WorldWideScience

Sample records for non-predictive control model

  1. Model Process Control Language

    Data.gov (United States)

    National Aeronautics and Space Administration — The MPC (Model Process Control) language enables the capture, communication and preservation of a simulation instance, with sufficient detail that it can be...

  2. Stochastic Control - External Models

    DEFF Research Database (Denmark)

    Poulsen, Niels Kjølstad

    2005-01-01

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

  3. Aeroservoelasticity modeling and control

    CERN Document Server

    Tewari, Ashish

    2015-01-01

    This monograph presents the state of the art in aeroservoelastic (ASE) modeling and analysis and develops a systematic theoretical and computational framework for use by researchers and practicing engineers. It is the first book to focus on the mathematical modeling of structural dynamics, unsteady aerodynamics, and control systems to evolve a generic procedure to be applied for ASE synthesis. Existing robust, nonlinear, and adaptive control methodology is applied and extended to some interesting ASE problems, such as transonic flutter and buffet, post-stall buffet and maneuvers, and flapping flexible wing. The author derives a general aeroservoelastic plant via the finite-element structural dynamic model, unsteady aerodynamic models for various regimes in the frequency domain, and the associated state-space model by rational function approximations. For more advanced models, the full-potential, Euler, and Navier-Stokes methods for treating transonic and separated flows are also briefly addressed. Essential A...

  4. Fuzzy Control Teaching Models

    Directory of Open Access Journals (Sweden)

    Klaus-Dietrich Kramer

    2016-05-01

    Full Text Available Many degree courses at technical universities include the subject of control systems engineering. As an addition to conventional approaches Fuzzy Control can be used to easily find control solutions for systems, even if they include nonlinearities. To support further educational training, models which represent a technical system to be controlled are required. These models have to represent the system in a transparent and easy cognizable manner. Furthermore, a programming tool is required that supports an easy Fuzzy Control development process, including the option to verify the results and tune the system behavior. In order to support the development process a graphical user interface is needed to display the fuzzy terms under real time conditions, especially with a debug system and trace functionality. The experiences with such a programming tool, the Fuzzy Control Design Tool (FHFCE Tool, and four fuzzy teaching models will be presented in this paper. The methodical and didactical objective in the utilization of these teaching models is to develop solution strategies using Computational Intelligence (CI applications for Fuzzy Controllers in order to analyze different algorithms of inference or defuzzyfication and to verify and tune those systems efficiently.

  5. Model-free control

    Science.gov (United States)

    Fliess, Michel; Join, Cédric

    2013-12-01

    'Model-free control'and the corresponding 'intelligent' PID controllers (iPIDs), which already had many successful concrete applications, are presented here for the first time in an unified manner, where the new advances are taken into account. The basics of model-free control is now employing some old functional analysis and some elementary differential algebra. The estimation techniques become quite straightforward via a recent online parameter identification approach. The importance of iPIs and especially of iPs is deduced from the presence of friction. The strange industrial ubiquity of classic PIDs and the great difficulty for tuning them in complex situations is deduced, via an elementary sampling, from their connections with iPIDs. Several numerical simulations are presented which include some infinite-dimensional systems. They demonstrate not only the power of our intelligent controllers but also the great simplicity for tuning them.

  6. Active control: Wind turbine model

    Energy Technology Data Exchange (ETDEWEB)

    Bindner, Henrik

    1999-07-01

    This report is a part of the reporting of the work done in the project `Active Control of Wind Turbines`. This project aim is to develop a simulation model for design of control systems for turbines with pitch control and to use that model to design controllers. This report describes the model developed for controller design and analysis. Emphasis has been put on establishment of simple models describing the dynamic behavior of the wind turbine in adequate details for controller design. This has been done with extensive use of measurements as the basis for selection of model complexity and model validation as well as parameter estimation. The model includes a simple model of the structure of the turbine including tower and flapwise blade bending, a detailed model of the gear box and induction generator, a linearized aerodynamic model including modelling of induction lag and actuator and sensor models. The models are all formulated as linear differential equations. The models are validated through comparisons with measurements performed on a Vestas WD 34 400 kW wind turbine. It is shown from a control point of view simple linear models can be used to describe the dynamic behavior of a pitch controlled wind turbine. The model and the measurements corresponds well in the relevant frequency range. The developed model is therefore applicable for controller design. (au) EFP-91. 18 ills., 22 refs.

  7. Active control: Wind turbine model

    DEFF Research Database (Denmark)

    Bindner, H.

    1999-01-01

    This report is a part of the reporting of the work done in the project 'Active Control of Wind Turbines'. This project aim is to develop a simulation model for design of control systems for turbines with pitch control and to use that model to designcontrollers. This report describes the model...... validation as well as parameter estimation. The model includes a simple model of the structure of the turbine including tower and flapwise blade bending,a detailed model of the gear box and induction generator, a linearized aerodynamic model including modelling of induction lag and actuator and sensor models...

  8. Controlling chaos in Internet congestion control model

    International Nuclear Information System (INIS)

    Chen Liang; Wang Xiaofan; Han Zhengzhi

    2004-01-01

    The TCP end-to-end congestion control plus RED router queue management can be modeled as a discrete-time dynamical system, which may create complex bifurcating and chaotic behavior. Based on the basic features of the TCP-RED model, we propose a time-dependent delayed feedback control algorithm to control chaos in the system by perturbing the accessible RED parameter p max . This method is able to stabilized a router queue occupancy at a level without knowing the exact knowledge of the network. Further, we study the situation of the presence of the UDP traffic

  9. Controlling chaos in Internet congestion control model

    Energy Technology Data Exchange (ETDEWEB)

    Chen Liang E-mail: chenmoon110@yahoo.com.cn; Wang Xiaofan; Han Zhengzhi

    2004-07-01

    The TCP end-to-end congestion control plus RED router queue management can be modeled as a discrete-time dynamical system, which may create complex bifurcating and chaotic behavior. Based on the basic features of the TCP-RED model, we propose a time-dependent delayed feedback control algorithm to control chaos in the system by perturbing the accessible RED parameter p{sub max}. This method is able to stabilized a router queue occupancy at a level without knowing the exact knowledge of the network. Further, we study the situation of the presence of the UDP traffic.

  10. Modelling and controlling hydropower plants

    CERN Document Server

    Munoz-Hernandez, German Ardul; Jones, Dewi Ieuan

    2013-01-01

    Hydroelectric power stations are a major source of electricity around the world; understanding their dynamics is crucial to achieving good performance.  Modelling and Controlling Hydropower Plants discusses practical and well-documented cases of modelling and controlling hydropower station modelling and control, focussing on a pumped storage scheme based in Dinorwig, North Wales.  Single-input-single-output and multiple-input-multiple-output models, which cover the linear and nonlinear characteristics of pump-storage hydroelectric power stations, are reviewed. The most important dynamic features are discussed, and the verification of these models by hardware in the loop simulation is described. To show how the performance of a pump-storage hydroelectric power station can be improved, classical and modern controllers are applied to simulated models of the Dinorwig power plant. These include PID, fuzzy approximation, feed-forward and model-based predictive control with linear and hybrid prediction models. Mod...

  11. 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...

  12. Modelling and Control of TCV

    International Nuclear Information System (INIS)

    Sharma, A.S.; Limebeer, D.J.N.; Jaimoukha, I.M.; Lister, J.B.

    2001-11-01

    A new approach to the modelling and control of tokamak fusion reactors is presented. A nonlinear model is derived using the classical arguments of Hamiltonian mechanics and a low-order linear model is derived from it. The modelling process used here addresses flux and energy conservation issues explicitly and self-consistently. The model is of particular value, because it shows the relationship between the initial modelling assumptions and the resulting predictions. The mechanisms behind the creation of uncontrollable modes in tokamak models are discussed. A normalised coprime factorisation controller is developed for the TCV tokamak using the verified linear model. Recent theory is applied to reduce the controller order significantly whilst guaranteeing a priori bounds on the robust stability and performance. The controller is shown to track successfully reference signals that dictate the plasma's shape, position and current. The tests used to verify this were carried out on linear and nonlinear models. (author)

  13. Modelling and Control of TCV

    Energy Technology Data Exchange (ETDEWEB)

    Sharma, A.S.; Limebeer, D.J.N.; Jaimoukha, I.M.; Lister, J.B

    2001-11-01

    A new approach to the modelling and control of tokamak fusion reactors is presented. A nonlinear model is derived using the classical arguments of Hamiltonian mechanics and a low-order linear model is derived from it. The modelling process used here addresses flux and energy conservation issues explicitly and self-consistently. The model is of particular value, because it shows the relationship between the initial modelling assumptions and the resulting predictions. The mechanisms behind the creation of uncontrollable modes in tokamak models are discussed. A normalised coprime factorisation controller is developed for the TCV tokamak using the verified linear model. Recent theory is applied to reduce the controller order significantly whilst guaranteeing a priori bounds on the robust stability and performance. The controller is shown to track successfully reference signals that dictate the plasma's shape, position and current. The tests used to verify this were carried out on linear and nonlinear models. (author)

  14. Modeling and Control for Microgrids

    Science.gov (United States)

    Steenis, Joel

    Traditional approaches to modeling microgrids include the behavior of each inverter operating in a particular network configuration and at a particular operating point. Such models quickly become computationally intensive for large systems. Similarly, traditional approaches to control do not use advanced methodologies and suffer from poor performance and limited operating range. In this document a linear model is derived for an inverter connected to the Thevenin equivalent of a microgrid. This model is then compared to a nonlinear simulation model and analyzed using the open and closed loop systems in both the time and frequency domains. The modeling error is quantified with emphasis on its use for controller design purposes. Control design examples are given using a Glover McFarlane controller, gain scheduled Glover McFarlane controller, and bumpless transfer controller which are compared to the standard droop control approach. These examples serve as a guide to illustrate the use of multi-variable modeling techniques in the context of robust controller design and show that gain scheduled MIMO control techniques can extend the operating range of a microgrid. A hardware implementation is used to compare constant gain droop controllers with Glover McFarlane controllers and shows a clear advantage of the Glover McFarlane approach.

  15. ECONOMIC MODELING STOCKS CONTROL SYSTEM: SIMULATION MODEL

    OpenAIRE

    Климак, М.С.; Войтко, С.В.

    2016-01-01

    Considered theoretical and applied aspects of the development of simulation models to predictthe optimal development and production systems that create tangible products andservices. It isproved that theprocessof inventory control needs of economicandmathematical modeling in viewof thecomplexity of theoretical studies. A simulation model of stocks control that allows make managementdecisions with production logistics

  16. MODEL PREDICTIVE CONTROL FUNDAMENTALS

    African Journals Online (AJOL)

    2012-07-02

    Jul 2, 2012 ... signal based on a process model, coping with constraints on inputs and ... paper, we will present an introduction to the theory and application of MPC with Matlab codes ... section 5 presents the simulation results and section 6.

  17. Frequency control modelling - basics

    DEFF Research Database (Denmark)

    Hansen, Anca Daniela; Sørensen, Poul Ejnar; Zeni, Lorenzo

    2016-01-01

    The purpose of this report is to provide an introduction on how the system balance in an island system can be maintained by controlling the frequency. The power balance differential equation, which is fundamental in understanding the effect on the system frequency of the unbalance between...

  18. Diabetes: Models, Signals and control

    Science.gov (United States)

    Cobelli, C.

    2010-07-01

    Diabetes and its complications impose significant economic consequences on individuals, families, health systems, and countries. The control of diabetes is an interdisciplinary endeavor, which includes significant components of modeling, signal processing and control. Models: first, I will discuss the minimal (coarse) models which describe the key components of the system functionality and are capable of measuring crucial processes of glucose metabolism and insulin control in health and diabetes; then, the maximal (fine-grain) models which include comprehensively all available knowledge about system functionality and are capable to simulate the glucose-insulin system in diabetes, thus making it possible to create simulation scenarios whereby cost effective experiments can be conducted in silico to assess the efficacy of various treatment strategies - in particular I will focus on the first in silico simulation model accepted by FDA as a substitute to animal trials in the quest for optimal diabetes control. Signals: I will review metabolic monitoring, with a particular emphasis on the new continuous glucose sensors, on the crucial role of models to enhance the interpretation of their time-series signals, and on the opportunities that they present for automation of diabetes control. Control: I will review control strategies that have been successfully employed in vivo or in silico, presenting a promise for the development of a future artificial pancreas and, in particular, I will discuss a modular architecture for building closed-loop control systems, including insulin delivery and patient safety supervision layers.

  19. Simple Models for Process Control

    Czech Academy of Sciences Publication Activity Database

    Gorez, R.; Klán, Petr

    2011-01-01

    Roč. 22, č. 2 (2011), s. 58-62 ISSN 0929-2268 Institutional research plan: CEZ:AV0Z10300504 Keywords : process model s * PID control * second order dynamics Subject RIV: JB - Sensors, Measurment, Regulation

  20. Nonlinear Control of Heartbeat Models

    Directory of Open Access Journals (Sweden)

    Witt Thanom

    2011-02-01

    Full Text Available This paper presents a novel application of nonlinear control theory to heartbeat models. Existing heartbeat models are investigated and modified by incorporating the control input as a pacemaker to provide the control channel. A nonlinear feedback linearization technique is applied to force the output of the systems to generate artificial electrocardiogram (ECG signal using discrete data as the reference inputs. The synthetic ECG may serve as a flexible signal source to assess the effectiveness of a diagnostic ECG signal-processing device.

  1. Wind Farms: Modeling and Control

    DEFF Research Database (Denmark)

    Soleimanzadeh, Maryam

    2012-01-01

    is minimized. The controller is practically feasible. Yet, the results on load reduction in this approach are not very significant. In the second strategy, the wind farm control problem has been divided into below rated and above rated wind speed conditions. In the above rated wind speed pitch angle and power....... Distributed controller design commences with formulating the problem, where a structured matrix approach has been put in to practice. Afterwards, an H2 control problem is implemented to obtain the controller dynamics for a wind farm such that the structural loads on wind turbines are minimized.......The primary purpose of this work is to develop control algorithms for wind farms to optimize the power production and augment the lifetime of wind turbines in wind farms. In this regard, a dynamical model for wind farms was required to be the basis of the controller design. In the first stage...

  2. Reflexion and control mathematical models

    CERN Document Server

    Novikov, Dmitry A

    2014-01-01

    This book is dedicated to modern approaches to mathematical modeling of reflexive processes in control. The authors consider reflexive games that describe the gametheoretical interaction of agents making decisions based on a hierarchy of beliefs regarding (1) essential parameters (informational reflexion), (2) decision principles used by opponents (strategic reflexion), (3) beliefs about beliefs, and so on. Informational and reflexive equilibria in reflexive games generalize a series of well-known equilibrium concepts in noncooperative games and models of collective behavior. These models allow posing and solving the problems of informational and reflexive control in organizational, economic, social and other systems, in military applications, etc. (the interested reader will find in the book over 30 examples of possible applications in these fields) and describing uniformly many psychological/sociological phenomena connected with reflexion, viz., implicit control, informational control via the mass media, re...

  3. Global nuclear material control model

    International Nuclear Information System (INIS)

    Dreicer, J.S.; Rutherford, D.A.

    1996-01-01

    The nuclear danger can be reduced by a system for global management, protection, control, and accounting as part of a disposition program for special nuclear materials. The development of an international fissile material management and control regime requires conceptual research supported by an analytical and modeling tool that treats the nuclear fuel cycle as a complete system. Such a tool must represent the fundamental data, information, and capabilities of the fuel cycle including an assessment of the global distribution of military and civilian fissile material inventories, a representation of the proliferation pertinent physical processes, and a framework supportive of national or international perspective. They have developed a prototype global nuclear material management and control systems analysis capability, the Global Nuclear Material Control (GNMC) model. The GNMC model establishes the framework for evaluating the global production, disposition, and safeguards and security requirements for fissile nuclear material

  4. The integrated environmental control model

    Energy Technology Data Exchange (ETDEWEB)

    Rubin, E.S.; Berkenpas, M.B.; Kalagnanam, J.R. [Carnegie Mellon Univ., Pittsburgh, PA (United States)

    1995-11-01

    The capability to estimate the performance and cost of emission control systems is critical to a variety of planning and analysis requirements faced by utilities, regulators, researchers and analysts in the public and private sectors. The computer model described in this paper has been developed for DOe to provide an up-to-date capability for analyzing a variety of pre-combustion, combustion, and post-combustion options in an integrated framework. A unique capability allows performance and costs to be modeled probabilistically, which allows explicit characterization of uncertainties and risks.

  5. Welding process modelling and control

    Science.gov (United States)

    Romine, Peter L.; Adenwala, Jinen A.

    1993-01-01

    The research and analysis performed, and software developed, and hardware/software recommendations made during 1992 in development of the PC-based data acquisition system for support of Welding Process Modeling and Control is reported. A need was identified by the Metals Processing Branch of NASA Marshall Space Flight Center, for a mobile data aquisition and analysis system, customized for welding measurement and calibration. Several hardware configurations were evaluated and a PC-based system was chosen. The Welding Measurement System (WMS) is a dedicated instrument, strictly for the use of data aquisition and analysis. Although the WMS supports many of the functions associated with the process control, it is not the intention for this system to be used for welding process control.

  6. Multiple Model Approaches to Modelling and Control,

    DEFF Research Database (Denmark)

    on the ease with which prior knowledge can be incorporated. It is interesting to note that researchers in Control Theory, Neural Networks,Statistics, Artificial Intelligence and Fuzzy Logic have more or less independently developed very similar modelling methods, calling them Local ModelNetworks, Operating......, and allows direct incorporation of high-level and qualitative plant knowledge into themodel. These advantages have proven to be very appealing for industrial applications, and the practical, intuitively appealing nature of the framework isdemonstrated in chapters describing applications of local methods...... to problems in the process industries, biomedical applications and autonomoussystems. The successful application of the ideas to demanding problems is already encouraging, but creative development of the basic framework isneeded to better allow the integration of human knowledge with automated learning...

  7. Automatic Flight Controller With Model Inversion

    Science.gov (United States)

    Meyer, George; Smith, G. Allan

    1992-01-01

    Automatic digital electronic control system based on inverse-model-follower concept being developed for proposed vertical-attitude-takeoff-and-landing airplane. Inverse-model-follower control places inverse mathematical model of dynamics of controlled plant in series with control actuators of controlled plant so response of combination of model and plant to command is unity. System includes feedback to compensate for uncertainties in mathematical model and disturbances imposed from without.

  8. A Model of Controlled Growth

    Science.gov (United States)

    Bressan, Alberto; Lewicka, Marta

    2018-03-01

    We consider a free boundary problem for a system of PDEs, modeling the growth of a biological tissue. A morphogen, controlling volume growth, is produced by specific cells and then diffused and absorbed throughout the domain. The geometric shape of the growing tissue is determined by the instantaneous minimization of an elastic deformation energy, subject to a constraint on the volumetric growth. For an initial domain with C}^{2,α boundary, our main result establishes the local existence and uniqueness of a classical solution, up to a rigid motion.

  9. Path modeling and process control

    DEFF Research Database (Denmark)

    Høskuldsson, Agnar; Rodionova, O.; Pomerantsev, A.

    2007-01-01

    and having three or more stages. The methods are applied to a process control of a multi-stage production process having 25 variables and one output variable. When moving along the process, variables change their roles. It is shown how the methods of path modeling can be applied to estimate variables...... be performed regarding the foreseeable output property y, and with respect to an admissible range of correcting actions for the parameters of the next stage. In this paper the basic principles of path modeling is presented. The mathematics is presented for processes having only one stage, having two stages...... of the next stage with the purpose of obtaining optimal or almost optimal quality of the output variable. An important aspect of the methods presented is the possibility of extensive graphic analysis of data that can provide the engineer with a detailed view of the multi-variate variation in data....

  10. Planning the unknown: the simultaneity of predictive and non-predictive entrepreneurial strategies

    NARCIS (Netherlands)

    Kraaijenbrink, Jeroen; Ratinho, Tiago; Groen, Arend J.

