is adopted to implement data encryption and decryption. Furthermore, we design a Detection and Reaction Mechanism (DARM on the basis of DES algorithm and the improved grey prediction model. Finally, our proposed security solutions are tested with the established models of deception and DOS attacks. According to the results of numerical experiments, it's clear to see the great feasibility and effectiveness of the proposed solutions above.
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
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 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.
Directory of Open Access Journals (Sweden)
Iman Sharifi
2014-12-01
Full Text Available In this paper, a singularity-free control methodology for the safe robot-human interaction is proposed using a hybrid control technique in robotic rehabilitation applications. With the use of max-plus algebra, a hybrid controller is designed to guarantee feasible robot motion in the vicinity of the kinematic singularities or going through and staying at the singular configuration. The approach taken in this paper is based on model-free impedance control and hence does not require any information about the model except the upper bounds on the system matrix. The stability of the approach is investigated using multiple Lyapunov function theory. The proposed control algorithm is applied to PUMA 560 robot arm, a six-axis industrial robot. The results demonstrate the validity of the proposed control scheme.
Modelling and controlling hydropower plants
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...
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.
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.
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.
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
Institute of Scientific and Technical Information of China (English)
Yong-gang PENG; Jun WANG; Wei WEI
2014-01-01
In view of the high energy consumption and low response speed of the traditional hydraulic system for an injection molding machine, a servo motor driven constant pump hydraulic system is designed for a precision injection molding process, which uses a servo motor, a constant pump, and a pressure sensor, instead of a common motor, a constant pump, a pressure pro-portion valve, and a flow proportion valve. A model predictive control strategy based on neurodynamic optimization is proposed to control this new hydraulic system in the injection molding process. Simulation results showed that this control method has good control precision and quick response.
Analysis of Demand Control Policies using an Agent-based Multi-layer Power System Model
Kühnlenz, Florian; Nardelli, Pedro H. J.; Alves, Hirley
2016-01-01
This paper studies how the communication network affects the power utilization and fairness in a simplified power system model, composed by three coupled layers: physical, communication and regulatory. Using an agent-based approach, we build a scenario where individuals may cooperate (by removing a load) or not (by keeping their loads or adding one more). The agent decision reflects its desire of maximizing the delivered power based on its internal state, its global state perception, a random...
Shan, Bonan; Wang, Jiang; Deng, Bin; Wei, Xile; Yu, Haitao; Zhang, Zhen; Li, Huiyan
2016-07-01
This paper proposes an epilepsy detection and closed-loop control strategy based on Particle Swarm Optimization (PSO) algorithm. The proposed strategy can effectively suppress the epileptic spikes in neural mass models, where the epileptiform spikes are recognized as the biomarkers of transitions from the normal (interictal) activity to the seizure (ictal) activity. In addition, the PSO algorithm shows capabilities of accurate estimation for the time evolution of key model parameters and practical detection for all the epileptic spikes. The estimation effects of unmeasurable parameters are improved significantly compared with unscented Kalman filter. When the estimated excitatory-inhibitory ratio exceeds a threshold value, the epileptiform spikes can be inhibited immediately by adopting the proportion-integration controller. Besides, numerical simulations are carried out to illustrate the effectiveness of the proposed method as well as the potential value for the model-based early seizure detection and closed-loop control treatment design.
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
not only can avoid the active/reactive power coupling, but also it may reduce the output voltage drop of the PCC voltage. The proposed adjustable complex virtual impedance loop is putted into the conventional P/Q droop control to overcome the difficulty of getting the line impedance, which may change...... 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....
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.
Cancellation-Based Nonquadratic Controller Design for Nonlinear Systems via Takagi-Sugeno Models.