    2012-01-01

    Two distinct approaches have emerged to categorize entrepreneurial strategies. While some argue that planning is beneficial for entrepreneurs, a growing body of literature argues that non-predictive strategies can also lead to successful outcomes. The effectuation framework gained attention and it

  11. Wind turbine control and model predictive control for uncertain systems

    DEFF Research Database (Denmark)

    Thomsen, Sven Creutz

    as disturbance models for controller design. The theoretical study deals with Model Predictive Control (MPC). MPC is an optimal control method which is characterized by the use of a receding prediction horizon. MPC has risen in popularity due to its inherent ability to systematically account for time...

  12. Model predictive control using fuzzy decision functions

    NARCIS (Netherlands)

    Kaymak, U.; Costa Sousa, da J.M.

    2001-01-01

    Fuzzy predictive control integrates conventional model predictive control with techniques from fuzzy multicriteria decision making, translating the goals and the constraints to predictive control in a transparent way. The information regarding the (fuzzy) goals and the (fuzzy) constraints of the

  13. Multiplicity Control in Structural Equation Modeling

    Science.gov (United States)

    Cribbie, Robert A.

    2007-01-01

    Researchers conducting structural equation modeling analyses rarely, if ever, control for the inflated probability of Type I errors when evaluating the statistical significance of multiple parameters in a model. In this study, the Type I error control, power and true model rates of famsilywise and false discovery rate controlling procedures were…

  14. Model complexity control for hydrologic prediction

    NARCIS (Netherlands)

    Schoups, G.; Van de Giesen, N.C.; Savenije, H.H.G.

    2008-01-01

    A common concern in hydrologic modeling is overparameterization of complex models given limited and noisy data. This leads to problems of parameter nonuniqueness and equifinality, which may negatively affect prediction uncertainties. A systematic way of controlling model complexity is therefore

  15. A discrete control model of PLANT

    Science.gov (United States)

    Mitchell, C. M.

    1985-01-01

    A model of the PLANT system using the discrete control modeling techniques developed by Miller is described. Discrete control models attempt to represent in a mathematical form how a human operator might decompose a complex system into simpler parts and how the control actions and system configuration are coordinated so that acceptable overall system performance is achieved. Basic questions include knowledge representation, information flow, and decision making in complex systems. The structure of the model is a general hierarchical/heterarchical scheme which structurally accounts for coordination and dynamic focus of attention. Mathematically, the discrete control model is defined in terms of a network of finite state systems. Specifically, the discrete control model accounts for how specific control actions are selected from information about the controlled system, the environment, and the context of the situation. The objective is to provide a plausible and empirically testable accounting and, if possible, explanation of control behavior.

  16. Model predictive control for a thermostatic controlled system

    DEFF Research Database (Denmark)

    Shafiei, Seyed Ehsan; Rasmussen, Henrik; Stoustrup, Jakob

    2013-01-01

    This paper proposes a model predictive control scheme to provide temperature set-points to thermostatic controlled cooling units in refrigeration systems. The control problem is formulated as a convex programming problem to minimize the overall operating cost of the system. The foodstuff temperat......This paper proposes a model predictive control scheme to provide temperature set-points to thermostatic controlled cooling units in refrigeration systems. The control problem is formulated as a convex programming problem to minimize the overall operating cost of the system. The foodstuff...

  17. Stochastic models, estimation, and control

    CERN Document Server

    Maybeck, Peter S

    1982-01-01

    This volume builds upon the foundations set in Volumes 1 and 2. Chapter 13 introduces the basic concepts of stochastic control and dynamic programming as the fundamental means of synthesizing optimal stochastic control laws.

  18. Tube Model Predictive Control with an Auxiliary Sliding Mode Controller

    Directory of Open Access Journals (Sweden)

    Miodrag Spasic

    2016-07-01

    Full Text Available This paper studies Tube Model Predictive Control (MPC with a Sliding Mode Controller (SMC as an auxiliary controller. It is shown how to calculate the tube widths under SMC control, and thus how much the constraints of the nominal MPC have to be tightened in order to achieve robust stability and constraint fulfillment. The analysis avoids the assumption of infinitely fast switching in the SMC controller.

  19. Modeling, robust and distributed model predictive control for freeway networks

    NARCIS (Netherlands)

    Liu, S.

    2016-01-01

    In Model Predictive Control (MPC) for traffic networks, traffic models are crucial since they are used as prediction models for determining the optimal control actions. In order to reduce the computational complexity of MPC for traffic networks, macroscopic traffic models are often used instead of

  20. Modelling and Control of a Mobile Robot

    DEFF Research Database (Denmark)

    Christensen, Georg Kronborg

    1998-01-01

    In order to control a mobile robot, kinematic odels as well as dynamic models are required. This parer describes these basic models for an experimental mobile robot under construction at the Department of Control and Engineering Design. A description of a set of trajectory control rules is given...

  1. Predictor-Based Model Reference Adaptive Control

    Science.gov (United States)

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

    2010-01-01

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

  2. Basic Research on Adaptive Model Algorithmic Control

    Science.gov (United States)

    1985-12-01

    Control Conference. Richalet, J., A. Rault, J.L. Testud and J. Papon (1978). Model predictive heuristic control: applications to industrial...pp.977-982. Richalet, J., A. Rault, J. L. Testud and J. Papon (1978). Model predictive heuristic control: applications to industrial processes

  3. Can better modelling improve tokamak control?

    International Nuclear Information System (INIS)

    Lister, J.B.; Vyas, P.; Ward, D.J.; Albanese, R.; Ambrosino, G.; Ariola, M.; Villone, F.; Coutlis, A.; Limebeer, D.J.N.; Wainwright, J.P.

    1997-01-01

    The control of present day tokamaks usually relies upon primitive modelling and TCV is used to illustrate this. A counter example is provided by the successful implementation of high order SISO controllers on COMPASS-D. Suitable models of tokamaks are required to exploit the potential of modern control techniques. A physics based MIMO model of TCV is presented and validated with experimental closed loop responses. A system identified open loop model is also presented. An enhanced controller based on these models is designed and the performance improvements discussed. (author) 5 figs., 9 refs

  4. Scramjet Isolator Modeling and Control

    Science.gov (United States)

    2011-12-01

    Layer Interactions,” (NATO) AGARD CP 193, May 1976. 17. Cox, C., Lewis, C., Pap, R., Glover, C., Priddy, K., Edwards, J., and McCarty, D., “Prediction...Static Polynomial Model . . . . . . . . . . . . . . . . . . 73 5.2 Continuous Linear Model with Static Polynomial Input . 75 5.3 ARX Models with Static...Vector of NARX model regression values . . . . . . . . . . 70 Nr Number of samples for a run . . . . . . . . . . . . . . . . 73 ΘNL Vector of

  5. Modeling and identification for robot motion control

    NARCIS (Netherlands)

    Kostic, D.; Jager, de A.G.; Steinbuch, M.; Kurfess, T.R.

    2004-01-01

    This chapter deals with the problems of robot modelling and identification for high-performance model-based motion control. A derivation of robot kinematic and dynamic models was explained. Modelling of friction effects was also discussed. Use of a writing task to establish correctness of the models

  6. Modelling and control of systems with flow

    NARCIS (Netherlands)

    van Mourik, S.

    2008-01-01

    In practice, feedback control design consists of three steps: modelling, model reduction and controller design for the reduced model. Systems with flow are often complicated, and there is yet no standard algorithm that integrates these steps. In this thesis we make a modest effort by considering two

  7. Nonlinear control of the Salnikov model reaction

    DEFF Research Database (Denmark)

    Recke, Bodil; Jørgensen, Sten Bay

    1999-01-01

    This paper explores different nonlinear control schemes, applied to a simple model reaction. The model is the Salnikov model, consisting of two ordinary differential equations. The control strategies investigated are I/O-linearisation, Exact linearisation, exact linearisation combined with LQR...

  8. Modeling Control Situations in Power System Operations

    DEFF Research Database (Denmark)

    Saleem, Arshad; Lind, Morten; Singh, Sri Niwas

    2010-01-01

    for intelligent operation and control must represent system features, so that information from measurements can be related to possible system states and to control actions. These general modeling requirements are well understood, but it is, in general, difficult to translate them into a model because of the lack...... of explicit principles for model construction. This paper presents a work on using explicit means-ends model based reasoning about complex control situations which results in maintaining consistent perspectives and selecting appropriate control action for goal driven agents. An example of power system......Increased interconnection and loading of the power system along with deregulation has brought new challenges for electric power system operation, control and automation. Traditional power system models used in intelligent operation and control are highly dependent on the task purpose. Thus, a model...

  9. Modeling and control of greenhouse crop growth

    CERN Document Server

    Rodríguez, Francisco; Guzmán, José Luis; Ramírez-Arias, Armando

    2015-01-01

    A discussion of challenges related to the modeling and control of greenhouse crop growth, this book presents state-of-the-art answers to those challenges. The authors model the subsystems involved in successful greenhouse control using different techniques and show how the models obtained can be exploited for simulation or control design; they suggest ideas for the development of physical and/or black-box models for this purpose. Strategies for the control of climate- and irrigation-related variables are brought forward. The uses of PID control and feedforward compensators, both widely used in commercial tools, are summarized. The benefits of advanced control techniques—event-based, robust, and predictive control, for example—are used to improve on the performance of those basic methods. A hierarchical control architecture is developed governed by a high-level multiobjective optimization approach rather than traditional constrained optimization and artificial intelligence techniques.  Reference trajector...

  10. Applying model predictive control to power system frequency control

    OpenAIRE

    Ersdal, AM; Imsland, L; Cecilio, IM; Fabozzi, D; Thornhill, NF

    2013-01-01

    16.07.14 KB Ok to add accepted version to Spiral Model predictive control (MPC) is investigated as a control method which may offer advantages in frequency control of power systems than the control methods applied today, especially in presence of increased renewable energy penetration. The MPC includes constraints on both generation amount and generation rate of change, and it is tested on a one-area system. The proposed MPC is tested against a conventional proportional-integral (PI) cont...

  11. Fractional Order Models of Industrial Pneumatic Controllers

    Directory of Open Access Journals (Sweden)

    Abolhassan Razminia

    2014-01-01

    Full Text Available This paper addresses a new approach for modeling of versatile controllers in industrial automation and process control systems such as pneumatic controllers. Some fractional order dynamical models are developed for pressure and pneumatic systems with bellows-nozzle-flapper configuration. In the light of fractional calculus, a fractional order derivative-derivative (FrDD controller and integral-derivative (FrID are remodeled. Numerical simulations illustrate the application of the obtained theoretical results in simple examples.

  12. Plant control using embedded predictive models

    International Nuclear Information System (INIS)

    Godbole, S.S.; Gabler, W.E.; Eschbach, S.L.

    1990-01-01

    B and W recently undertook the design of an advanced light water reactor control system. A concept new to nuclear steam system (NSS) control was developed. The concept, which is called the Predictor-Corrector, uses mathematical models of portions of the controlled NSS to calculate, at various levels within the system, demand and control element position signals necessary to satisfy electrical demand. The models give the control system the ability to reduce overcooling and undercooling of the reactor coolant system during transients and upsets. Two types of mathematical models were developed for use in designing and testing the control system. One model was a conventional, comprehensive NSS model that responds to control system outputs and calculates the resultant changes in plant variables that are then used as inputs to the control system. Two other models, embedded in the control system, were less conventional, inverse models. These models accept as inputs plant variables, equipment states, and demand signals and predict plant operating conditions and control element states that will satisfy the demands. This paper reports preliminary results of closed-loop Reactor Coolant (RC) pump trip and normal load reduction testing of the advanced concept. Results of additional transient testing, and of open and closed loop stability analyses will be reported as they are available

  13. Towards an adaptive model for greenhouse control

    NARCIS (Netherlands)

    Speetjens, S.L.; Stigter, J.D.; Straten, van G.

    2009-01-01

    Application of advanced controllers in horticultural practice requires detailed models. Even highly sophisticated models require regular attention from the user due to changing circumstances like plant growth, changing material properties and modifications in greenhouse design and layout. Moreover,

  14. Model for RHIC ramp controls

    International Nuclear Information System (INIS)

    Kewisch, J.; Mane, V.; Clifford, T.; Hartmann, H.; Kahn, T.; Oerter, B.; Peggs, S.

    1994-01-01

    This paper introduces the hardware and software concepts for the implementation of the ramp controls. The hardware part of the ramp controls consists of a number of multi-purpose Wave Form Generators (WFGS) which control the settings of accelerator hardware directly or indirectly by controlling their WFG. A Real Time Data Link (RTDL) data transfer system connects the WFGs in a three layer architecture. To the usual two layers which generate an independent timing signal and dependent set points, respectively, an intermediate layer is added which produces accelerator parameters such as the magnet strength. The task of the bottom layer is therefore reduced to the function of implementing those parameters. This architecture de-couples two independent functions which axe normally folded together. The function of the hardware becomes modular and easily maintainable. The ramp control software is layered in the same way. Between the top layer (the ramp procedure application program) and the bottom layer (the hardware interface) an additional layer of ''manager'' programs allow operation of accelerator subsystems

  15. Modeling and Modern Control of Wind Power

    DEFF Research Database (Denmark)

    This book covers the modeling of wind power and application of modern control methods to the wind power control—specifically the models of type 3 and type 4 wind turbines. The modeling aspects will help readers to streamline the wind turbine and wind power plant modeling, and reduce the burden...... of power system simulations to investigate the impact of wind power on power systems. The use of modern control methods will help technology development, especially from the perspective of manufactures....

  16. Modeling, Control and Coordination of Helicopter Systems

    CERN Document Server

    Ren, Beibei; Chen, Chang; Fua, Cheng-Heng; Lee, Tong Heng

    2012-01-01

    Modeling, Control and Coordination of Helicopter Systems provides a comprehensive treatment of helicopter systems, ranging from related nonlinear flight dynamic modeling and stability analysis to advanced control design for single helicopter systems, and also covers issues related to the coordination and formation control of multiple helicopter systems to achieve high performance tasks. Ensuring stability in helicopter flight is a challenging problem for nonlinear control design and development. This book is a valuable reference on modeling, control and coordination of helicopter systems,providing readers with practical solutions for the problems that still plague helicopter system design and implementation. Readers will gain a complete picture of helicopters at the systems level, as well as a better understanding of the technical intricacies involved. This book also: Presents a complete picture of modeling, control and coordination for helicopter systems Provides a modeling platform for a general class of ro...

  17. 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

  18. THE INTERNAL CONTROL MODELS IN ROMANIA

    Directory of Open Access Journals (Sweden)

    TEODORESCU CRISTIAN DRAGOȘ

    2015-06-01

    Full Text Available Internal control is indissolubly linked to business and accounting. Throughout history, domestic and international trade has grown exponentially, which has led to an increasing complexity of internal control, to new methods and techniques to control the business. The literature has presented the first models of internal control in the Sumerian period (3600 - 3200 BC, and the emergence and development of internal control in Egypt, Persia, Greek and Roman Empire, in the Middle Ages till modern times. The purpose of this article is to present the models of internal control in Romania, starting from the principles of the classical model of internal control (COSO model. For a better understanding of the implication of internal control in terms of public and private sector, I have structured the article in the following parts: (a the definition of internal control in the literature; (b the presentation of the COSO model; (c internal control and internal audit in public institutions; (d internal control issues in accounting regulations on the individual and consolidated annual financial statements; (e internal / managerial control; (f conclusions.

  19. Control Valve Stiction Identification, Modelling, Quantification and Control - A Review

    Directory of Open Access Journals (Sweden)

    Srinivasan Arumugam

    2011-09-01

    Full Text Available Most of the processes found in process industries exhibit undesirable nonlinearity due to backlash, saturation, hysteresis, stiction (friction, dead-zone and stuck-fault existing in control valves. The control valve is the actuator for most process control loops and, as the only moving part in the loop, its function is to implement the control action. If the control valve malfunctions, the performance of the control loop is likely to deteriorate, no matter how good the controller is. Commonly encountered control valve problems include nonlinear responses to the demand signal caused by effects such as stiction, dead-band or saturation. Because of these problems, the control loop may be oscillatory, which in turn may cause oscillations in many process variables causing a range of operational problems including increased valve wear. Understanding nonlinear behaviour of control valves in order to maintain the quality of the end products in the industry, this review article surveys the identification, modelling, estimation and design of dynamic models of stiction nonlinearity and providing appropriate controller to obtain optimum responses of the process. The primary objective of this work is to present state-of-art-review of common nonlinear problems associated with mechanical and chemical processes for encouraging researchers, practicing engineers working in this field, so that readers can invent their goals for future research work on nonlinear systems identification and control.

  20. PI controller based model reference adaptive control for nonlinear

    African Journals Online (AJOL)

    user

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

  1. Fault Tolerant Control Using Gaussian Processes and Model Predictive Control

    Directory of Open Access Journals (Sweden)

    Yang Xiaoke

    2015-03-01

    Full Text Available Essential ingredients for fault-tolerant control are the ability to represent system behaviour following the occurrence of a fault, and the ability to exploit this representation for deciding control actions. Gaussian processes seem to be very promising candidates for the first of these, and model predictive control has a proven capability for the second. We therefore propose to use the two together to obtain fault-tolerant control functionality. Our proposal is illustrated by several reasonably realistic examples drawn from flight control.

  2. Flexible AC transmission systems modelling and control

    CERN Document Server

    Zhang, Xiao-Ping; Pal, Bikash

    2012-01-01

    The extended and revised second edition of this successful monograph presents advanced modeling, analysis and control techniques of Flexible AC Transmission Systems (FACTS). The book covers comprehensively a range of power-system control problems: from steady-state voltage and power flow control, to voltage and reactive power control, to voltage stability control, to small signal stability control using FACTS controllers. In the six years since the first edition of the book has been published research on the FACTS has continued to flourish while renewable energy has developed into a mature and

  3. Unreachable Setpoints in Model Predictive Control

    DEFF Research Database (Denmark)

    Rawlings, James B.; Bonné, Dennis; Jørgensen, John Bagterp

    2008-01-01

    In this work, a new model predictive controller is developed that handles unreachable setpoints better than traditional model predictive control methods. The new controller induces an interesting fast/slow asymmetry in the tracking response of the system. Nominal asymptotic stability of the optimal...... steady state is established for terminal constraint model predictive control (MPC). The region of attraction is the steerable set. Existing analysis methods for closed-loop properties of MPC are not applicable to this new formulation, and a new analysis method is developed. It is shown how to extend...

  4. Model based development of engine control algorithms

    NARCIS (Netherlands)

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

    1996-01-01

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

  5. Model predictive Controller for Mobile Robot

    OpenAIRE

    Alireza Rezaee

    2017-01-01

    This paper proposes a Model Predictive Controller (MPC) for control of a P2AT mobile robot. MPC refers to a group of controllers that employ a distinctly identical model of process to predict its future behavior over an extended prediction horizon. The design of a MPC is formulated as an optimal control problem. Then this problem is considered as linear quadratic equation (LQR) and is solved by making use of Ricatti equation. To show the effectiveness of the proposed method this controller is...

  6. Integrated identification, modeling and control with applications

    Science.gov (United States)

    Shi, Guojun

    This thesis deals with the integration of system design, identification, modeling and control. In particular, six interdisciplinary engineering problems are addressed and investigated. Theoretical results are established and applied to structural vibration reduction and engine control problems. First, the data-based LQG control problem is formulated and solved. It is shown that a state space model is not necessary to solve this problem; rather a finite sequence from the impulse response is the only model data required to synthesize an optimal controller. The new theory avoids unnecessary reliance on a model, required in the conventional design procedure. The infinite horizon model predictive control problem is addressed for multivariable systems. The basic properties of the receding horizon implementation strategy is investigated and the complete framework for solving the problem is established. The new theory allows the accommodation of hard input constraints and time delays. The developed control algorithms guarantee the closed loop stability. A closed loop identification and infinite horizon model predictive control design procedure is established for engine speed regulation. The developed algorithms are tested on the Cummins Engine Simulator and desired results are obtained. A finite signal-to-noise ratio model is considered for noise signals. An information quality index is introduced which measures the essential information precision required for stabilization. The problems of minimum variance control and covariance control are formulated and investigated. Convergent algorithms are developed for solving the problems of interest. The problem of the integrated passive and active control design is addressed in order to improve the overall system performance. A design algorithm is developed, which simultaneously finds: (i) the optimal values of the stiffness and damping ratios for the structure, and (ii) an optimal output variance constrained stabilizing

  7. Model predictive controller design of hydrocracker reactors

    OpenAIRE

    GÖKÇE, Dila

    2011-01-01

    This study summarizes the design of a Model Predictive Controller (MPC) in Tüpraş, İzmit Refinery Hydrocracker Unit Reactors. Hydrocracking process, in which heavy vacuum gasoil is converted into lighter and valuable products at high temperature and pressure is described briefly. Controller design description, identification and modeling studies are examined and the model variables are presented. WABT (Weighted Average Bed Temperature) equalization and conversion increase are simulate...

  8. Mathematical Ship Modeling for Control Applications

    DEFF Research Database (Denmark)

    Perez, Tristan; Blanke, Mogens

    2002-01-01

    In this report, we review the models for describing the motion of a ship in four degrees of freedom suitable for control applications. We present the hydrodynamic models of two ships: a container and a multi-role naval vessel. The models are based on experimental results in the four degrees...

  9. Flexible AC transmission systems. Modelling and control

    Energy Technology Data Exchange (ETDEWEB)

    Zhang, Xiao-Ping [Birmingham Univ. (United Kingdom); Rehtanz, Christian [Technische Univ. Dortmund (Germany); Pal, Bikash [Imperial College, London (United Kingdom)

    2012-11-01

    This monograph presents advanced modelling, analysis and control techniques of FACTS. These topics reflect the recent research and development of FACTS controllers, and anticipate the future applications of FACTS in power systems. The book covers comprehensively a range of power-system control problems: from steady-state voltage and power flow control, to voltage and reactive power control, to voltage stability control, to small signal stability control using FACTS controllers. The book presents the modelling of the latest FACTS controllers for power flow control, compensation and power quality (IPFC, GUPF, VSC HVDC and M-VSCHVDC, etc.) in power system analysis. The selection is evaluated by the actual and likely future practical relevance of each. The material is derived mainly from the research and industrial development in which the authors have been heavily involved. The book is timely and of great value to power engineering engineers and students of modelling, simulations and control design of FACTS for a broad practical range of power system operation, planning and control problems.

  10. Model predictive control classical, robust and stochastic

    CERN Document Server

    Kouvaritakis, Basil

    2016-01-01

    For the first time, a textbook that brings together classical predictive control with treatment of up-to-date robust and stochastic techniques. Model Predictive Control describes the development of tractable algorithms for uncertain, stochastic, constrained systems. The starting point is classical predictive control and the appropriate formulation of performance objectives and constraints to provide guarantees of closed-loop stability and performance. Moving on to robust predictive control, the text explains how similar guarantees may be obtained for cases in which the model describing the system dynamics is subject to additive disturbances and parametric uncertainties. Open- and closed-loop optimization are considered and the state of the art in computationally tractable methods based on uncertainty tubes presented for systems with additive model uncertainty. Finally, the tube framework is also applied to model predictive control problems involving hard or probabilistic constraints for the cases of multiplic...

  11. Parametric Analysis of Flexible Logic Control Model

    Directory of Open Access Journals (Sweden)

    Lihua Fu

    2013-01-01

    Full Text Available Based on deep analysis about the essential relation between two input variables of normal two-dimensional fuzzy controller, we used universal combinatorial operation model to describe the logic relationship and gave a flexible logic control method to realize the effective control for complex system. In practical control application, how to determine the general correlation coefficient of flexible logic control model is a problem for further studies. First, the conventional universal combinatorial operation model has been limited in the interval [0,1]. Consequently, this paper studies a kind of universal combinatorial operation model based on the interval [a,b]. And some important theorems are given and proved, which provide a foundation for the flexible logic control method. For dealing reasonably with the complex relations of every factor in complex system, a kind of universal combinatorial operation model with unequal weights is put forward. Then, this paper has carried out the parametric analysis of flexible logic control model. And some research results have been given, which have important directive to determine the values of the general correlation coefficients in practical control application.

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

    Science.gov (United States)

    Jungwirth, Patrick; Badawy, Abdel-Hameed

    2017-04-01

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

  13. Wind farm models and control strategies

    Energy Technology Data Exchange (ETDEWEB)

    Soerensen, Poul; Hansen, Anca D.; Iov, F.; Blaabjerg, F.; Donovan, M.H.

    2005-08-01

    This report describes models and control strategies for 3 different concepts of wind farms. Initially, the potential in improvement of grid integration, structural loads and energy production is investigated in a survey of opportunities. Then simulation models are described, including wind turbine models for a fixed speed wind turbine with active stall control and a variable speed wind turbine with doubly-fed induction generator. After that, the 3 wind farm concepts and control strategies are described. The 3 concepts are AC connected doubly fed turbines, AC connected active stall turbines and DC connected active stall turbines. Finally, some simulation examples and conclusions are presented. (au)

  14. Modelling supervisory controller for hybrid power systems

    Energy Technology Data Exchange (ETDEWEB)

    Pereira, A; Bindner, H; Lundsager, P [Risoe National Lab., Roskilde (Denmark); Jannerup, O [Technical Univ. of Denmark, Dept. of Automation, Lyngby (Denmark)

    1999-03-01

    Supervisory controllers are important to achieve optimal operation of hybrid power systems. The performance and economics of such systems depend mainly on the control strategy for switching on/off components. The modular concept described in this paper is an attempt to design standard supervisory controllers that could be used in different applications, such as village power and telecommunication applications. This paper presents some basic aspects of modelling and design of modular supervisory controllers using the object-oriented modelling technique. The functional abstraction hierarchy technique is used to formulate the control requirements and identify the functions of the control system. The modular algorithm is generic and flexible enough to be used with any system configuration and several goals (different applications). The modularity includes accepting modification of system configuration and goals during operation with minor or no changes in the supervisory controller. (au)

  15. Contrast Gain Control Model Fits Masking Data

    Science.gov (United States)

    Watson, Andrew B.; Solomon, Joshua A.; Null, Cynthia H. (Technical Monitor)

    1994-01-01

    We studied the fit of a contrast gain control model to data of Foley (JOSA 1994), consisting of thresholds for a Gabor patch masked by gratings of various orientations, or by compounds of two orientations. Our general model includes models of Foley and Teo & Heeger (IEEE 1994). Our specific model used a bank of Gabor filters with octave bandwidths at 8 orientations. Excitatory and inhibitory nonlinearities were power functions with exponents of 2.4 and 2. Inhibitory pooling was broad in orientation, but narrow in spatial frequency and space. Minkowski pooling used an exponent of 4. All of the data for observer KMF were well fit by the model. We have developed a contrast gain control model that fits masking data. Unlike Foley's, our model accepts images as inputs. Unlike Teo & Heeger's, our model did not require multiple channels for different dynamic ranges.

  16. Modelling and control of large cryogenic refrigerator

    International Nuclear Information System (INIS)

    Bonne, Francois

    2014-01-01

    This manuscript is concern with both the modeling and the derivation of control schemes for large cryogenic refrigerators. The particular case of those which are submitted to highly variable pulsed heat load is studied. A model of each object that normally compose a large cryo-refrigerator is proposed. The methodology to gather objects model into the model of a subsystem is presented. The manuscript also shows how to obtain a linear equivalent model of the subsystem. Based on the derived models, advances control scheme are proposed. Precisely, a linear quadratic controller for warm compression station working with both two and three pressures state is derived, and a predictive constrained one for the cold-box is obtained. The particularity of those control schemes is that they fit the computing and data storage capabilities of Programmable Logic Controllers (PLC) with are well used in industry. The open loop model prediction capability is assessed using experimental data. Developed control schemes are validated in simulation and experimentally on the 400W1.8K SBT's cryogenic test facility and on the CERN's LHC warm compression station. (author) [fr

  17. Aspects of modelling and control of bioprocesses

    Energy Technology Data Exchange (ETDEWEB)

    Zhang, Xiachang

    1996-12-31

    The modelling and control of bioprocesses are the main subjects in this thesis. Different modelling approaches are proposed for different purposes in various bioprocesses. A conventional global model was constructed for a very complex mammalian cell culture process. A new concept of functional state and a multiple model (local models) approach were used for modelling the fed-batch baker`s yeast process for monitoring and control purposes. Finally, a combination of conventional electrical and biological models was used to simulate and to control a microbial fuel cell process. In the thesis, a yeast growth process was taken as an example to demonstrate the usefulness of the functional state concept and local models. The functional states were first defined according to the yeast metabolism. The process was then described by a set of simple local models. In different functional states, different local models were used. On the other hand, the on-line estimation of functional state and biomass of the process was discussed for process control purpose. As a consequence, both the functional state concept and the multiple model approach were applied for fuzzy logic control of yeast growth process. A fuzzy factor was calculated on the basis of a knowledge-based expert system and fuzzy logic rules. The factor was used to correct an ideal substrate feed rate. In the last part of the thesis, microbial fuel cell processes were studied. A microbial fuel cell is a device for direct conversion of chemical energy to electrical energy by using micro-organisms as catalysts. A combined model including conventional electrical and biological models was constructed for the process based on the biological and electrochemical phenomena

  18. Aspects of modelling and control of bioprocesses

    Energy Technology Data Exchange (ETDEWEB)

    Zhang, Xiachang

    1995-12-31

    The modelling and control of bioprocesses are the main subjects in this thesis. Different modelling approaches are proposed for different purposes in various bioprocesses. A conventional global model was constructed for a very complex mammalian cell culture process. A new concept of functional state and a multiple model (local models) approach were used for modelling the fed-batch baker`s yeast process for monitoring and control purposes. Finally, a combination of conventional electrical and biological models was used to simulate and to control a microbial fuel cell process. In the thesis, a yeast growth process was taken as an example to demonstrate the usefulness of the functional state concept and local models. The functional states were first defined according to the yeast metabolism. The process was then described by a set of simple local models. In different functional states, different local models were used. On the other hand, the on-line estimation of functional state and biomass of the process was discussed for process control purpose. As a consequence, both the functional state concept and the multiple model approach were applied for fuzzy logic control of yeast growth process. A fuzzy factor was calculated on the basis of a knowledge-based expert system and fuzzy logic rules. The factor was used to correct an ideal substrate feed rate. In the last part of the thesis, microbial fuel cell processes were studied. A microbial fuel cell is a device for direct conversion of chemical energy to electrical energy by using micro-organisms as catalysts. A combined model including conventional electrical and biological models was constructed for the process based on the biological and electrochemical phenomena

  19. Mob control models of threshold collective behavior

    CERN Document Server

    Breer, Vladimir V; Rogatkin, Andrey D

    2017-01-01

    This book presents mathematical models of mob control with threshold (conformity) collective decision-making of the agents. Based on the results of analysis of the interconnection between the micro- and macromodels of active network structures, it considers the static (deterministic, stochastic and game-theoretic) and dynamic (discrete- and continuous-time) models of mob control, and highlights models of informational confrontation. Many of the results are applicable not only to mob control problems, but also to control problems arising in social groups, online social networks, etc. Aimed at researchers and practitioners, it is also a valuable resource for undergraduate and postgraduate students as well as doctoral candidates specializing in the field of collective behavior modeling.

  20. Modelling and control of a flotation process

    International Nuclear Information System (INIS)

    Ding, L.; Gustafsson, T.

    1999-01-01

    A general description of a flotation process is given. The dynamic model of a MIMO nonlinear subprocess in flotation, i. e. the pulp levels in five compartments in series is developed and the model is verified with real data from a production plant. In order to reject constant disturbances five extra states are introduced and the model is modified. An exact linearization has been made for the non-linear model and a linear quadratic gaussian controller is proposed based on the linearized model. The simulation result shows an improved performance of the pulp level control when the set points are changed or a disturbance occur. In future the controller will be tested in production. (author)

  1. Improving Wind Farm Dispatchability Using Model Predictive Control for Optimal Operation of Grid-Scale Energy Storage

    Directory of Open Access Journals (Sweden)

    Douglas Halamay

    2014-09-01

    Full Text Available This paper demonstrates the use of model-based predictive control for energy storage systems to improve the dispatchability of wind power plants. Large-scale wind penetration increases the variability of power flow on the grid, thus increasing reserve requirements. Large energy storage systems collocated with wind farms can improve dispatchability of the wind plant by storing energy during generation over-the-schedule and sourcing energy during generation under-the-schedule, essentially providing on-site reserves. Model predictive control (MPC provides a natural framework for this application. By utilizing an accurate energy storage system model, control actions can be planned in the context of system power and state-of-charge limitations. MPC also enables the inclusion of predicted wind farm performance over a near-term horizon that allows control actions to be planned in anticipation of fast changes, such as wind ramps. This paper demonstrates that model-based predictive control can improve system performance compared with a standard non-predictive, non-model-based control approach. It is also demonstrated that secondary objectives, such as reducing the rate of change of the wind plant output (i.e., ramps, can be considered and successfully implemented within the MPC framework. Specifically, it is shown that scheduling error can be reduced by 81%, reserve requirements can be improved by up to 37%, and the number of ramp events can be reduced by 74%.

  2. Mosaic model for sensorimotor learning and control.

    Science.gov (United States)

    Haruno, M; Wolpert, D M; Kawato, M

    2001-10-01

    Humans demonstrate a remarkable ability to generate accurate and appropriate motor behavior under many different and often uncertain environmental conditions. We previously proposed a new modular architecture, the modular selection and identification for control (MOSAIC) model, for motor learning and control based on multiple pairs of forward (predictor) and inverse (controller) models. The architecture simultaneously learns the multiple inverse models necessary for control as well as how to select the set of inverse models appropriate for a given environment. It combines both feedforward and feedback sensorimotor information so that the controllers can be selected both prior to movement and subsequently during movement. This article extends and evaluates the MOSAIC architecture in the following respects. The learning in the architecture was implemented by both the original gradient-descent method and the expectation-maximization (EM) algorithm. Unlike gradient descent, the newly derived EM algorithm is robust to the initial starting conditions and learning parameters. Second, simulations of an object manipulation task prove that the architecture can learn to manipulate multiple objects and switch between them appropriately. Moreover, after learning, the model shows generalization to novel objects whose dynamics lie within the polyhedra of already learned dynamics. Finally, when each of the dynamics is associated with a particular object shape, the model is able to select the appropriate controller before movement execution. When presented with a novel shape-dynamic pairing, inappropriate activation of modules is observed followed by on-line correction.

  3. Modeling and (adaptive) control of greenhouse climates

    NARCIS (Netherlands)

    Udink ten Cate, A.J.

    1983-01-01

    The material presented in this thesis can be grouped around four themes, system concepts, modeling, control and adaptive control. In this summary these themes will be treated separately.

    System concepts

    In Chapters 1 and 2 an overview of the problem formulation

  4. Controller Synthesis using Qualitative Models and Constraints

    OpenAIRE

    Ramamoorthy, Subramanian; Kuipers, Benjamin J

    2004-01-01

    Many engineering systems require the synthesis of global behaviors in nonlinear dynamical systems. Multiple model approaches to control design make it possible to synthesize robust and optimal versions of such global behaviors. We propose a methodology called Qualitative Heterogeneous Control that enables this type of control design. This methodology is based on a separation of concerns between qualitative correctness and quantitative optimization. Qualitative sufficient conditions are derive...

  5. Simplified ejector model for control and optimization

    International Nuclear Information System (INIS)

    Zhu Yinhai; Cai Wenjian; Wen Changyun; Li Yanzhong

    2008-01-01

    In this paper, a simple yet effective ejector model for a real time control and optimization of an ejector system is proposed. Firstly, a fundamental model for calculation of ejector entrainment ratio at critical working conditions is derived by one-dimensional analysis and the shock circle model. Then, based on thermodynamic principles and the lumped parameter method, the fundamental ejector model is simplified to result in a hybrid ejector model. The model is very simple, which only requires two or three parameters and measurement of two variables to determine the ejector performance. Furthermore, the procedures for on line identification of the model parameters using linear and non-linear least squares methods are also presented. Compared with existing ejector models, the solution of the proposed model is much easier without coupled equations and iterative computations. Finally, the effectiveness of the proposed model is validated by published experimental data. Results show that the model is accurate and robust and gives a better match to the real performances of ejectors over the entire operating range than the existing models. This model is expected to have wide applications in real time control and optimization of ejector systems

  6. Multiple model adaptive control with mixing

    Science.gov (United States)

    Kuipers, Matthew

    Despite the remarkable theoretical accomplishments and successful applications of adaptive control, the field is not sufficiently mature to solve challenging control problems requiring strict performance and safety guarantees. Towards addressing these issues, a novel deterministic multiple-model adaptive control approach called adaptive mixing control is proposed. In this approach, adaptation comes from a high-level system called the supervisor that mixes into feedback a number of candidate controllers, each finely-tuned to a subset of the parameter space. The mixing signal, the supervisor's output, is generated by estimating the unknown parameters and, at every instant of time, calculating the contribution level of each candidate controller based on certainty equivalence. The proposed architecture provides two characteristics relevant to solving stringent, performance-driven applications. First, the full-suite of linear time invariant control tools is available. A disadvantage of conventional adaptive control is its restriction to utilizing only those control laws whose solutions can be feasibly computed in real-time, such as model reference and pole-placement type controllers. Because its candidate controllers are computed off line, the proposed approach suffers no such restriction. Second, the supervisor's output is smooth and does not necessarily depend on explicit a priori knowledge of the disturbance model. These characteristics can lead to improved performance by avoiding the unnecessary switching and chattering behaviors associated with some other multiple adaptive control approaches. The stability and robustness properties of the adaptive scheme are analyzed. It is shown that the mean-square regulation error is of the order of the modeling error. And when the parameter estimate converges to its true value, which is guaranteed if a persistence of excitation condition is satisfied, the adaptive closed-loop system converges exponentially fast to a closed

  7. Modelling and control of refrigerant circuits

    Energy Technology Data Exchange (ETDEWEB)

    Gruhle, W D; Isermann, R

    1987-01-01

    Conventional evaporator control systems involving a thermostatic expansion valve often to not work satisfactorily in terms of stability and evaporator utilization. To improve this, the author first studies the cause of this behaviour by means of theoretic modelling which is greatly determined by processes occurring within the evaporator and by structural combinations. After verification of the simulated model by means of measurements performed on a pilot plant, the results obtained are used to build up a new control system. Various experiments reveal a clearly improved evaporator utilization at greater control stability. (orig.).

  8. Model Based Control of Refrigeration Systems

    DEFF Research Database (Denmark)

    Larsen, Lars Finn Sloth

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

  9. Distributed model predictive control made easy

    CERN Document Server

    Negenborn, Rudy

    2014-01-01

    The rapid evolution of computer science, communication, and information technology has enabled the application of control techniques to systems beyond the possibilities of control theory just a decade ago. Critical infrastructures such as electricity, water, traffic and intermodal transport networks are now in the scope of control engineers. The sheer size of such large-scale systems requires the adoption of advanced distributed control approaches. Distributed model predictive control (MPC) is one of the promising control methodologies for control of such systems.   This book provides a state-of-the-art overview of distributed MPC approaches, while at the same time making clear directions of research that deserve more attention. The core and rationale of 35 approaches are carefully explained. Moreover, detailed step-by-step algorithmic descriptions of each approach are provided. These features make the book a comprehensive guide both for those seeking an introduction to distributed MPC as well as for those ...

  10. Intelligent Mechatronic Systems Modeling, Control and Diagnosis

    CERN Document Server

    Merzouki, Rochdi; Pathak, Pushparaj Mani; Ould Bouamama, Belkacem

    2013-01-01

    Acting as a support resource for practitioners and professionals looking to advance their understanding of complex mechatronic systems, Intelligent Mechatronic Systems explains their design and recent developments from first principles to practical applications. Detailed descriptions of the mathematical models of complex mechatronic systems, developed from fundamental physical relationships, are built on to develop innovative solutions with particular emphasis on physical model-based control strategies. Following a concurrent engineering approach, supported by industrial case studies, and drawing on the practical experience of the authors, Intelligent Mechatronic Systems covers range of topic and includes:  • An explanation of a common graphical tool for integrated design and its uses from modeling and simulation to the control synthesis • Introductions to key concepts such as different means of achieving fault tolerance, robust overwhelming control and force and impedance control • Dedicated chapters ...