Gonzalez, Temoatzin; Bernal, Miguel; Sala, Antonio; Aguiar, Braulio
2016-08-12
This paper is concerned with nonquadratic conditions for stabilization of continuous-time nonlinear systems via exact Takagi-Sugeno models and generalized fuzzy Lyapunov functions. The approach hereby proposed feedback to the time derivatives of the membership functions through a multi-index control law that cancels out the terms responsible of former a priori local conditions. Thus, a nonquadratic controller design in the form of linear matrix inequalities is achieved; it does not require bounds on the time derivatives nor any extra parameters. The examples included are shown to outperform former approaches.
POPEYE: A production rule-based model of multitask supervisory control (POPCORN)
Townsend, James T.; Kadlec, Helena; Kantowitz, Barry H.
1988-01-01
Recent studies of relationships between subjective ratings of mental workload, performance, and human operator and task characteristics have indicated that these relationships are quite complex. In order to study the various relationships and place subjective mental workload within a theoretical framework, we developed a production system model for the performance component of the complex supervisory task called POPCORN. The production system model is represented by a hierarchial structure of goals and subgoals, and the information flow is controlled by a set of condition-action rules. The implementation of this production system, called POPEYE, generates computer simulated data under different task difficulty conditions which are comparable to those of human operators performing the task. This model is the performance aspect of an overall dynamic psychological model which we are developing to examine and quantify relationships between performance and psychological aspects in a complex environment.
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.)
An Optimization Model of the Single-Leg Air Cargo Space Control Based on Markov Decision Process
Directory of Open Access Journals (Sweden)
Chun-rong Qin
2012-01-01
Full Text Available Based on the single-leg air cargo issues, we establish a dynamic programming model to consider the overbooking and space inventory control problem. We analyze the structure of optimal booking policy for every kind of booking requests and show that the optimal booking decision is of threshold type (known as booking limit policy. Our research provides a theoretical support for the air cargo space control.
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...... the dynamics of electrical and communication systems interact with each other. Apart from that, the communication characteristics also affect the dynamics of the system. Due to discrete nature of information exchange in communication network, Laplace domain analysis is not accurate enough for this kind...
A Physics-Based Charge-Control Model for InP DHBT Including Current-Blocking Effect
Institute of Scientific and Technical Information of China (English)
GE Ji; JIN Zhi; SU Yong-Bo; CHENG Wei; WANG Xian-Wai; CHEN Gao-Peng; LIU Xin-Yu
2009-01-01
We develop a physics-based charge-control InP double heterojunction bipolar transistor model including three important effects: current blocking, mobile-charge modulation of the base-collector capacitance and velocity-field modulation in the transit time. The bias-dependent base-collector depletion charge is obtained analytically, which takes into account the mobile-charge modulation. Then, a measurement based voltage-dependent transit time formulation is implemented. As a result, over a wide range of biases, the developed model shows good agreement between the modeled and measured S-parameters and cutoff frequency. Also, the model considering current blocking effect demonstrates more accurate prediction of the output characteristics than conventional vertical bipolar inter company results.
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.
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.
Institute of Scientific and Technical Information of China (English)
Long DI; Zongli LIN
2014-01-01
Active magnetic bearings (AMBs) have found a wide range of applications in high-speed rotating machinery industry. The instability and nonlinearity of AMBs make controller designs difficult, and when AMBs are coupled with a flexible rotor, the resulting complex dynamics make the problems of stabilization and disturbance rejection, which are critical for a stable and smooth operation of the rotor AMB system, even more difficult. Proportional-integral-derivative (PID) control dominates the current AMB applications in the field. Even though PID controllers are easy to implement, there are critical performance limitations associated with them that prevent the more advanced applications of AMBs, which usually require stronger robustness and performance offered by modern control methods such as H-infinity control andμ-synthesis. However, these advanced control designs rely heavily on the relatively accurate plant models and uncertainty characterizations, which are sometimes difficult to obtain. In this paper, we explore and report on the use of the characteristic model based all-coefficient adaptive control method to stabilize a flexible rotor AMB test rig. In spite of the simple structure of such a characteristic model based all-coefficient adaptive controller, both simulation and experimental results show its strong performance.