  11. NONLINEAR MODEL PREDICTIVE CONTROL OF CHEMICAL PROCESSES

    Directory of Open Access Journals (Sweden)

    SILVA R. G.

    1999-01-01

    Full Text Available A new algorithm for model predictive control is presented. The algorithm utilizes a simultaneous solution and optimization strategy to solve the model's differential equations. The equations are discretized by equidistant collocation, and along with the algebraic model equations are included as constraints in a nonlinear programming (NLP problem. This algorithm is compared with the algorithm that uses orthogonal collocation on finite elements. The equidistant collocation algorithm results in simpler equations, providing a decrease in computation time for the control moves. Simulation results are presented and show a satisfactory performance of this algorithm.

  12. Two stage neural network modelling for robust model predictive control.

    Science.gov (United States)

    Patan, Krzysztof

    2018-01-01

    The paper proposes a novel robust model predictive control scheme realized by means of artificial neural networks. The neural networks are used twofold: to design the so-called fundamental model of a plant and to catch uncertainty associated with the plant model. In order to simplify the optimization process carried out within the framework of predictive control an instantaneous linearization is applied which renders it possible to define the optimization problem in the form of constrained quadratic programming. Stability of the proposed control system is also investigated by showing that a cost function is monotonically decreasing with respect to time. Derived robust model predictive control is tested and validated on the example of a pneumatic servomechanism working at different operating regimes. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

  13. Model Predictive Control for Load Frequency Control with Wind Turbines

    Directory of Open Access Journals (Sweden)

    Yi Zhang

    2015-01-01

    Full Text Available Reliable load frequency (LFC control is crucial to the operation and design of modern electric power systems. Considering the LFC problem of a four-area interconnected power system with wind turbines, this paper presents a distributed model predictive control (DMPC based on coordination scheme. The proposed algorithm solves a series of local optimization problems to minimize a performance objective for each control area. The scheme incorporates the two critical nonlinear constraints, for example, the generation rate constraint (GRC and the valve limit, into convex optimization problems. Furthermore, the algorithm reduces the impact on the randomness and intermittence of wind turbine effectively. A performance comparison between the proposed controller with and that without the participation of the wind turbines is carried out. Good performance is obtained in the presence of power system nonlinearities due to the governors and turbines constraints and load change disturbances.

  14. Model Predictive Control for Smart Energy Systems

    DEFF Research Database (Denmark)

    Halvgaard, Rasmus

    pumps, heat tanks, electrical vehicle battery charging/discharging, wind farms, power plants). 2.Embed forecasting methodologies for the weather (e.g. temperature, solar radiation), the electricity consumption, and the electricity price in a predictive control system. 3.Develop optimization algorithms....... Chapter 3 introduces Model Predictive Control (MPC) including state estimation, filtering and prediction for linear models. Chapter 4 simulates the models from Chapter 2 with the certainty equivalent MPC from Chapter 3. An economic MPC minimizes the costs of consumption based on real electricity prices...... that determined the flexibility of the units. A predictive control system easily handles constraints, e.g. limitations in power consumption, and predicts the future behavior of a unit by integrating predictions of electricity prices, consumption, and weather variables. The simulations demonstrate the expected...

  15. Parametric uncertainty modeling for robust control

    DEFF Research Database (Denmark)

    Rasmussen, K.H.; Jørgensen, Sten Bay

    1999-01-01

    The dynamic behaviour of a non-linear process can often be approximated with a time-varying linear model. In the presented methodology the dynamics is modeled non-conservatively as parametric uncertainty in linear lime invariant models. The obtained uncertainty description makes it possible...... to perform robustness analysis on a control system using the structured singular value. The idea behind the proposed method is to fit a rational function to the parameter variation. The parameter variation can then be expressed as a linear fractional transformation (LFT), It is discussed how the proposed...... point changes. It is shown that a diagonal PI control structure provides robust performance towards variations in feed flow rate or feed concentrations. However including both liquid and vapor flow delays robust performance specifications cannot be satisfied with this simple diagonal control structure...

  16. Modelling and control of dynamic systems using gaussian process models

    CERN Document Server

    Kocijan, Juš

    2016-01-01

    This monograph opens up new horizons for engineers and researchers in academia and in industry dealing with or interested in new developments in the field of system identification and control. It emphasizes guidelines for working solutions and practical advice for their implementation rather than the theoretical background of Gaussian process (GP) models. The book demonstrates the potential of this recent development in probabilistic machine-learning methods and gives the reader an intuitive understanding of the topic. The current state of the art is treated along with possible future directions for research. Systems control design relies on mathematical models and these may be developed from measurement data. This process of system identification, when based on GP models, can play an integral part of control design in data-based control and its description as such is an essential aspect of the text. The background of GP regression is introduced first with system identification and incorporation of prior know...

  17. Modeling, Optimization & Control of Hydraulic Networks

    DEFF Research Database (Denmark)

    Tahavori, Maryamsadat

    2014-01-01

    . The nonlinear network model is derived based on the circuit theory. A suitable projection is used to reduce the state vector and to express the model in standard state-space form. Then, the controllability of nonlinear nonaffine hydraulic networks is studied. The Lie algebra-based controllability matrix is used......Water supply systems consist of a number of pumping stations, which deliver water to the customers via pipeline networks and elevated reservoirs. A huge amount of drinking water is lost before it reaches to end-users due to the leakage in pipe networks. A cost effective solution to reduce leakage...... in water network is pressure management. By reducing the pressure in the water network, the leakage can be reduced significantly. Also it reduces the amount of energy consumption in water networks. The primary purpose of this work is to develop control algorithms for pressure control in water supply...

  18. Dynamic modeling and control of CFSTF

    International Nuclear Information System (INIS)

    Danesh, Y.; Jalali Farahani, F.

    2001-01-01

    This paper deals with the modeling and control of a continuous-flow fermentation process for the production of alcohol: The dynamic behavior of ferment ors has been developed from mass balance and leads to nonlinear differential equations. Based on the proposed model, two computer algorithms are provided to control output alcohol concentration at the desired value by input flow rate manipulation. The first algorithm is based on a conventional Proportional-Integral-Derivative, in which its parameters are determined in a trial and error procedure. The second algorithm is based on optimal controllers. In this way, the difference between output alcohol concentration and desired value is minimized by flow rate manipulation. Minimization (optimization) is done based on the MARQYARDT procedure. The advantages of this method over the conventional Proportional-Integral-Derivative controller are its higher speed and lack of overshoot

  19. Ising model for packet routing control

    International Nuclear Information System (INIS)

    Horiguchi, Tsuyoshi; Takahashi, Hideyuki; Hayashi, Keisuke; Yamaguchi, Chiaki

    2004-01-01

    For packet routing control in computer networks, we propose an Ising model which is defined in order to express competition among a queue length and a distance from a node with a packet to its destination node. By introducing a dynamics for a mean-field value of an Ising spin, we show by computer simulations that effective control of packet routing through priority links is possible

  20. Measurement control program at model facility

    International Nuclear Information System (INIS)

    Schneider, R.A.

    1984-01-01

    A measurement control program for the model plant is described. The discussion includes the technical basis for such a program, the application of measurement control principles to each measurement, and the use of special experiments to estimate measurement error parameters for difficult-to-measure materials. The discussion also describes the statistical aspects of the program, and the documentation procedures used to record, maintain, and process the basic data

  1. Optimization control of LNG regasification plant using Model Predictive Control

    Science.gov (United States)

    Wahid, A.; Adicandra, F. F.

    2018-03-01

    Optimization of liquified natural gas (LNG) regasification plant is important to minimize costs, especially operational costs. Therefore, it is important to choose optimum LNG regasification plant design and maintaining the optimum operating conditions through the implementation of model predictive control (MPC). Optimal tuning parameter for MPC such as P (prediction horizon), M (control of the horizon) and T (sampling time) are achieved by using fine-tuning method. The optimal criterion for design is the minimum amount of energy used and for control is integral of square error (ISE). As a result, the optimum design is scheme 2 which is developed by Devold with an energy savings of 40%. To maintain the optimum conditions, required MPC with P, M and T as follows: tank storage pressure: 90, 2, 1; product pressure: 95, 2, 1; temperature vaporizer: 65, 2, 2; and temperature heater: 35, 6, 5, with ISE value at set point tracking respectively 0.99, 1792.78, 34.89 and 7.54, or improvement of control performance respectively 4.6%, 63.5%, 3.1% and 58.2% compared to PI controller performance. The energy savings that MPC controllers can make when there is a disturbance in temperature rise 1°C of sea water is 0.02 MW.

  2. Model predictive control of a wind turbine modelled in Simpack

    International Nuclear Information System (INIS)

    Jassmann, U; Matzke, D; Reiter, M; Abel, D; Berroth, J; Schelenz, R; Jacobs, G

    2014-01-01

    Wind turbines (WT) are steadily growing in size to increase their power production, which also causes increasing loads acting on the turbine's components. At the same time large structures, such as the blades and the tower get more flexible. To minimize this impact, the classical control loops for keeping the power production in an optimum state are more and more extended by load alleviation strategies. These additional control loops can be unified by a multiple-input multiple-output (MIMO) controller to achieve better balancing of tuning parameters. An example for MIMO control, which has been paid more attention to recently by wind industry, is Model Predictive Control (MPC). In a MPC framework a simplified model of the WT is used to predict its controlled outputs. Based on a user-defined cost function an online optimization calculates the optimal control sequence. Thereby MPC can intrinsically incorporate constraints e.g. of actuators. Turbine models used for calculation within the MPC are typically simplified. For testing and verification usually multi body simulations, such as FAST, BLADED or FLEX5 are used to model system dynamics, but they are still limited in the number of degrees of freedom (DOF). Detailed information about load distribution (e.g. inside the gearbox) cannot be provided by such models. In this paper a Model Predictive Controller is presented and tested in a co-simulation with SlMPACK, a multi body system (MBS) simulation framework used for detailed load analysis. The analysis are performed on the basis of the IME6.0 MBS WT model, described in this paper. It is based on the rotor of the NREL 5MW WT and consists of a detailed representation of the drive train. This takes into account a flexible main shaft and its main bearings with a planetary gearbox, where all components are modelled flexible, as well as a supporting flexible main frame. The wind loads are simulated using the NREL AERODYN v13 code which has been implemented as a routine

  3. Model predictive control of a wind turbine modelled in Simpack

    Science.gov (United States)

    Jassmann, U.; Berroth, J.; Matzke, D.; Schelenz, R.; Reiter, M.; Jacobs, G.; Abel, D.

    2014-06-01

    Wind turbines (WT) are steadily growing in size to increase their power production, which also causes increasing loads acting on the turbine's components. At the same time large structures, such as the blades and the tower get more flexible. To minimize this impact, the classical control loops for keeping the power production in an optimum state are more and more extended by load alleviation strategies. These additional control loops can be unified by a multiple-input multiple-output (MIMO) controller to achieve better balancing of tuning parameters. An example for MIMO control, which has been paid more attention to recently by wind industry, is Model Predictive Control (MPC). In a MPC framework a simplified model of the WT is used to predict its controlled outputs. Based on a user-defined cost function an online optimization calculates the optimal control sequence. Thereby MPC can intrinsically incorporate constraints e.g. of actuators. Turbine models used for calculation within the MPC are typically simplified. For testing and verification usually multi body simulations, such as FAST, BLADED or FLEX5 are used to model system dynamics, but they are still limited in the number of degrees of freedom (DOF). Detailed information about load distribution (e.g. inside the gearbox) cannot be provided by such models. In this paper a Model Predictive Controller is presented and tested in a co-simulation with SlMPACK, a multi body system (MBS) simulation framework used for detailed load analysis. The analysis are performed on the basis of the IME6.0 MBS WT model, described in this paper. It is based on the rotor of the NREL 5MW WT and consists of a detailed representation of the drive train. This takes into account a flexible main shaft and its main bearings with a planetary gearbox, where all components are modelled flexible, as well as a supporting flexible main frame. The wind loads are simulated using the NREL AERODYN v13 code which has been implemented as a routine to

  4. Model Based Control of Reefer Container Systems

    DEFF Research Database (Denmark)

    Sørensen, Kresten Kjær

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

  5. Modelling and Control of Magnetorheological Damper

    DEFF Research Database (Denmark)

    Bhowmik, Subrata

    , used as reference case for assessment of the proposed control methods with negative stiffness. Viscous damping with negative stiffness (VDNS) initially illustrates the effectiveness of the negative stiffness component in structural damping. In a linear control setting negative stiffness requires active...... damper is identified by both the standard parametric Bouc-Wen model and the non-parametric neural network model from an experimental data set generated by dynamic tests of the MR damper mounted in a hydraulic testing machine. The forward model represents the direct dynamics of the MR damper where...... are essential input parameters for the MR damper modelling. Thus, for proper training, the quality of the velocity data is very important. However, direct velocity measurement is not easy. From the displacement data or the acceleration data, velocity can be determined by using simple differentiation...

  6. Model Predictive Control of Wind Turbines

    DEFF Research Database (Denmark)

    Henriksen, Lars Christian

    Wind turbines play a major role in the transformation from a fossil fuel based energy production to a more sustainable production of energy. Total-cost-of-ownership is an important parameter when investors decide in which energy technology they should place their capital. Modern wind turbines...... the need for maintenance of the wind turbine. Either way, better total-cost-of-ownership for wind turbine operators can be achieved by improved control of the wind turbines. Wind turbine control can be improved in two ways, by improving the model on which the controller bases its design or by improving...

  7. Model Predictive Control of Sewer Networks

    DEFF Research Database (Denmark)

    Pedersen, Einar B.; Herbertsson, Hannes R.; Niemann, Henrik

    2016-01-01

    The developments in solutions for management of urban drainage are of vital importance, as the amount of sewer water from urban areas continues to increase due to the increase of the world’s population and the change in the climate conditions. How a sewer network is structured, monitored and cont...... benchmark model. Due to the inherent constraints the applied approach is based on Model Predictive Control....

  8. Control system modelling for superconducting accelerator

    International Nuclear Information System (INIS)

    Czarski, T.; Pozniak, K.; Romaniuk, R.

    2006-01-01

    A digital control of superconducting cavities for a linear accelerator is presented. The LLRF - Low Level Radio Frequency system for FLASH project in DESY is introduced. FPGA based controller supported by MATLAB system was developed to investigate the novel firmware implementation. Algebraic model in complex domain is proposed for the system analyzing. Calibration procedure of a signal path is considered for a multi-channel control. Identification of the system parameters is carried out by the least squares method application. Control tables: Feed-Forward and Set- Point are determined for the required cavity performance, according to the recognized process. Feedback loop is tuned by fitting a complex gain of a corrector unit. Adaptive control algorithm is applied for feed-forward and feedback modes. Experimental results are presented for a cavity representative operation. (orig.)

  9. Comparison Analysis of Model Predictive Controller with Classical PID Controller For pH Control Process

    Directory of Open Access Journals (Sweden)

    V. Balaji

    2016-12-01

    Full Text Available pH control plays a important role in any chemical plant and process industries. For the past four decades the classical PID controller has been occupied by the industries. Due to the faster computing   technology in the industry demands a tighter advanced control strategy. To fulfill the needs and requirements Model Predictive Control (MPC is the best among all the advanced control algorithms available in the present scenario. The study and analysis has been done for First Order plus Delay Time (FOPDT model controlled by Proportional Integral Derivative (PID and MPC using the Matlab software. This paper explores the capability of the MPC strategy, analyze and compare the control effects with conventional control strategy in pH control. A comparison results between the PID and MPC is plotted using the software. The results clearly show that MPC provide better performance than the classical controller.

  10. Model based design of electronic throttle control

    Science.gov (United States)

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

    2017-11-01

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

  11. 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

  12. MODELING MERCURY CONTROL WITH POWDERED ACTIVATED CARBON

    Science.gov (United States)

    The paper presents a mathematical model of total mercury removed from the flue gas at coal-fired plants equipped with powdered activated carbon (PAC) injection for Mercury control. The developed algorithms account for mercury removal by both existing equipment and an added PAC in...

  13. Modeling and control of antennas and telescopes

    CERN Document Server

    Gawronski, Wodek

    2008-01-01

    The book shows, step-by-step, the design, implementation, and testing of the antenna/telescope control system, from the design stage (analytical model) to fine tuning of the RF beam pointing (monopulse and conscan). It includes wide use of Matlab and Simulink..

  14. Advanced feeder control using fast simulation models

    NARCIS (Netherlands)

    Verheijen, O.S.; Op den Camp, O.M.G.C.; Beerkens, R.G.C.; Backx, A.C.P.M.; Huisman, L.; Drummond, C.H.

    2005-01-01

    For the automatic control of glass quality in glass production, the relation between process variable and product or glass quality and process conditions/process input parameters must be known in detail. So far, detailed 3-D glass melting simulation models were used to predict the effect of process

  15. Plant Modeling for Human Supervisory Control

    DEFF Research Database (Denmark)

    Lind, Morten

    1999-01-01

    This paper provides an overview of multilevel flow modelling (MFM) and its application for design of displays for the supervisory control of industrial plant. The problem of designing the inforrrzatian content of sacpervisory displays is discussed and plant representations like MFM using levels...

  16. Power system stability modelling, analysis and control

    CERN Document Server

    Sallam, Abdelhay A

    2015-01-01

    This book provides a comprehensive treatment of the subject from both a physical and mathematical perspective and covers a range of topics including modelling, computation of load flow in the transmission grid, stability analysis under both steady-state and disturbed conditions, and appropriate controls to enhance stability.

  17. Distributed Model Predictive Control via Dual Decomposition

    DEFF Research Database (Denmark)

    Biegel, Benjamin; Stoustrup, Jakob; Andersen, Palle

    2014-01-01

    This chapter presents dual decomposition as a means to coordinate a number of subsystems coupled by state and input constraints. Each subsystem is equipped with a local model predictive controller while a centralized entity manages the subsystems via prices associated with the coupling constraints...

  18. Modeling the Aneuploidy Control of Cancer

    Directory of Open Access Journals (Sweden)

    Wang Zhong

    2010-07-01

    Full Text Available Abstract Background Aneuploidy has long been recognized to be associated with cancer. A growing body of evidence suggests that tumorigenesis, the formation of new tumors, can be attributed to some extent to errors occurring at the mitotic checkpoint, a major cell cycle control mechanism that acts to prevent chromosome missegregation. However, so far no statistical model has been available quantify the role aneuploidy plays in determining cancer. Methods We develop a statistical model for testing the association between aneuploidy loci and cancer risk in a genome-wide association study. The model incorporates quantitative genetic principles into a mixture-model framework in which various genetic effects, including additive, dominant, imprinting, and their interactions, are estimated by implementing the EM algorithm. Results Under the new model, a series of hypotheses tests are formulated to explain the pattern of the genetic control of cancer through aneuploid loci. Simulation studies were performed to investigate the statistical behavior of the model. Conclusions The model will provide a tool for estimating the effects of genetic loci on aneuploidy abnormality in genome-wide studies of cancer cells.

  19. Nonsmooth mechanics models, dynamics and control

    CERN Document Server

    Brogliato, Bernard

    2016-01-01

    Now in its third edition, this standard reference is a comprehensive treatment of nonsmooth mechanical systems refocused to give more prominence to control and modelling. It covers Lagrangian and Newton–Euler systems, detailing mathematical tools such as convex analysis and complementarity theory. The ways in which nonsmooth mechanics influence and are influenced by well-posedness analysis, numerical analysis and simulation, modelling and control are explained. Contact/impact laws, stability theory and trajectory-tracking control are given in-depth exposition connected by a framework formed from complementarity systems and measure-differential inclusions. Links are established with electrical circuits with set-valued nonsmooth elements and with other nonsmooth dynamical systems like impulsive and piecewise linear systems. Nonsmooth Mechanics (third edition) has been substantially rewritten, edited and updated to account for the significant body of results that have emerged in the twenty-first century—incl...

  20. Nonlinear model predictive control theory and algorithms

    CERN Document Server

    Grüne, Lars

    2017-01-01

    This book offers readers a thorough and rigorous introduction to nonlinear model predictive control (NMPC) for discrete-time and sampled-data systems. NMPC schemes with and without stabilizing terminal constraints are detailed, and intuitive examples illustrate the performance of different NMPC variants. NMPC is interpreted as an approximation of infinite-horizon optimal control so that important properties like closed-loop stability, inverse optimality and suboptimality can be derived in a uniform manner. These results are complemented by discussions of feasibility and robustness. An introduction to nonlinear optimal control algorithms yields essential insights into how the nonlinear optimization routine—the core of any nonlinear model predictive controller—works. Accompanying software in MATLAB® and C++ (downloadable from extras.springer.com/), together with an explanatory appendix in the book itself, enables readers to perform computer experiments exploring the possibilities and limitations of NMPC. T...

  1. MODELLING OF DYNAMIC SPEED LIMITS USING THE MODEL PREDICTIVE CONTROL

    Directory of Open Access Journals (Sweden)

    Andrey Borisovich Nikolaev

    2017-09-01

    Full Text Available The article considers the issues of traffic management using intelligent system “Car-Road” (IVHS, which consist of interacting intelligent vehicles (IV and intelligent roadside controllers. Vehicles are organized in convoy with small distances between them. All vehicles are assumed to be fully automated (throttle control, braking, steering. Proposed approaches for determining speed limits for traffic cars on the motorway using a model predictive control (MPC. The article proposes an approach to dynamic speed limit to minimize the downtime of vehicles in traffic.

  2. Nonlinear Model Predictive Control for Cooperative Control and Estimation

    Science.gov (United States)

    Ru, Pengkai

    Recent advances in computational power have made it possible to do expensive online computations for control systems. It is becoming more realistic to perform computationally intensive optimization schemes online on systems that are not intrinsically stable and/or have very small time constants. Being one of the most important optimization based control approaches, model predictive control (MPC) has attracted a lot of interest from the research community due to its natural ability to incorporate constraints into its control formulation. Linear MPC has been well researched and its stability can be guaranteed in the majority of its application scenarios. However, one issue that still remains with linear MPC is that it completely ignores the system's inherent nonlinearities thus giving a sub-optimal solution. On the other hand, if achievable, nonlinear MPC, would naturally yield a globally optimal solution and take into account all the innate nonlinear characteristics. While an exact solution to a nonlinear MPC problem remains extremely computationally intensive, if not impossible, one might wonder if there is a middle ground between the two. We tried to strike a balance in this dissertation by employing a state representation technique, namely, the state dependent coefficient (SDC) representation. This new technique would render an improved performance in terms of optimality compared to linear MPC while still keeping the problem tractable. In fact, the computational power required is bounded only by a constant factor of the completely linearized MPC. The purpose of this research is to provide a theoretical framework for the design of a specific kind of nonlinear MPC controller and its extension into a general cooperative scheme. The controller is designed and implemented on quadcopter systems.

  3. Model Predictive Controller Combined with LQG Controller and Velocity Feedback to Control the Stewart Platform

    DEFF Research Database (Denmark)

    Nadimi, Esmaeil Sharak; Bak, Thomas; Izadi-Zamanabadi, Roozbeh

    2006-01-01

    The main objective of this paper is to investigate the erformance and applicability of two GPC (generalized predictive control) based control methods on a complete benchmark model of the Stewart platform made in MATLAB V6.5. The first method involves an LQG controller (Linear Quadratic Gaussian...

  4. Manual control models of industrial management

    Science.gov (United States)

    Crossman, E. R. F. W.

    1972-01-01

    The industrial engineer is often required to design and implement control systems and organization for manufacturing and service facilities, to optimize quality, delivery, and yield, and minimize cost. Despite progress in computer science most such systems still employ human operators and managers as real-time control elements. Manual control theory should therefore be applicable to at least some aspects of industrial system design and operations. Formulation of adequate model structures is an essential prerequisite to progress in this area; since real-world production systems invariably include multilevel and multiloop control, and are implemented by timeshared human effort. A modular structure incorporating certain new types of functional element, has been developed. This forms the basis for analysis of an industrial process operation. In this case it appears that managerial controllers operate in a discrete predictive mode based on fast time modelling, with sampling interval related to plant dynamics. Successive aggregation causes reduced response bandwidth and hence increased sampling interval as a function of level.

  5. Integrated soft sensor model for flow control.

    Science.gov (United States)

    Aijälä, G; Lumley, D

    2006-01-01

    Tighter discharge permits often require wastewater treatment plants to maximize utilization of available facilities in order to cost-effectively reach these goals. Important aspects are minimizing internal disturbances and using available information in a smart way to improve plant performance. In this study, flow control throughout a large highly automated wastewater treatment plant (WWTP) was implemented in order to reduce internal disturbances and to provide a firm foundation for more advanced process control. A modular flow control system was constructed based on existing instrumentation and soft sensor flow models. Modules were constructed for every unit process in water treatment and integrated into a plant-wide model. The flow control system is used to automatically control recirculation flows and bypass flows at the plant. The system was also successful in making accurate flow estimations at points in the plant where it is not possible to have conventional flow meter instrumentation. The system provides fault detection for physical flow measuring devices. The module construction allows easy adaptation for new unit processes added to the treatment plant.

  6. Modeling and Control of Underwater Robotic Systems

    Energy Technology Data Exchange (ETDEWEB)

    Schjoelberg, I:

    1996-12-31

    This doctoral thesis describes modeling and control of underwater vehicle-manipulator systems. The thesis also presents a model and a control scheme for a system consisting of a surface vessel connected to an underwater robotic system by means of a slender marine structure. The equations of motion of the underwater vehicle and manipulator are described and the system kinematics and properties presented. Feedback linearization technique is applied to the system and evaluated through a simulation study. Passivity-based controllers for vehicle and manipulator control are presented. Stability of the closed loop system is proved and simulation results are given. The equation of motion for lateral motion of a cable/riser system connected to a surface vessel at the top end and to a thruster at the bottom end is described and stability analysis and simulations are presented. The equations of motion in 3 degrees of freedom of the cable/riser, surface vessel and robotic system are given. Stability analysis of the total system with PD-controllers is presented. 47 refs., 32 figs., 7 tabs.

  7. Models, controls, and levels of semiotic autonomy

    Energy Technology Data Exchange (ETDEWEB)

    Joslyn, C.

    1998-12-01

    In this paper the authors consider forms of autonomy, forms of semiotic systems, and any necessary relations among them. Levels of autonomy are identified as levels of system identity, from adiabatic closure to disintegration. Forms of autonomy or closure in systems are also recognized, including physical, dynamical, functional, and semiotic. Models and controls are canonical linear and circular (closed) semiotic relations respectively. They conclude that only at higher levels of autonomy do semiotic properties become necessary. In particular, all control systems display at least a minimal degree of semiotic autonomy; and all systems with sufficiently interesting functional autonomy are semiotically related to their environments.

  8. Modeling and control of flexible space structures

    Science.gov (United States)

    Wie, B.; Bryson, A. E., Jr.

    1981-01-01

    The effects of actuator and sensor locations on transfer function zeros are investigated, using uniform bars and beams as generic models of flexible space structures. It is shown how finite element codes may be used directly to calculate transfer function zeros. The impulse response predicted by finite-dimensional models is compared with the exact impulse response predicted by the infinite dimensional models. It is shown that some flexible structures behave as if there were a direct transmission between actuator and sensor (equal numbers of zeros and poles in the transfer function). Finally, natural damping models for a vibrating beam are investigated since natural damping has a strong influence on the appropriate active control logic for a flexible structure.

  9. Data Driven Economic Model Predictive Control

    Directory of Open Access Journals (Sweden)

    Masoud Kheradmandi

    2018-04-01

    Full Text Available This manuscript addresses the problem of data driven model based economic model predictive control (MPC design. To this end, first, a data-driven Lyapunov-based MPC is designed, and shown to be capable of stabilizing a system at an unstable equilibrium point. The data driven Lyapunov-based MPC utilizes a linear time invariant (LTI model cognizant of the fact that the training data, owing to the unstable nature of the equilibrium point, has to be obtained from closed-loop operation or experiments. Simulation results are first presented demonstrating closed-loop stability under the proposed data-driven Lyapunov-based MPC. The underlying data-driven model is then utilized as the basis to design an economic MPC. The economic improvements yielded by the proposed method are illustrated through simulations on a nonlinear chemical process system example.

  10. Modeling and control of active twist aircraft

    Science.gov (United States)

    Cramer, Nicholas Bryan

    The Wright Brothers marked the beginning of powered flight in 1903 using an active twist mechanism as their means of controlling roll. As time passed due to advances in other technologies that transformed aviation the active twist mechanism was no longer used. With the recent advances in material science and manufacturability, the possibility of the practical use of active twist technologies has emerged. In this dissertation, the advantages and disadvantages of active twist techniques are investigated through the development of an aeroelastic modeling method intended for informing the designs of such technologies and wind tunnel testing to confirm the capabilities of the active twist technologies and validate the model. Control principles for the enabling structural technologies are also proposed while the potential gains of dynamic, active twist are analyzed.

  11. Snake Robots Modelling, Mechatronics, and Control

    CERN Document Server

    Liljebäck, Pål; Stavdahl, Øyvind; Gravdahl, Jan Tommy

    2013-01-01

    Snake Robots is a novel treatment of theoretical and practical topics related to snake robots: robotic mechanisms designed to move like biological snakes and able to operate in challenging environments in which human presence is either undesirable or impossible. Future applications of such robots include search and rescue, inspection and maintenance, and subsea operations. Locomotion in unstructured environments is a focus for this book. The text targets the disparate muddle of approaches to modelling, development and control of snake robots in current literature, giving a unified presentation of recent research results on snake robot locomotion to increase the reader’s basic understanding of these mechanisms and their motion dynamics and clarify the state of the art in the field. The book is a complete treatment of snake robotics, with topics ranging from mathematical modelling techniques, through mechatronic design and implementation, to control design strategies. The development of two snake robots is de...

  12. Adaptive Control with Reference Model Modification

    Science.gov (United States)

    Stepanyan, Vahram; Krishnakumar, Kalmanje

    2012-01-01

    This paper presents a modification of the conventional model reference adaptive control (MRAC) architecture in order to improve transient performance of the input and output signals of uncertain systems. A simple modification of the reference model is proposed by feeding back the tracking error signal. It is shown that the proposed approach guarantees tracking of the given reference command and the reference control signal (one that would be designed if the system were known) not only asymptotically but also in transient. Moreover, it prevents generation of high frequency oscillations, which are unavoidable in conventional MRAC systems for large adaptation rates. The provided design guideline makes it possible to track a reference commands of any magnitude from any initial position without re-tuning. The benefits of the method are demonstrated with a simulation example

  13. Hierarchical Model Predictive Control for Resource Distribution

    DEFF Research Database (Denmark)

    Bendtsen, Jan Dimon; Trangbæk, K; Stoustrup, Jakob

    2010-01-01

    units. The approach is inspired by smart-grid electric power production and consumption systems, where the flexibility of a large number of power producing and/or power consuming units can be exploited in a smart-grid solution. The objective is to accommodate the load variation on the grid, arising......This paper deals with hierarchichal model predictive control (MPC) of distributed systems. A three level hierachical approach is proposed, consisting of a high level MPC controller, a second level of so-called aggregators, controlled by an online MPC-like algorithm, and a lower level of autonomous...... on one hand from varying consumption, on the other hand by natural variations in power production e.g. from wind turbines. The approach presented is based on quadratic optimization and possess the properties of low algorithmic complexity and of scalability. In particular, the proposed design methodology...

  14. Global nuclear material flow/control model

    International Nuclear Information System (INIS)

    Dreicer, J.S.; Rutherford, D.S.; Fasel, P.K.; Riese, J.M.

    1997-01-01

    This is the final report of a two-year, Laboratory Directed Research and Development (LDRD) project at the Los Alamos National Laboratory (LANL). The nuclear danger can be reduced by a system for global management, protection, control, and accounting as part of an international regime for nuclear materials. The development of an international fissile material management and control regime requires conceptual research supported by an analytical and modeling tool which treats the nuclear fuel cycle as a complete system. The prototype model developed visually represents the fundamental data, information, and capabilities related to the nuclear fuel cycle in a framework supportive of national or an international perspective. This includes an assessment of the global distribution of military and civilian fissile material inventories, a representation of the proliferation pertinent physical processes, facility specific geographic identification, and the capability to estimate resource requirements for the management and control of nuclear material. The model establishes the foundation for evaluating the global production, disposition, and safeguards and security requirements for fissile nuclear material and supports the development of other pertinent algorithmic capabilities necessary to undertake further global nuclear material related studies

  15. Modelling and Control of Thermal System

    Directory of Open Access Journals (Sweden)

    Vratislav Hladky

    2014-01-01

    Full Text Available Work presented here deals with the modelling of thermal processes in a thermal system consisting of direct and indirect heat exchangers. The overal thermal properties of the medium and the system itself such as liquid mixing or heat capacity are shortly analysed and their features required for modelling are reasoned and therefore simplified or neglected. Special attention is given to modelling heat losses radiated into the surroundings through the walls as they are the main issue of the effective work with the heat systems. Final part of the paper proposes several ways of controlling the individual parts’ temperatures as well as the temperature of the system considering heating elements or flowage rate as actuators.

  16. Mathematical modeling for control zika transmission

    Science.gov (United States)

    Nugraha, Edwin Setiawan; Naiborhu, Janson; Nuraini, Nuning; Ahmadin

    2017-11-01

    After 70 years since the zika was identified in Uganda, zika is now documented in 62 countries. In general, people infected with this disease do not experience severe conditions, but for pregnant women can cause serious problems because the zika can spread to the fetus. One result, zika can cause abnormalities in the fetal brain called microcephaly. Control and prevention are very important to reduce the spread of this disease. Here, we discussed the problem of optimal control in the model of zika transmission associated with the use of insecticide-treated nets (ITN) and indoor residual spraying (IRS). Using the approach of optimal control theory, we completed the objective function so that the infected population and its control cost are minimum. Numerically using the Forward-Backward Sweep Method, we obtained the control design of ITN and IRS as a function of time. The results show that the use of both simultaneously is more effective in reducing the population of infection than the use of ITN alone or the IRS alone.

  17. Model predictive control of a crude oil distillation column

    Directory of Open Access Journals (Sweden)

    Morten Hovd

    1999-04-01

    Full Text Available The project of designing and implementing model based predictive control on the vacuum distillation column at the Nynäshamn Refinery of Nynäs AB is described in this paper. The paper describes in detail the modeling for the model based control, covers the controller implementation, and documents the benefits gained from the model based controller.

  18. Model Predictive Control based on Finite Impulse Response Models

    DEFF Research Database (Denmark)

    Prasath, Guru; Jørgensen, John Bagterp

    2008-01-01

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

  19. A model of optimal voluntary muscular control.

    Science.gov (United States)

    FitzHugh, R

    1977-07-19

    In the absence of detailed knowledge of how the CNS controls a muscle through its motor fibers, a reasonable hypothesis is that of optimal control. This hypothesis is studied using a simplified mathematical model of a single muscle, based on A.V. Hill's equations, with series elastic element omitted, and with the motor signal represented by a single input variable. Two cost functions were used. The first was total energy expended by the muscle (work plus heat). If the load is a constant force, with no inertia, Hill's optimal velocity of shortening results. If the load includes a mass, analysis by optimal control theory shows that the motor signal to the muscle consists of three phases: (1) maximal stimulation to accelerate the mass to the optimal velocity as quickly as possible, (2) an intermediate level of stimulation to hold the velocity at its optimal value, once reached, and (3) zero stimulation, to permit the mass to slow down, as quickly as possible, to zero velocity at the specified distance shortened. If the latter distance is too small, or the mass too large, the optimal velocity is not reached, and phase (2) is absent. For lengthening, there is no optimal velocity; there are only two phases, zero stimulation followed by maximal stimulation. The second cost function was total time. The optimal control for shortening consists of only phases (1) and (3) above, and is identical to the minimal energy control whenever phase (2) is absent from the latter. Generalization of this model to include viscous loads and a series elastic element are discussed.

  20. Performance and robustness of hybrid model predictive control for controllable dampers in building models

    Science.gov (United States)

    Johnson, Erik A.; Elhaddad, Wael M.; Wojtkiewicz, Steven F.

    2016-04-01

    A variety of strategies have been developed over the past few decades to determine controllable damping device forces to mitigate the response of structures and mechanical systems to natural hazards and other excitations. These "smart" damping devices produce forces through passive means but have properties that can be controlled in real time, based on sensor measurements of response across the structure, to dramatically reduce structural motion by exploiting more than the local "information" that is available to purely passive devices. A common strategy is to design optimal damping forces using active control approaches and then try to reproduce those forces with the smart damper. However, these design forces, for some structures and performance objectives, may achieve high performance by selectively adding energy, which cannot be replicated by a controllable damping device, causing the smart damper performance to fall far short of what an active system would provide. The authors have recently demonstrated that a model predictive control strategy using hybrid system models, which utilize both continuous and binary states (the latter to capture the switching behavior between dissipative and non-dissipative forces), can provide reductions in structural response on the order of 50% relative to the conventional clipped-optimal design strategy. This paper explores the robustness of this newly proposed control strategy through evaluating controllable damper performance when the structure model differs from the nominal one used to design the damping strategy. Results from the application to a two-degree-of-freedom structure model confirms the robustness of the proposed strategy.

  1. Control mechanisms for a nonlinear model of international relations

    Energy Technology Data Exchange (ETDEWEB)

    Pentek, A.; Kadtke, J. [Univ. of California, San Diego, La Jolla, CA (United States). Inst. for Pure and Applied Physical Sciences; Lenhart, S. [Univ. of Tennessee, Knoxville, TN (United States). Mathematics Dept.; Protopopescu, V. [Oak Ridge National Lab., TN (United States). Computer Science and Mathematics Div.

    1997-07-15

    Some issues of control in complex dynamical systems are considered. The authors discuss two control mechanisms, namely: a short range, reactive control based on the chaos control idea and a long-term strategic control based on an optimal control algorithm. They apply these control ideas to simple examples in a discrete nonlinear model of a multi-nation arms race.

  2. Robust intelligent sliding model control using recurrent cerebellar model articulation controller for uncertain nonlinear chaotic systems

    International Nuclear Information System (INIS)

    Peng Yafu

    2009-01-01

    In this paper, a robust intelligent sliding model control (RISMC) scheme using an adaptive recurrent cerebellar model articulation controller (RCMAC) is developed for a class of uncertain nonlinear chaotic systems. This RISMC system offers a design approach to drive the state trajectory to track a desired trajectory, and it is comprised of an adaptive RCMAC and a robust controller. The adaptive RCMAC is used to mimic an ideal sliding mode control (SMC) due to unknown system dynamics, and a robust controller is designed to recover the residual approximation error for guaranteeing the stable characteristic. Moreover, the Taylor linearization technique is employed to derive the linearized model of the RCMAC. The all adaptation laws of the RISMC system are derived based on the Lyapunov stability analysis and projection algorithm, so that the stability of the system can be guaranteed. Finally, the proposed RISMC system is applied to control a Van der Pol oscillator, a Genesio chaotic system and a Chua's chaotic circuit. The effectiveness of the proposed control scheme is verified by some simulation results with unknown system dynamics and existence of external disturbance. In addition, the advantages of the proposed RISMC are indicated in comparison with a SMC system

  3. Modeling and control of dialysis systems

    CERN Document Server

    2013-01-01

    This book is the first text of its kind that presents both the traditional and the modern aspects of dialysis modeling and control in a clear, insightful and highly comprehensive writing style. It provides an in-depth analysis of the mathematical models and algorithms, and demonstrates their applications in real world problems of significant complexity. It explains concepts in a clear, matter-of-fact style. The material of this book will be useful to advanced undergraduate and graduate biomedical engineering students. Also, researchers and practitioners in the field of dialysis, control systems, soft computing will benefit from it. In order to make the reader aware of the applied side of the subject, the book includes:       Chapter openers with a chapter outline, chapter objectives, key terms list, and abstract.       Solved numerical examples to illustrate the application of a particular concept, and also to encourage good problem-solving skills.       More than 1000 questions to give the rea...