Directory of Open Access Journals (Sweden)
de la Torre Bartolomé
2006-11-01
Full Text Available Abstract Background Previous studies of the relationship between job strain and blood or saliva cortisol levels have been small and based on selected occupational groups. Our aim was to examine the association between job strain and saliva cortisol levels in a population-based study in which a number of potential confounders could be adjusted for. Methods The material derives from a population-based study in Stockholm on mental health and its potential determinants. Two data collections were performed three years apart with more than 8500 subjects responding to a questionnaire in both waves. In this paper our analyses are based on 529 individuals who held a job, participated in both waves as well as in an interview linked to the second wave. They gave saliva samples at awakening, half an hour later, at lunchtime and before going to bed on a weekday in close connection with the interview. Job control and job demands were assessed from the questionnaire in the second wave. Mixed models were used to analyse the association between the demand control model and saliva cortisol. Results Women in low strain jobs (high control and low demands had significantly lower cortisol levels half an hour after awakening than women in high strain (low control and high demands, active (high control and high demands or passive jobs (low control and low demands. There were no significant differences between the groups during other parts of the day and furthermore there was no difference between the job strain, active and passive groups. For men, no differences were found between demand control groups. Conclusion This population-based study, on a relatively large sample, weakly support the hypothesis that the demand control model is associated with saliva cortisol concentrations.
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 multidimensional effects are calculated using empirical correlations. Transformations of the conservation equations into new variables, artificial dissipation for dissipating acoustic phenomena, and an asymmetric interpolation method for minimising numerical diffusion and non physical temperature oscillations...
Directory of Open Access Journals (Sweden)
Jia-Qiang Yang
2016-04-01
Full Text Available This article focuses on the design of a control system for intelligent prostheses. Learning vector quantization neural network–based model reference adaptive control method is employed to implement real-time trajectory tracking and damp torque control of intelligent lower-limb prosthesis. The method is then analyzed and proposed. A model reference control system is first built with two learning vector quantization neural networks. One neural network is used for output prediction, and the other is used for input control. The angle information of the prosthetic knee joint is utilized to train these two neural networks with the given learning algorithm. The testing results of different movement patterns verify the effectiveness of the proposed method and its suitability for intelligent lower-limb prostheses.
Back stepping-Based-PID-Controller Designed for an Artificial Pancreas model
Directory of Open Access Journals (Sweden)
ShaimaMahmou Mahdi
2011-01-01
Full Text Available Artificial pancreas is simulated to handle Type I diabetic patients under intensive care by automatically controlling the insulin infusion rate. A Backstepping technique is used to apply the effect of PID controller to blood glucose level since there is no direct relation between insulin infusion (the manipulated variable and glucose level in Bergmans system model subjected to an oral glucose tolerance test by applying a meal translated into a disturbance. Backstepping technique is usually recommended to stabilize and control the states of Bergman's class of nonlinear systems. The results showed a very satisfactory behavior of glucose deviation to a sudden rise represented by the meal that increase the blood glucose
Dynamic-Phasor-Based Nonlinear Modelling of AC Islanded Microgrids Under Droop Control
DEFF Research Database (Denmark)
Mariani, Valerio; Vasca, Francesco; Guerrero, Josep M.
2014-01-01
dynamics that are also affected by the control parameters. This paper shows how a dynamic phasor approach can be used to derive a closed loop model of the microgrid and then to perform an eigenvalues analysis that highlights how instabilities arise for suitable values of the frequency droop control...... parameter. Further, it is shown that the full order system is well approximated by a reduced order system which captures the inverters phase and line currents dynamics.......Droop controlled inverters are widely used in islanded microgrids to interface distributed energy resources and to provide for the loads active and reactive powers demand. In this scenario, an important issue is to assess the stability of the microgrids taking into account the network and currents...
DEFF Research Database (Denmark)
Manoonpong, Poramate; Dasgupta, Sakyasingha; Goldschmidt, Dennis
2014-01-01
for generating basic rhythmic patterns and coordinated movements, 2) reservoir-based adaptive forward models with efference copies for sensory prediction as well as state estimation, and 3) searching and elevation control for adapting the movement of an individual leg to deal with different environmental...