  4. Nonconvex model predictive control for commercial refrigeration

    Science.gov (United States)

    Gybel Hovgaard, Tobias; Boyd, Stephen; Larsen, Lars F. S.; Bagterp Jørgensen, John

    2013-08-01

    We consider the control of a commercial multi-zone refrigeration system, consisting of several cooling units that share a common compressor, and is used to cool multiple areas or rooms. In each time period we choose cooling capacity to each unit and a common evaporation temperature. The goal is to minimise the total energy cost, using real-time electricity prices, while obeying temperature constraints on the zones. We propose a variation on model predictive control to achieve this goal. When the right variables are used, the dynamics of the system are linear, and the constraints are convex. The cost function, however, is nonconvex due to the temperature dependence of thermodynamic efficiency. To handle this nonconvexity we propose a sequential convex optimisation method, which typically converges in fewer than 5 or so iterations. We employ a fast convex quadratic programming solver to carry out the iterations, which is more than fast enough to run in real time. We demonstrate our method on a realistic model, with a full year simulation and 15-minute time periods, using historical electricity prices and weather data, as well as random variations in thermal load. These simulations show substantial cost savings, on the order of 30%, compared to a standard thermostat-based control system. Perhaps more important, we see that the method exhibits sophisticated response to real-time variations in electricity prices. This demand response is critical to help balance real-time uncertainties in generation capacity associated with large penetration of intermittent renewable energy sources in a future smart grid.

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

    International Nuclear Information System (INIS)

    Sidhu, S.S.

    1987-01-01

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

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

    OpenAIRE

    Shrivastava, Piyush

    2012-01-01

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

  7. 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...

  8. Wind turbine model and loop shaping controller design

    Science.gov (United States)

    Gilev, Bogdan

    2017-12-01

    A model of a wind turbine is evaluated, consisting of: wind speed model, mechanical and electrical model of generator and tower oscillation model. Model of the whole system is linearized around of a nominal point. By using the linear model with uncertainties is synthesized a uncertain model. By using the uncertain model is developed a H∞ controller, which provide mode of stabilizing the rotor frequency and damping the tower oscillations. Finally is simulated work of nonlinear system and H∞ controller.

  9. Modeling and control in the biomedical sciences

    CERN Document Server

    Banks, H T

    1975-01-01

    These notes are based on (i) a series of lectures that I gave at the 14th Biennial Seminar of the Canadian Mathematical Congress held at the University of Western Ontario August 12-24, 1973 and (li) some of my lectures in a modeling course that I have cotaught in the Division of Bio-Medical Sciences at Brown during the past several years. An earlier version of these notes appeared in the Center for Dynamical Systems Lectures Notes series (CDS LN 73-1, November 1973). I have in this revised and extended version of those earlier notes incorporated a number of changes based both on classroom experience and on my research efforts with several colleagues during the intervening period. The narrow viewpoint of the present notes (use of optimization and control theory in biomedical problems) reflects more the scope of the CMC lectures given in August, 1973 than the scope of my own interests. Indeed, my real interests have included the modeling process itself as well as the contributions made by investiga­ tors who e...

  10. Model Predictive Control with Constraints of a Wind Turbine

    DEFF Research Database (Denmark)

    Henriksen, Lars Christian; Poulsen, Niels Kjølstad

    2007-01-01

    Model predictive control of wind turbines offer a more systematic approach of constructing controllers that handle constraints while focusing on the main control objective. In this article several controllers are designed for different wind conditions and appropriate switching conditions ensure a...... an efficient control of the wind turbine over the entire range of wind speeds. Both onshore and floating offshore wind turbines are tested with the controllers.......Model predictive control of wind turbines offer a more systematic approach of constructing controllers that handle constraints while focusing on the main control objective. In this article several controllers are designed for different wind conditions and appropriate switching conditions ensure...

  11. 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.

  12. General model and control of an n rotor helicopter

    International Nuclear Information System (INIS)

    Sidea, A G; Brogaard, R Yding; Andersen, N A; Ravn, O

    2014-01-01

    The purpose of this study was to create a dynamic, nonlinear mathematical model of a multirotor that would be valid for different numbers of rotors. Furthermore, a set of Single Input Single Output (SISO) controllers were implemented for attitude control. Both model and controllers were tested experimentally on a quadcopter. Using the combined model and controllers, simple system simulation and control is possible, by replacing the physical values for the individual systems

  13. General model and control of an n rotor helicopter

    Science.gov (United States)

    Sidea, A. G.; Yding Brogaard, R.; Andersen, N. A.; Ravn, O.

    2014-12-01

    The purpose of this study was to create a dynamic, nonlinear mathematical model of a multirotor that would be valid for different numbers of rotors. Furthermore, a set of Single Input Single Output (SISO) controllers were implemented for attitude control. Both model and controllers were tested experimentally on a quadcopter. Using the combined model and controllers, simple system simulation and control is possible, by replacing the physical values for the individual systems.

  14. Nuclear reactor power control system based on flexibility model

    International Nuclear Information System (INIS)

    Li Gang; Zhao Fuyu; Li Chong; Tai Yun

    2011-01-01

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

  15. 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...

  16. Model Predictive Control for Integrating Traffic Control Measures

    NARCIS (Netherlands)

    Hegyi, A.

    2004-01-01

    Dynamic traffic control measures, such as ramp metering and dynamic speed limits, can be used to better utilize the available road capacity. Due to the increasing traffic volumes and the increasing number of traffic jams the interaction between the control measures has increased such that local

  17. On Model Based Synthesis of Embedded Control Software

    OpenAIRE

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

    2012-01-01

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

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

    International Nuclear Information System (INIS)

    Casella, R.A.

    1987-01-01

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

  19. Catalytic cracking models developed for predictive control purposes

    Directory of Open Access Journals (Sweden)

    Dag Ljungqvist

    1993-04-01

    Full Text Available The paper deals with state-space modeling issues in the context of model-predictive control, with application to catalytic cracking. Emphasis is placed on model establishment, verification and online adjustment. Both the Fluid Catalytic Cracking (FCC and the Residual Catalytic Cracking (RCC units are discussed. Catalytic cracking units involve complex interactive processes which are difficult to operate and control in an economically optimal way. The strong nonlinearities of the FCC process mean that the control calculation should be based on a nonlinear model with the relevant constraints included. However, the model can be simple compared to the complexity of the catalytic cracking plant. Model validity is ensured by a robust online model adjustment strategy. Model-predictive control schemes based on linear convolution models have been successfully applied to the supervisory dynamic control of catalytic cracking units, and the control can be further improved by the SSPC scheme.

  20. Wind turbine control with constraint handling: a model predictive control approach

    DEFF Research Database (Denmark)

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

    2012-01-01

    on model predictive control, a control method well suited for constraint handling. The performance of the presented controller during an extreme operating gust is compared to that of a proportional-integral controller with integrator anti-windup. Furthermore, the presented controller-s capability...

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

    International Nuclear Information System (INIS)

    Casella, R.A.

    1987-01-01

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

  2. Control System Design for Cylindrical Tank Process Using Neural Model Predictive Control Technique

    Directory of Open Access Journals (Sweden)

    M. Sridevi

    2010-10-01

    Full Text Available Chemical manufacturing and process industry requires innovative technologies for process identification. This paper deals with model identification and control of cylindrical process. Model identification of the process was done using ARMAX technique. A neural model predictive controller was designed for the identified model. The performance of the controllers was evaluated using MATLAB software. The performance of NMPC controller was compared with Smith Predictor controller and IMC controller based on rise time, settling time, overshoot and ISE and it was found that the NMPC controller is better suited for this process.

  3. Generic Model Predictive Control Framework for Advanced Driver Assistance Systems

    NARCIS (Netherlands)

    Wang, M.

    2014-01-01

    This thesis deals with a model predictive control framework for control design of Advanced Driver Assistance Systems, where car-following tasks are under control. The framework is applied to design several autonomous and cooperative controllers and to examine the controller properties at the

  4. A Design Method of Robust Servo Internal Model Control with Control Input Saturation

    OpenAIRE

    山田, 功; 舩見, 洋祐

    2001-01-01

    In the present paper, we examine a design method of robust servo Internal Model Control with control input saturation. First of all, we clarify the condition that Internal Model Control has robust servo characteristics for the system with control input saturation. From this consideration, we propose new design method of Internal Model Control with robust servo characteristics. A numerical example to illustrate the effectiveness of the proposed method is shown.

  5. Behavioural Models of Motor Control and Short-Term Memory

    OpenAIRE

    Imanaka, Kuniyasu; Funase, Kozo; Yamauchi, Masaki

    1995-01-01

    We examined in this review article the behavioural and conceptual models of motor control and short-term memory which have intensively been investigated since the 1970s. First, we reviewed both the dual-storage model of short-term memory in which movement information is stored and a typical model of motor control which emphasizes the importance of efferent factors. We then examined two models of preselection effects: a cognitive model and a cognitive/ efferent model. Following this we reviewe...

  6. High pressure common rail injection system modeling and control.

    Science.gov (United States)

    Wang, H P; Zheng, D; Tian, Y

    2016-07-01

    In this paper modeling and common-rail pressure control of high pressure common rail injection system (HPCRIS) is presented. The proposed mathematical model of high pressure common rail injection system which contains three sub-systems: high pressure pump sub-model, common rail sub-model and injector sub-model is a relative complicated nonlinear system. The mathematical model is validated by the software Matlab and a virtual detailed simulation environment. For the considered HPCRIS, an effective model free controller which is called Extended State Observer - based intelligent Proportional Integral (ESO-based iPI) controller is designed. And this proposed method is composed mainly of the referred ESO observer, and a time delay estimation based iPI controller. Finally, to demonstrate the performances of the proposed controller, the proposed ESO-based iPI controller is compared with a conventional PID controller and ADRC. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

  7. Towards a South African crowd control model

    CSIR Research Space (South Africa)

    Modise, M

    2013-03-01

    Full Text Available . Phase 3, will be the development of decision support system for crowd control. This paper discusses Phase 1 of the project, which includes identification of various variables regarding crowd control and their relationships. During the Arab Spring...

  8. Modeling of Control Costs, Emissions, and Control Retrofits for Cost Effectiveness and Feasibility Analyses

    Science.gov (United States)

    Learn about EPA’s use of the Integrated Planning Model (IPM) to develop estimates of SO2 and NOx emission control costs, projections of futureemissions, and projections of capacity of future control retrofits, assuming controls on EGUs.

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

    Science.gov (United States)

    Luh, Cheng-Jye; Zeigler, Bernard P.

    1993-01-01

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

  10. Functional Dual Adaptive Control with Recursive Gaussian Process Model

    International Nuclear Information System (INIS)

    Prüher, Jakub; Král, Ladislav

    2015-01-01

    The paper deals with dual adaptive control problem, where the functional uncertainties in the system description are modelled by a non-parametric Gaussian process regression model. Current approaches to adaptive control based on Gaussian process models are severely limited in their practical applicability, because the model is re-adjusted using all the currently available data, which keeps growing with every time step. We propose the use of recursive Gaussian process regression algorithm for significant reduction in computational requirements, thus bringing the Gaussian process-based adaptive controllers closer to their practical applicability. In this work, we design a bi-criterial dual controller based on recursive Gaussian process model for discrete-time stochastic dynamic systems given in an affine-in-control form. Using Monte Carlo simulations, we show that the proposed controller achieves comparable performance with the full Gaussian process-based controller in terms of control quality while keeping the computational demands bounded. (paper)

  11. Modeling And Position Control Of Scara Type 3D Printer

    Directory of Open Access Journals (Sweden)

    Ahmet Saygamp305n Ogulmuamp351

    2015-08-01

    Full Text Available In this work a scara robot type 3D printer system is dynamically modeled and position control of the system is realized. For this aim computer aided design model of three degrees of freedom robotic system is created using SolidWorks program then obtained model is exported to MATLABSimMechanics software for position control. Also mathematical model of servo motors used in robotic 3D printer system is included in control methodology to design proportional controllers. Uncontrolled and controlled position results are simulated and given in the form of the graphics.

  12. 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...

  13. 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...

  14. Optimal treatment interruptions control of TB transmission model

    Science.gov (United States)

    Nainggolan, Jonner; Suparwati, Titik; Kawuwung, Westy B.

    2018-03-01

    A tuberculosis model which incorporates treatment interruptions of infectives is established. Optimal control of individuals infected with active TB is given in the model. It is obtained that the control reproduction numbers is smaller than the reproduction number, this means treatment controls could optimize the decrease in the spread of active TB. For this model, controls on treatment of infection individuals to reduce the actively infected individual populations, by application the Pontryagins Maximum Principle for optimal control. The result further emphasized the importance of controlling disease relapse in reducing the number of actively infected and treatment interruptions individuals with tuberculosis.

  15. Design, modeling and control of nanopositioning systems

    CERN Document Server

    Fleming, Andrew J

    2014-01-01

    Covering the complete design cycle of nanopositioning systems, this is the first comprehensive text on the topic. The book first introduces concepts associated with nanopositioning stages and outlines their application in such tasks as scanning probe microscopy, nanofabrication, data storage, cell surgery and precision optics. Piezoelectric transducers, employed ubiquitously in nanopositioning applications are then discussed in detail including practical considerations and constraints on transducer response. The reader is then given an overview of the types of nanopositioner before the text turns to the in-depth coverage of mechanical design including flexures, materials, manufacturing techniques, and electronics. This process is illustrated by the example of a high-speed serial-kinematic nanopositioner. Position sensors are then catalogued and described and the text then focuses on control. Several forms of control are treated: shunt control, feedback control, force feedback control and feedforward control (...

  16. Modeling, simulation and control of fermentation processes

    OpenAIRE

    Aros, Nelson; Cifuentes, Marcelo; Mardones, Javier

    2011-01-01

    Se presenta un simulador en ambiente Matlab/Simulink para controlar el proceso de fermentación, diseñando una ley de control invariante, luego un control estabilizante para mantener la planta dentro del sistema de referencia y finalmente un control estabilizante mejorado con la implementación de un controlador difuso. El modelo Monod es utilizado y vía simulación se prueban las estrategias aludidas para controlar la tasa de crecimiento específica de la biomasa. El control estabilizante aplica...

  17. Robust control design verification using the modular modeling system

    International Nuclear Information System (INIS)

    Edwards, R.M.; Ben-Abdennour, A.; Lee, K.Y.

    1991-01-01

    The Modular Modeling System (B ampersand W MMS) is being used as a design tool to verify robust controller designs for improving power plant performance while also providing fault-accommodating capabilities. These controllers are designed based on optimal control theory and are thus model based controllers which are targeted for implementation in a computer based digital control environment. The MMS is being successfully used to verify that the controllers are tolerant of uncertainties between the plant model employed in the controller and the actual plant; i.e., that they are robust. The two areas in which the MMS is being used for this purpose is in the design of (1) a reactor power controller with improved reactor temperature response, and (2) the design of a multiple input multiple output (MIMO) robust fault-accommodating controller for a deaerator level and pressure control problem

  18. Longitudinal Control for Mengshi Autonomous Vehicle via Gauss Cloud Model

    Directory of Open Access Journals (Sweden)

    Hongbo Gao

    2017-12-01

    Full Text Available Dynamic robustness and stability control is a requirement for self-driving of autonomous vehicle. Longitudinal control technique of autonomous vehicle is basic theory and one key complex technique which must have the reliability and precision of vehicle controller. The longitudinal control technique is one of the foundations of the safety and stability of autonomous vehicle control. In our paper, we present a longitudinal control algorithm based on cloud model for Mengshi autonomous vehicle to ensure the dynamic stability and tracking performance of Mengshi autonomous vehicle. The longitudinal control algorithm mainly uses cloud model generator to control the acceleration of the autonomous vehicle to achieve the goal that controls the speed of Mengshi autonomous vehicle. The proposed longitudinal control algorithm based on cloud model is verified by real experiments on Highway driving scene. The experiments results of the acceleration and speed show that the algorithm is validity and stability.

  19. Hybrid Adaptive Flight Control with Model Inversion Adaptation

    Science.gov (United States)

    Nguyen, Nhan

    2011-01-01

    This study investigates a hybrid adaptive flight control method as a design possibility for a flight control system that can enable an effective adaptation strategy to deal with off-nominal flight conditions. The hybrid adaptive control blends both direct and indirect adaptive control in a model inversion flight control architecture. The blending of both direct and indirect adaptive control provides a much more flexible and effective adaptive flight control architecture than that with either direct or indirect adaptive control alone. The indirect adaptive control is used to update the model inversion controller by an on-line parameter estimation of uncertain plant dynamics based on two methods. The first parameter estimation method is an indirect adaptive law based on the Lyapunov theory, and the second method is a recursive least-squares indirect adaptive law. The model inversion controller is therefore made to adapt to changes in the plant dynamics due to uncertainty. As a result, the modeling error is reduced that directly leads to a decrease in the tracking error. In conjunction with the indirect adaptive control that updates the model inversion controller, a direct adaptive control is implemented as an augmented command to further reduce any residual tracking error that is not entirely eliminated by the indirect adaptive control.

  20. Stabilization of model-based networked control systems

    Energy Technology Data Exchange (ETDEWEB)

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

    2016-06-08

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

  1. Model-based control for automotive applications

    NARCIS (Netherlands)

    Naus, G.J.L.

    2010-01-01

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

  2. Architecture of the Neurath Basic Model View Controller

    Directory of Open Access Journals (Sweden)

    K. Yermashov

    2006-01-01

    Full Text Available The idea of the Neurath Basic Model View Controller (NBMVC appeared during the discussion of the design of domain-specific modeling tools based on the Neurath Modeling Language [Yer06]. The NBMVC is the core of the modeling process within the modeling environment. It reduces complexity out of the design process by providing domain-specific interfaces between the developer and the model. These interfaces help to organize and manipulate the model. The organization includes, for example, a layer with visual components to drop them in and filter them out. The control routines includes, for example, model transformations.

  3. A model-based control system concept

    International Nuclear Information System (INIS)

    Aarzen, K.E.

    1992-12-01

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

  4. Design and Modelling of Thermostatically Controlled Loads as Frequency Controlled Reserve

    DEFF Research Database (Denmark)

    Xu, Zhao; Østergaard, Jacob; Togeby, Mikael

    2007-01-01

    Using demand as frequency controlled reserve (DFR) is beneficial to power systems in many aspects. To study the impacts of this technology on power system operation, control logics and simulation models of relevant loads should be carefully developed. Two advanced control logics for using demand...... frequency, is developed. The developed simulation model is able to represent a variety of aggregated thermostatically controlled loads, such as heaters or refrigerators. Uncertainties including customer behaviours and ambient temperature variation are also modelled. Preliminary simulation results...

  5. Variable-Structure Control of a Model Glider Airplane

    Science.gov (United States)

    Waszak, Martin R.; Anderson, Mark R.

    2008-01-01

    A variable-structure control system designed to enable a fuselage-heavy airplane to recover from spin has been demonstrated in a hand-launched, instrumented model glider airplane. Variable-structure control is a high-speed switching feedback control technique that has been developed for control of nonlinear dynamic systems.

  6. The semiotics of control and modeling relations in complex systems.

    Science.gov (United States)

    Joslyn, C

    2001-01-01

    We provide a conceptual analysis of ideas and principles from the systems theory discourse which underlie Pattee's semantic or semiotic closure, which is itself foundational for a school of theoretical biology derived from systems theory and cybernetics, and is now being related to biological semiotics and explicated in the relational biological school of Rashevsky and Rosen. Atomic control systems and models are described as the canonical forms of semiotic organization, sharing measurement relations, but differing topologically in that control systems are circularly and models linearly related to their environments. Computation in control systems is introduced, motivating hierarchical decomposition, hybrid modeling and control systems, and anticipatory or model-based control. The semiotic relations in complex control systems are described in terms of relational constraints, and rules and laws are distinguished as contingent and necessary functional entailments, respectively. Finally, selection as a meta-level of constraint is introduced as the necessary condition for semantic relations in control systems and models.

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

    Energy Technology Data Exchange (ETDEWEB)

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

    1999-02-01

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

  8. An integrated control-oriented modelling for HVAC performance benchmarking

    NARCIS (Netherlands)

    Satyavada, Harish; Baldi, S.

    2016-01-01

    Energy efficiency in building heating, ventilating and air conditioning (HVAC) equipment requires the development of accurate models for testing HVAC control strategies and corresponding energy consumption. In order to make the HVAC control synthesis computationally affordable, such

  9. On-line control models for the Stanford Linear Collider

    International Nuclear Information System (INIS)

    Sheppard, J.C.; Helm, R.H.; Lee, M.J.; Woodley, M.D.

    1983-03-01

    Models for computer control of the SLAC three-kilometer linear accelerator and damping rings have been developed as part of the control system for the Stanford Linear Collider. Some of these models have been tested experimentally and implemented in the control program for routine linac operations. This paper will describe the development and implementation of these models, as well as some of the operational results

  10. Fuzzy model-based control of a nuclear reactor

    International Nuclear Information System (INIS)

    Van Den Durpel, L.; Ruan, D.

    1994-01-01

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

  11. Polynomial model inversion control: numerical tests and applications

    OpenAIRE

    Novara, Carlo

    2015-01-01

    A novel control design approach for general nonlinear systems is described in this paper. The approach is based on the identification of a polynomial model of the system to control and on the on-line inversion of this model. Extensive simulations are carried out to test the numerical efficiency of the approach. Numerical examples of applicative interest are presented, concerned with control of the Duffing oscillator, control of a robot manipulator and insulin regulation in a type 1 diabetic p...

  12. Attributes Enhanced Role-Based Access Control Model

    DEFF Research Database (Denmark)

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

    2015-01-01

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

  13. Fuzzy modeling and control theory and applications

    CERN Document Server

    Matía, Fernando; Jiménez, Emilio

    2014-01-01

    Much work on fuzzy control, covering research, development and applications, has been developed in Europe since the 90's. Nevertheless, the existing books in the field are compilations of articles without interconnection or logical structure or they express the personal point of view of the author. This book compiles the developments of researchers with demonstrated experience in the field of fuzzy control following a logic structure and a unified the style. The first chapters of the book are dedicated to the introduction of the main fuzzy logic techniques, where the following chapters focus on concrete applications. This book is supported by the EUSFLAT and CEA-IFAC societies, which include a large number of researchers in the field of fuzzy logic and control. The central topic of the book, Fuzzy Control, is one of the main research and development lines covered by these associations.

  14. 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.

  15. Stability Constraints for Robust Model Predictive Control

    Directory of Open Access Journals (Sweden)

    Amanda G. S. Ottoni

    2015-01-01

    Full Text Available This paper proposes an approach for the robust stabilization of systems controlled by MPC strategies. Uncertain SISO linear systems with box-bounded parametric uncertainties are considered. The proposed approach delivers some constraints on the control inputs which impose sufficient conditions for the convergence of the system output. These stability constraints can be included in the set of constraints dealt with by existing MPC design strategies, in this way leading to the “robustification” of the MPC.

  16. Control functions in nonseparable simultaneous equations models

    OpenAIRE

    Blundell, R.; Matzkin, R. L.

    2014-01-01

    The control function approach (Heckman and Robb (1985)) in a system of linear simultaneous equations provides a convenient procedure to estimate one of the functions in the system using reduced form residuals from the other functions as additional regressors. The conditions on the structural system under which this procedure can be used in nonlinear and nonparametric simultaneous equations has thus far been unknown. In this paper, we define a new property of functions called control function ...

  17. Design of disturbances control model at automotive company

    Science.gov (United States)

    Marie, I. A.; Sari, D. K.; Astuti, P.; Teorema, M.

    2017-12-01

    The discussion was conducted at PT. XYZ which produces automotive components and motorcycle products. The company produced X123 type cylinder head which is a motor vehicle forming component. The disturbances in the production system has affected the company performance in achieving the target of Key Performance Indicator (KPI). Currently, the determination of the percentage of safety stock of cylinder head products is not in accordance to the control limits set by the company (60% - 80%), and tends to exceed the control limits that cause increasing the inventory wastage in the company. This study aims to identify the production system disturbances that occurs in the production process of manufacturing components of X123 type cylinder head products and design the control model of disturbance to obtain control action and determine the safety stock policy in accordance with the needs of the company. The design stage has been done based on the Disturbance Control Model which already existing and customized with the company need in controlling the production system disturbances at the company. The design of the disturbances control model consists of sub-model of the risk level of the disturbance, sub-model of action status, sub-model action control of the disturbance, and sub-model of determining the safety stock. The model can assist the automotive company in taking the decision to perform the disturbances control action in production system cylinder head while controlling the percentage of the safety stock.

  18. Nonlinear adaptive inverse control via the unified model neural network

    Science.gov (United States)

    Jeng, Jin-Tsong; Lee, Tsu-Tian

    1999-03-01

    In this paper, we propose a new nonlinear adaptive inverse control via a unified model neural network. In order to overcome nonsystematic design and long training time in nonlinear adaptive inverse control, we propose the approximate transformable technique to obtain a Chebyshev Polynomials Based Unified Model (CPBUM) neural network for the feedforward/recurrent neural networks. It turns out that the proposed method can use less training time to get an inverse model. Finally, we apply this proposed method to control magnetic bearing system. The experimental results show that the proposed nonlinear adaptive inverse control architecture provides a greater flexibility and better performance in controlling magnetic bearing systems.

  19. Discrete Model Reference Adaptive Control System for Automatic Profiling Machine

    Directory of Open Access Journals (Sweden)

    Peng Song

    2012-01-01

    Full Text Available Automatic profiling machine is a movement system that has a high degree of parameter variation and high frequency of transient process, and it requires an accurate control in time. In this paper, the discrete model reference adaptive control system of automatic profiling machine is discussed. Firstly, the model of automatic profiling machine is presented according to the parameters of DC motor. Then the design of the discrete model reference adaptive control is proposed, and the control rules are proven. The results of simulation show that adaptive control system has favorable dynamic performances.

  20. Dynamics and control of quadcopter using linear model predictive control approach

    Science.gov (United States)

    Islam, M.; Okasha, M.; Idres, M. M.

    2017-12-01

    This paper investigates the dynamics and control of a quadcopter using the Model Predictive Control (MPC) approach. The dynamic model is of high fidelity and nonlinear, with six degrees of freedom that include disturbances and model uncertainties. The control approach is developed based on MPC to track different reference trajectories ranging from simple ones such as circular to complex helical trajectories. In this control technique, a linearized model is derived and the receding horizon method is applied to generate the optimal control sequence. Although MPC is computer expensive, it is highly effective to deal with the different types of nonlinearities and constraints such as actuators’ saturation and model uncertainties. The MPC parameters (control and prediction horizons) are selected by trial-and-error approach. Several simulation scenarios are performed to examine and evaluate the performance of the proposed control approach using MATLAB and Simulink environment. Simulation results show that this control approach is highly effective to track a given reference trajectory.

  1. Integrated Heat Air & Moisture Modeling and control

    NARCIS (Netherlands)

    Schijndel, van A.W.M.

    2007-01-01

    The paper presents a recently developed Heat Air & Moisture Laboratory in SimuLink. The simulation laboratory facilitates the integration of the following models: (1) a whole building model; (2) Heating Venting and Air-Conditioning and primary systems; (3) 2D indoor airflow, 3D Heat Air & Moisture

  2. Model Predictive Control of a Wave Energy Converter

    DEFF Research Database (Denmark)

    Andersen, Palle; Pedersen, Tom Søndergård; Nielsen, Kirsten Mølgaard

    2015-01-01

    In this paper reactive control and Model Predictive Control (MPC) for a Wave Energy Converter (WEC) are compared. The analysis is based on a WEC from Wave Star A/S designed as a point absorber. The model predictive controller uses wave models based on the dominating sea states combined with a model...... connecting undisturbed wave sequences to sequences of torque. Losses in the conversion from mechanical to electrical power are taken into account in two ways. Conventional reactive controllers are tuned for each sea state with the assumption that the converter has the same efficiency back and forth. MPC...

  3. A service-oriented data access control model

    Science.gov (United States)

    Meng, Wei; Li, Fengmin; Pan, Juchen; Song, Song; Bian, Jiali

    2017-01-01

    The development of mobile computing, cloud computing and distributed computing meets the growing individual service needs. Facing with complex application system, it's an urgent problem to ensure real-time, dynamic, and fine-grained data access control. By analyzing common data access control models, on the basis of mandatory access control model, the paper proposes a service-oriented access control model. By regarding system services as subject and data of databases as object, the model defines access levels and access identification of subject and object, and ensures system services securely to access databases.

  4. Integrated Intelligent Modeling, Design and Control of Crystal Growth Processes

    National Research Council Canada - National Science Library

    Prasad, V

    2000-01-01

    .... This MURI program took an integrated approach towards modeling, design and control of crystal growth processes and in conjunction with growth and characterization experiments developed much better...

  5. Modeling, Simulation and Position Control of 3DOF Articulated Manipulator

    Directory of Open Access Journals (Sweden)

    Hossein Sadegh Lafmejani

    2014-08-01

    Full Text Available In this paper, the modeling, simulation and control of 3 degrees of freedom articulated robotic manipulator have been studied. First, we extracted kinematics and dynamics equations of the mentioned manipulator by using the Lagrange method. In order to validate the analytical model of the manipulator we compared the model simulated in the simulation environment of Matlab with the model was simulated with the SimMechanics toolbox. A sample path has been designed for analyzing the tracking subject. The system has been linearized with feedback linearization and then a PID controller was applied to track a reference trajectory. Finally, the control results have been compared with a nonlinear PID controller.

  6. A modelling and control structure for product quality control in climate-controlled processing of agro-material

    NARCIS (Netherlands)

    Verdijck, G.J.C.; Straten, van G.

    2002-01-01

    In this paper a modelling and control structure for product quality control is presented for a class of operations that processes agro-material. This class can be characterised as climate-controlled operations, such as storage, transport and drying. The basic model consists of three parts. These are

  7. Model Predictive Vibration Control Efficient Constrained MPC Vibration Control for Lightly Damped Mechanical Structures

    CERN Document Server

    Takács, Gergely

    2012-01-01

    Real-time model predictive controller (MPC) implementation in active vibration control (AVC) is often rendered difficult by fast sampling speeds and extensive actuator-deformation asymmetry. If the control of lightly damped mechanical structures is assumed, the region of attraction containing the set of allowable initial conditions requires a large prediction horizon, making the already computationally demanding on-line process even more complex. Model Predictive Vibration Control provides insight into the predictive control of lightly damped vibrating structures by exploring computationally efficient algorithms which are capable of low frequency vibration control with guaranteed stability and constraint feasibility. In addition to a theoretical primer on active vibration damping and model predictive control, Model Predictive Vibration Control provides a guide through the necessary steps in understanding the founding ideas of predictive control applied in AVC such as: ·         the implementation of ...

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

    Energy Technology Data Exchange (ETDEWEB)

    Hofsten, Kai

    2001-07-01

    This work contributes to the research on control, optimization and simulation of gas transmission systems to support the dispatch personnel at gas control centres for the decision makings in the daily operation of the natural gas transportation systems. Different control and optimization strategies have been studied. The focus is on the operation of long distance natural gas transportation systems. Stationary optimization in conjunction with linear model predictive control using state space models is proposed for supply security, the control of quality parameters and minimization of transportation costs for networks offering transportation services. The result from the stationary optimization together with a reformulation of a simplified fluid flow model formulates a linear dynamic optimization model. This model is used in a finite time control and state constrained linear model predictive controller. The deviation from the control and the state reference determined from the stationary optimization is penalized quadratically. Because of the time varying status of infrastructure, the control space is also generally time varying. When the average load is expected to change considerably, a new stationary optimization is performed, giving a new state and control reference together with a new dynamic model that is used for both optimization and state estimation. Another proposed control strategy is a control and output constrained nonlinear model predictive controller for the operation of gas transmission systems. Here, the objective is also the security of the supply, quality control and minimization of transportation costs. An output vector is defined, which together with a control vector are both penalized quadratically from their respective references in the objective function. The nonlinear model predictive controller can be combined with a stationary optimization. At each sampling instant, a non convex nonlinear programming problem is solved giving a local minimum

  9. Advances in power system modelling, control and stability analysis

    CERN Document Server

    Milano, Federico

    2016-01-01

    Advances in Power System Modelling, Control and Stability Analysis captures the variety of new methodologies and technologies that are changing the way modern electric power systems are modelled, simulated and operated.

  10. Foundation for a Time Interval Access Control Model

    National Research Council Canada - National Science Library

    Afinidad, Francis B; Levin, Timothy E; Irvine, Cynthia E; Nguyen, Thuy D

    2005-01-01

    A new model for representing temporal access control policies is introduced. In this model, temporal authorizations are represented by time attributes associated with both subjects and objects, and a time interval access graph...

  11. Neutron density optimal control of A-1 reactor analoque model

    International Nuclear Information System (INIS)

    Grof, V.

    1975-01-01

    Two applications are described of the optimal control of a reactor analog model. Both cases consider the control of neutron density. Control loops containing the on-line controlled process, the reactor of the first Czechoslovak nuclear power plant A-1, are simulated on an analog computer. Two versions of the optimal control algorithm are derived using modern control theory (Pontryagin's maximum principle, the calculus of variations, and Kalman's estimation theory), the minimum time performance index, and the quadratic performance index. The results of the optimal control analysis are compared with the A-1 reactor conventional control. (author)

  12. Model Predictive Control of Buoy Type Wave Energy Converter

    DEFF Research Database (Denmark)

    Soltani, Mohsen; Sichani, Mahdi Teimouri; Mirzaei, Mahmood

    2014-01-01

    by forcing this condition. In the paper the theoretical framework for this principal is shown. The optimal controller requires information of the sea state for infinite horizon which is not applicable. Model Predictive Controllers (MPC) can have finite horizon which crosses out this requirement....... This approach is then taken into account and an MPC controller is designed for a model WEC and implemented on a numerical example. Further, the power outtake of this controller is compared to the optimal controller as an indicator of the performance of the designed controller....

  13. Model Predictive Control of Buoy Type Wave Energy Converter

    DEFF Research Database (Denmark)

    Soltani, Mohsen N.; Sichani, Mahdi T.; Mirzaei, Mahmood

    2014-01-01

    by forcing this condition. In the paper the theoretical framework for this principal is shown. The optimal controller requires information of the sea state for infinite horizon which is not applicable. Model Predictive Controllers (MPC) can have finite horizon which crosses out this requirement....... This approach is then taken into account and an MPC controller is designed for a model wave energy converter and implemented on a numerical example. Further, the power outtake of this controller is compared to the optimal controller as an indicator of the performance of the designed controller....

  14. Longitudinal Control for Mengshi Autonomous Vehicle via Cloud Model

    Science.gov (United States)

    Gao, H. B.; Zhang, X. Y.; Li, D. Y.; Liu, Y. C.

    2018-03-01

    Dynamic robustness and stability control is a requirement for self-driving of autonomous vehicle. Longitudinal control method of autonomous is a key technique which has drawn the attention of industry and academe. In this paper, we present a longitudinal control algorithm based on cloud model for Mengshi autonomous vehicle to ensure the dynamic stability and tracking performance of Mengshi autonomous vehicle. An experiments is applied to test the implementation of the longitudinal control algorithm. Empirical results show that if the longitudinal control algorithm based Gauss cloud model are applied to calculate the acceleration, and the vehicles drive at different speeds, a stable longitudinal control effect is achieved.

  15. Multi-Model Adaptive Fuzzy Controller for a CSTR Process

    Directory of Open Access Journals (Sweden)

    Shubham Gogoria

    2015-09-01

    Full Text Available Continuous Stirred Tank Reactors are intensively used to control exothermic reactions in chemical industries. It is a very complex multi-variable system with non-linear characteristics. This paper deals with linearization of the mathematical model of a CSTR Process. Multi model adaptive fuzzy controller has been designed to control the reactor concentration and temperature of CSTR process. This method combines the output of multiple Fuzzy controllers, which are operated at various operating points. The proposed solution is a straightforward implementation of Fuzzy controller with gain scheduler to control the linearly inseparable parameters of a highly non-linear process.

  16. 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.

  17. Control Architecture Modeling for Future Power Systems

    DEFF Research Database (Denmark)

    Heussen, Kai

    electricity exchange. However, at the same time, it seems that the overall system design cannot keep up by simply adapting in response to changes, but that also new strategies have to be designed in anticipation. Changes to the electricity markets have been suggested to adapt to the limited predictability...... of wind power, and several new control strategies have been proposed, in particular to enable the control of distributed energy resources, including for example, distributed generation or electric vehicles. Market designs addressing the procurement of balancing resources are highly dependent...... on the operation strategies specifying the resource requirements. How should one decide which control strategy and market configuration is best for a future power system? Most research up to this point has addressed single isolated aspects of this design problem. Those of the ideas that fit with current markets...

  18. A continuous-time control model on production planning network ...

    African Journals Online (AJOL)

    A continuous-time control model on production planning network. DEA Omorogbe, MIU Okunsebor. Abstract. In this paper, we give a slightly detailed review of Graves and Hollywood model on constant inventory tactical planning model for a job shop. The limitations of this model are pointed out and a continuous time ...

  19. New model performance index for engineering design of control systems

    Science.gov (United States)

    1970-01-01

    Performance index includes a model representing linear control-system design specifications. Based on a geometric criterion for approximation of the model by the actual system, the index can be interpreted directly in terms of the desired system response model without actually having the model's time response.

  20. Control of Stirling engine. Simplified, compressible model

    Science.gov (United States)

    Plotnikov, P. I.; Sokołowski, J.; Żochowski, A.

    2016-06-01

    A one-dimensional free boundary problem on a motion of a heavy piston in a tube filled with viscous gas is considered. The system of governing equations and boundary conditions is derived. The obtained system of differential equations can be regarded as a mathematical model of an exterior combustion engine. The existence of a weak solution to this model is proved. The problem of maximization of the total work of the engine is considered.

  1. Control room habitability system review models

    International Nuclear Information System (INIS)

    Gilpin, H.

    1990-12-01

    This report provides a method of calculating control room operator doses from postulated reactor accidents and chemical spills as part of the resolution of TMI Action Plan III.D.3.4. The computer codes contained in this report use source concentrations calculated by either TACT5, FPFP, or EXTRAN, and transport them via user-defined flow rates to the control room envelope. The codes compute doses to six organs from up to 150 radionuclides (or 1 toxic chemical) for time steps as short as one second. Supporting codes written in Clipper assist in data entry and manipulation, and graphically display the results of the FORTRAN calculations. 7 refs., 22 figs

  2. Modelling and Multi-Variable Control of Refrigeration Systems

    DEFF Research Database (Denmark)

    Larsen, Lars Finn Slot; Holm, J. R.

    2003-01-01

    In this paper a dynamic model of a 1:1 refrigeration system is presented. The main modelling effort has been concentrated on a lumped parameter model of a shell and tube condenser. The model has shown good resemblance with experimental data from a test rig, regarding as well the static as the dyn......In this paper a dynamic model of a 1:1 refrigeration system is presented. The main modelling effort has been concentrated on a lumped parameter model of a shell and tube condenser. The model has shown good resemblance with experimental data from a test rig, regarding as well the static...... as the dynamic behavior. Based on this model the effects of the cross couplings has been examined. The influence of the cross couplings on the achievable control performance has been investigated. A MIMO controller is designed and the performance is compared with the control performance achieved by using...

  3. Modeling and Advanced Control for Sustainable Process ...

    Science.gov (United States)

    This book chapter introduces a novel process systems engineering framework that integrates process control with sustainability assessment tools for the simultaneous evaluation and optimization of process operations. The implemented control strategy consists of a biologically-inspired, multi-agent-based method. The sustainability and performance assessment of process operating points is carried out using the U.S. E.P.A.’s GREENSCOPE assessment tool that provides scores for the selected economic, material management, environmental and energy indicators. The indicator results supply information on whether the implementation of the controller is moving the process towards a more sustainable operation. The effectiveness of the proposed framework is illustrated through a case study of a continuous bioethanol fermentation process whose dynamics are characterized by steady-state multiplicity and oscillatory behavior. This book chapter contribution demonstrates the application of novel process control strategies for sustainability by increasing material management, energy efficiency, and pollution prevention, as needed for SHC Sustainable Uses of Wastes and Materials Management.