Kane Method Based Dynamics Modeling and Control Study for Space Manipulator Capturing a Space Target
Directory of Open Access Journals (Sweden)
Yanhua Han
2016-01-01
Full Text Available Dynamics modeling and control problem of a two-link manipulator mounted on a spacecraft (so-called carrier freely flying around a space target on earth’s circular orbit is studied in the paper. The influence of the carrier’s relative movement on its manipulator is considered in dynamics modeling; nevertheless, that of the manipulator on its carrier is neglected with the assumption that the mass and inertia moment of the manipulator is far less than that of the carrier. Meanwhile, we suppose that the attitude control system of the carrier guarantees its side on which the manipulator is mounted points accurately always the space target during approaching operation. The ideal constraint forces can be out of consideration in dynamics modeling as Kane method is used. The path functions of the manipulator’s end-effector approaching the space target as well as the manipulator’s joints control torque functions are programmed to meet the soft touch requirement that the end-effector’s relative velocity to the space target is zero at touch moment. Numerical simulation validation is conducted finally.
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
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.
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.
Kuppan Chetty, R. M.; Singaperumal, M.; Nagarajan, T.
2007-12-01
The coordinated motion of group of autonomous mobile robots for the achievement of goal has been of high interest since the last decade. Previous research works have revealed that one of the essential problems in the area is to plan, navigate and coordinate the motion of robots, avoiding obstacles as well as each other while still achieving the goal. In this paper, Behavior Based approach for the control of distributed networked robotic system, concentrated towards the navigation, planning and coordination between them in unknown complex environment is addressed. A layered behavior based control architecture, with the basic behaviors of Message passing, Obstacle avoidance, Safe wandering and Pit sensing have been designed and assigned to the individual robotic systems to form a navigation algorithm. Validation of this guidance algorithm is carried out through simulations using SIMULINK/State flow.
Integrated Methodology for Information System Change Control Based on Enterprise Architecture Models
Directory of Open Access Journals (Sweden)
Pirta Ruta
2015-12-01
Full Text Available The information system (IS change management and governance, according to the best practices, are defined and described in several international methodologies, standards, and frameworks (ITIL, COBIT, ValIT etc.. These methodologies describe IS change management aspects from the viewpoint of their particular enterprise resource management area. The areas are mainly viewed in a partly isolated environment, and the integration of the existing methodologies is insufficient for providing unified and controlled methodological support for holistic IS change management. In this paper, an integrated change management methodology is introduced. The methodology consists of guidelines for IS change control by integrating the following significant resource management areas – information technology (IT governance, change management and enterprise architecture (EA change management. In addition, the methodology includes lists of controls applicable at different phases. The approach is based on re-use and fusion of principles used by related methodologies as well as on empirical observations about typical IS change management mistakes in enterprises.
Green, David; Dunaway, Brad; Reaper, Jerome
2005-05-01
The Virtual Testbed for Advanced Command and Control Concepts (VTAC) program is performing research and development efforts leading to the creation of a testbed for new Command and Control (C2) processes, subprocesses and embedded automated systems and subsystems. This testbed will initially support the capture and modeling of existing C2 processes/subprocesses. Having modeled these at proper levels of abstraction, proposed revisions or replacements to processes, systems and subsystems can be evaluated within a virtual workspace that integrates human operators and automated systems in the context of a larger C2 process. By utilizing such a testbed early in the development cycle, expected improvements resulting from specific revisions or replacements can be quantitatively established. Crossover effects resulting from changes to one or more interrelated processes can also be measured. Quantified measures of improvement can then be provided to decision makers for use in cost-to-performance benefits analysis prior to implementing proposed revisions, replacements, or a sequence of planned enhancements. This paper first presents a high-level view of the VTAC project, followed by a discussion of an example C2 process that was captured, abstracted, and modeled. The abstraction approach, model implementation, and simulations results are covered in detail.