  4. Model-based control of hopper dredgers

    NARCIS (Netherlands)

    Braaksma, J.

    2008-01-01

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

  5. 76 FR 31456 - Special Conditions: Gulfstream Model GVI Airplane; Electronic Flight Control System: Control...

    Science.gov (United States)

    2011-06-01

    ... electronic flight control system. The applicable airworthiness regulations do not contain adequate or... Design Features The Gulfstream Model GVI airplane has an electronic flight control system and no direct... impending control surface limiting, piloted or auto-flight system control of the airplane might be...

  6. 76 FR 9265 - Special Conditions: Gulfstream Model GVI Airplane; Electronic Flight Control System: Control...

    Science.gov (United States)

    2011-02-17

    ...: Gulfstream Model GVI Airplane; Electronic Flight Control System: Control Surface Position Awareness AGENCY... for transport category airplanes. These design features include an electronic flight control system... Design Features The GVI has an electronic flight control system and no direct coupling from the cockpit...

  7. MODELS OF AIR TRAFFIC CONTROLLERS ERRORS PREVENTION IN TERMINAL CONTROL AREAS UNDER UNCERTAINTY CONDITIONS

    Directory of Open Access Journals (Sweden)

    Volodymyr Kharchenko

    2017-03-01

    Full Text Available Purpose: the aim of this study is to research applied models of air traffic controllers’ errors prevention in terminal control areas (TMA under uncertainty conditions. In this work the theoretical framework descripting safety events and errors of air traffic controllers connected with the operations in TMA is proposed. Methods: optimisation of terminal control area formal description based on the Threat and Error management model and the TMA network model of air traffic flows. Results: the human factors variables associated with safety events in work of air traffic controllers under uncertainty conditions were obtained. The Threat and Error management model application principles to air traffic controller operations and the TMA network model of air traffic flows were proposed. Discussion: Information processing context for preventing air traffic controller errors, examples of threats in work of air traffic controllers, which are relevant for TMA operations under uncertainty conditions.

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

    DEFF Research Database (Denmark)

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

    2017-01-01

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

  9. Modeling of Reaction Processes Controlled by Diffusion

    International Nuclear Information System (INIS)

    Revelli, Jorge

    2003-01-01

    Stochastic modeling is quite powerful in science and technology.The technics derived from this process have been used with great success in laser theory, biological systems and chemical reactions.Besides, they provide a theoretical framework for the analysis of experimental results on the field of particle's diffusion in ordered and disordered materials.In this work we analyze transport processes in one-dimensional fluctuating media, which are media that change their state in time.This fact induces changes in the movements of the particles giving rise to different phenomena and dynamics that will be described and analyzed in this work.We present some random walk models to describe these fluctuating media.These models include state transitions governed by different dynamical processes.We also analyze the trapping problem in a lattice by means of a simple model which predicts a resonance-like phenomenon.Also we study effective diffusion processes over surfaces due to random walks in the bulk.We consider different boundary conditions and transitions movements.We derive expressions that describe diffusion behaviors constrained to bulk restrictions and the dynamic of the particles.Finally it is important to mention that the theoretical results obtained from the models proposed in this work are compared with Monte Carlo simulations.We find, in general, excellent agreements between the theory and the simulations

  10. Dynamical model of birdsong maintenance and control

    Science.gov (United States)

    Abarbanel, Henry D. I.; Talathi, Sachin S.; Mindlin, Gabriel; Rabinovich, Misha; Gibb, Leif

    2004-11-01

    The neuroethology of song learning, production, and maintenance in songbirds presents interesting similarities to human speech. We have developed a biophysical model of the manner in which song could be maintained in adult songbirds. This model may inform us about the human counterpart to these processes. In songbirds, signals generated in nucleus High Vocal center (HVc) follow a direct route along a premotor pathway to the robust nucleus of the archistriatum (RA) as well as an indirect route to RA through the anterior forebrain pathway (AFP): the neurons of RA are innervated from both sources. HVc expresses very sparse bursts of spikes having interspike intervals of about 2ms . The expressions of these bursts arrive at the RA with a time difference ΔT≈50±10ms between the two pathways. The observed combination of AMPA and NMDA receptors at RA projection neurons suggests that long-term potentiation and long-term depression can both be induced by spike timing plasticity through the pairing of the HVc and AFP signals. We present a dynamical model that stabilizes this synaptic plasticity through a feedback from the RA to the AFP using known connections. The stabilization occurs dynamically and is absent when the RA→AFP connection is removed. This requires a dynamical selection of ΔT . The model does this, and ΔT lies within the observed range. Our model represents an illustration of a functional consequence of activity-dependent plasticity directly connected with neuroethological observations. Within the model the parameters of the AFP, and thus the magnitude of ΔT , can also be tuned to an unstable regime. This means that destabilization might be induced by neuromodulation of the AFP.

  11. Modelling and Control of the Wavestar Prototype

    DEFF Research Database (Denmark)

    Hansen, Rico Hjerm; Kramer, Morten M.

    2011-01-01

    Algorithm (WPEA), applied to the full-scale Wavestar Prototype for maximizing energy extraction. The WPEA is optimized based on simulations of the point absorbers in different sea states. Hence, a presentation of a hydrodynamic model of the Wavestar is included in the paper. A simplified Power Take-Off (PTO......) is also added to the model, enabling the optimization of the WPEA to take into account the PTO constraints of PTO bandwidth and force limitations. The predicted results of the optimized WPEA are compared to real measurements from theWavestar Prototype, showing good compliance....

  12. General model and control of an n rotor helicopter

    DEFF Research Database (Denmark)

    Sidea, Adriana-Gabriela; Brogaard, Rune Yding; Andersen, Nils Axel

    2015-01-01

    The purpose of this study was to create a dynamic, nonlinear mathematical model ofa multirotor that would be valid for different numbers of rotors. Furthermore, a set of SingleInput Single Output (SISO) controllers were implemented for attitude control. Both model andcontrollers were tested exper...

  13. A control model for district heating networks with storage

    NARCIS (Netherlands)

    Scholten, Tjeert; De Persis, Claudio; Tesi, Pietro

    2014-01-01

    In [1] pressure control of hydraulic networks is investigated. We extend this work to district heating systems with storage capabilities and derive a model taking the topology of the network into account. The goal for the derived model is that it should allow for control of the storage level and

  14. Multiple Model Adaptive Control Using Dual Youla-Kucera Factorisation

    DEFF Research Database (Denmark)

    Bendtsen, Jan Dimon; Trangbæk, Klaus

    2012-01-01

    We propose a multi-model adaptive control scheme for uncertain linear plants based on the concept of model unfalsification. The approach relies on examining the ability of a pre-computed set of plant-controller candidates and choosing the one that is best able to reproduce observed in- and output...

  15. Model-Based Engineering of Supervisory Controllers using CIF

    NARCIS (Netherlands)

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

    2009-01-01

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

  16. Quality control of geological voxel models using experts' gaze

    NARCIS (Netherlands)

    Maanen, P.P. van; Busschers, F.S.; Brouwer, A.M.; Meulen, M.J. van der; Erp, J.B.F. van

    2015-01-01

    Due to an expected increase in geological voxel model data-flow and user demands, the development of improved quality control for such models is crucial. This study explores the potential of a new type of quality control that improves the detection of errors by just using gaze behavior of 12

  17. Quality Control of Geological Voxel Models using Experts' Gaze

    NARCIS (Netherlands)

    van Maanen, Peter-Paul; Busschers, Freek S.; Brouwer, Anne-Marie; van der Meulendijk, Michiel J.; van Erp, Johannes Bernardus Fransiscus

    Due to an expected increase in geological voxel model data-flow and user demands, the development of improved quality control for such models is crucial. This study explores the potential of a new type of quality control that improves the detection of errors by just using gaze behavior of 12

  18. Model Predictive Control for Offset-Free Reference Tracking

    Czech Academy of Sciences Publication Activity Database

    Belda, Květoslav

    2016-01-01

    Roč. 5, č. 1 (2016), s. 8-13 ISSN 1805-3386 Institutional support: RVO:67985556 Keywords : offset-free reference tracking * predictive control * ARX model * state-space model * multi-input multi-output system * robotic system * mechatronic system Subject RIV: BC - Control Systems Theory http://library.utia.cas.cz/separaty/2016/AS/belda-0458355.pdf

  19. Model predictive control for wind power gradients

    DEFF Research Database (Denmark)

    Hovgaard, Tobias Gybel; Boyd, Stephen; Jørgensen, John Bagterp

    2015-01-01

    We consider the operation of a wind turbine and a connected local battery or other electrical storage device, taking into account varying wind speed, with the goal of maximizing the total energy generated while respecting limits on the time derivative (gradient) of power delivered to the grid. We...... ranges. The system dynamics are quite non-linear, and the constraints and objectives are not convex functions of the control inputs, so the resulting optimal control problem is difficult to solve globally. In this paper, we show that by a novel change of variables, which focuses on power flows, we can...... wind data and modern wind forecasting methods. The simulation results using real wind data demonstrate the ability to reject the disturbances from fast changes in wind speed, ensuring certain power gradients, with an insignificant loss in energy production....

  20. Wind Turbine Control: Robust Model Based Approach

    DEFF Research Database (Denmark)

    Mirzaei, Mahmood

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

  1. Modelling of command and control agility

    CSIR Research Space (South Africa)

    Oosthuizen, R

    2014-06-01

    Full Text Available . Therefore, the stock of information decays over time. Situation Awareness is developed through processing and interpretation of information. This leads to decisions on action to be taken by own forces in reaction to incidents. The understanding..., collective dynamics, and adaptation (Cil & Mala 2010, Beyerchen 1992, Clausewitz 1976). The C2 system support designing courses of action through problem solving within a military context as well as controlling their execution. The purpose of C2, as a force...

  2. Modelling and control of a diffusion/LPCVD furnace

    Science.gov (United States)

    Dewaard, H.; Dekoning, W. L.

    1988-12-01

    Heat transfer inside a cylindrical resistance diffusion/Low Pressure Chemical Vapor Deposition (LPCVD) furnace is studied with the aim of developing an improved temperature controller. A model of the thermal behavior is derived, which covers the important class of furnaces equipped with semitransparent quartz process tubes. The model takes into account the thermal behavior of the thermocouples. Currently used temperature controllers are shown to be highly inefficient for very large scale integration applications. Based on the model an alternative temperature controller of the LQG (linear quadratic Gaussian) type is proposed which features direct wafer temperature control. Some simulation results are given.

  3. Nonlinear Model Predictive Control with Constraint Satisfactions for a Quadcopter

    Science.gov (United States)

    Wang, Ye; Ramirez-Jaime, Andres; Xu, Feng; Puig, Vicenç

    2017-01-01

    This paper presents a nonlinear model predictive control (NMPC) strategy combined with constraint satisfactions for a quadcopter. The full dynamics of the quadcopter describing the attitude and position are nonlinear, which are quite sensitive to changes of inputs and disturbances. By means of constraint satisfactions, partial nonlinearities and modeling errors of the control-oriented model of full dynamics can be transformed into the inequality constraints. Subsequently, the quadcopter can be controlled by an NMPC controller with the updated constraints generated by constraint satisfactions. Finally, the simulation results applied to a quadcopter simulator are provided to show the effectiveness of the proposed strategy.

  4. Robust Output Model Predictive Control of an Unstable Rijke Tube

    Directory of Open Access Journals (Sweden)

    Fabian Jarmolowitz

    2012-01-01

    Full Text Available This work investigates the active control of an unstable Rijke tube using robust output model predictive control (RMPC. As internal model a polytopic linear system with constraints is assumed to account for uncertainties. For guaranteed stability, a linear state feedback controller is designed using linear matrix inequalities and used within a feedback formulation of the model predictive controller. For state estimation a robust gain-scheduled observer is developed. It is shown that the proposed RMPC ensures robust stability under constraints over the considered operating range.

  5. High level model predictive control for plug-and-play process control with stability guaranty

    DEFF Research Database (Denmark)

    Michelsen, Axel Gottlieb; Stoustrup, Jakob

    2010-01-01

    In this paper a method for designing a stabilizing high level model predictive controller for a hierarchical plug- and-play process is presented. This is achieved by abstracting the lower layers of the controller structure as low order models with uncertainty and by using a robust model predictive...... controller for generating the references for these. A simulation example, in which the actuators in a process control system are changed, is reported to show the potential of this approach for plug and play process control....

  6. Modeling to control spores in raw milk

    NARCIS (Netherlands)

    Vissers, M.

    2007-01-01

    A modeling approach was used to identify measures at the farm that reduce transmission of microorganisms to raw milk. Butyric acid bacteria (BAB) and Bacillus cereus were used as case-studies. Minimizing the concentration of BAB spores in raw milk is important to prevent late-blowing of Gouda-type

  7. Modelling and controlling infectious diseases | IDRC - International ...

    International Development Research Centre (IDRC) Digital Library (Canada)

    The research team is exploring the potential of mathematical modelling to ... to China's health system and improvements to its medical research capacity. ... and on the scientific board of the Gates Foundation's Global Health program. ... He has published more than 400 research papers in national and international journals.

  8. Modelling and Internal Fuzzy Model Power Control of a Francis Water Turbine

    Directory of Open Access Journals (Sweden)

    Klemen Nagode

    2014-02-01

    Full Text Available This paper presents dynamic modelling of a Francis turbine with a surge tank and the control of a hydro power plant (HPP. Non-linear and linear models include technical parameters and show high similarity to measurement data. Turbine power control with an internal model control (IMC is proposed, based on a turbine fuzzy model. Considering appropriate control responses in the entire area of turbine power, the model parameters of the process are determined from a fuzzy model, which are further included in the internal model controller. The results are compared to a proportional-integral (PI controller tuned with an integral absolute error (IAE objective function, and show an improved response of internal model control.

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

    CERN Document Server

    Irschik, Hans; Krommer, Michael

    2014-01-01

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

  10. Biomolecular Modeling in a Process Dynamics and Control Course

    Science.gov (United States)

    Gray, Jeffrey J.

    2006-01-01

    I present modifications to the traditional course entitled, "Process dynamics and control," which I renamed "Modeling, dynamics, and control of chemical and biological processes." Additions include the central dogma of biology, pharmacokinetic systems, population balances, control of gene transcription, and large­-scale…

  11. Application of Model-Checking Technology to Controller Synthesis

    DEFF Research Database (Denmark)

    David, Alexandre; Grunnet, Jacob Deleuran; Jessen, Jan Jacob

    2011-01-01

    In this paper we present two frameworks that have been implemented to link traditional model-checking techniques to the domain of control. The techniques are based on solving a timed game and using the resulting solution (a strategy) as a controller. The obtained discrete controller must fit with...

  12. Distributed Model Predictive Control for Smart Energy Systems

    DEFF Research Database (Denmark)

    Halvgaard, Rasmus Fogtmann; Vandenberghe, Lieven; Poulsen, Niels Kjølstad

    2016-01-01

    Integration of a large number of flexible consumers in a smart grid requires a scalable power balancing strategy. We formulate the control problem as an optimization problem to be solved repeatedly by the aggregator in a model predictive control framework. To solve the large-scale control problem...

  13. Introducing Model Predictive Control for Improving Power Plant Portfolio Performance

    DEFF Research Database (Denmark)

    Edlund, Kristian Skjoldborg; Bendtsen, Jan Dimon; Børresen, Simon

    2008-01-01

    This paper introduces a model predictive control (MPC) approach for construction of a controller for balancing the power generation against consumption in a power system. The objective of the controller is to coordinate a portfolio consisting of multiple power plant units in the effort to perform...

  14. Model predictive control for Z-source power converter

    DEFF Research Database (Denmark)

    Mo, W.; Loh, P.C.; Blaabjerg, Frede

    2011-01-01

    This paper presents Model Predictive Control (MPC) of impedance-source (commonly known as Z-source) power converter. Output voltage control and current control for Z-source inverter are analyzed and simulated. With MPC's ability of multi- system variables regulation, load current and voltage...

  15. Model Predictive Control Algorithms for Pen and Pump Insulin Administration

    DEFF Research Database (Denmark)

    Boiroux, Dimitri

    at mealtime, and the case where the insulin sensitivity increases during the night. This thesis consists of a summary report, glucose and insulin proles of the clinical studies and research papers submitted, peer-reviewed and/or published in the period September 2009 - September 2012....... of current closed-loop controllers. In this thesis, we present different control strategies based on Model Predictive Control (MPC) for an artificial pancreas. We use Nonlinear Model Predictive Control (NMPC) in order to determine the optimal insulin and blood glucose profiles. The optimal control problem...

  16. Model Predictive Control for a Small Scale Unmanned Helicopter

    Directory of Open Access Journals (Sweden)

    Jianfu Du

    2008-11-01

    Full Text Available Kinematical and dynamical equations of a small scale unmanned helicoper are presented in the paper. Based on these equations a model predictive control (MPC method is proposed for controlling the helicopter. This novel method allows the direct accounting for the existing time delays which are used to model the dynamics of actuators and aerodynamics of the main rotor. Also the limits of the actuators are taken into the considerations during the controller design. The proposed control algorithm was verified in real flight experiments where good perfomance was shown in postion control mode.

  17. Supervisory Model Predictive Control of the Heat Integrated Distillation Column

    DEFF Research Database (Denmark)

    Meyer, Kristian; Bisgaard, Thomas; Huusom, Jakob Kjøbsted

    2017-01-01

    This paper benchmarks a centralized control system based on model predictive control for the operation of the heat integrated distillation column (HIDiC) against a fully decentralized control system using the most complete column model currently available in the literature. The centralized control...... system outperforms the decentralized system, because it handles the interactions in the HIDiC process better. The integral absolute error (IAE) is reduced by a factor of 2 and a factor of 4 for control of the top and bottoms compositions, respectively....

  18. Generalized internal model robust control for active front steering intervention

    Science.gov (United States)

    Wu, Jian; Zhao, Youqun; Ji, Xuewu; Liu, Yahui; Zhang, Lipeng

    2015-03-01

    Because of the tire nonlinearity and vehicle's parameters' uncertainties, robust control methods based on the worst cases, such as H ∞, µ synthesis, have been widely used in active front steering control, however, in order to guarantee the stability of active front steering system (AFS) controller, the robust control is at the cost of performance so that the robust controller is a little conservative and has low performance for AFS control. In this paper, a generalized internal model robust control (GIMC) that can overcome the contradiction between performance and stability is used in the AFS control. In GIMC, the Youla parameterization is used in an improved way. And GIMC controller includes two sections: a high performance controller designed for the nominal vehicle model and a robust controller compensating the vehicle parameters' uncertainties and some external disturbances. Simulations of double lane change (DLC) maneuver and that of braking on split- µ road are conducted to compare the performance and stability of the GIMC control, the nominal performance PID controller and the H ∞ controller. Simulation results show that the high nominal performance PID controller will be unstable under some extreme situations because of large vehicle's parameters variations, H ∞ controller is conservative so that the performance is a little low, and only the GIMC controller overcomes the contradiction between performance and robustness, which can both ensure the stability of the AFS controller and guarantee the high performance of the AFS controller. Therefore, the GIMC method proposed for AFS can overcome some disadvantages of control methods used by current AFS system, that is, can solve the instability of PID or LQP control methods and the low performance of the standard H ∞ controller.

  19. A Queueing Model for Supervisory Control of Unmanned Autonomous Vehicles

    Science.gov (United States)

    2013-09-01

    Autonomous Vehicles Joseph DiVita, PhD Robert L. Morris Maria Olinda Rodas SSC Pacific Approved...298 (Rev. 8/98) Prescribed by ANSI Std. Z39.18 09–2013 Final A Queueing Model for Supervisory Control of Unmanned Autonomous Vehicles Joseph...Mission Area: Command and Control, Queueing Model; Supervisory Control; Unmanned Autonomous Vehicles M. O. Rodas U U U U 38 (619)

  20. The GMOC Model : Supporting Development of Systems for Human Control

    OpenAIRE

    Tschirner, Simon

    2015-01-01

    Train traffic control is a complex task in a dynamic environment. Different actors have to cooperate to meet strong requirements regarding safety, punctuality, capacity utilization, energy consumption, and more. The GMOC model has been developed and utilized in a number of studies in several different areas. This thesis describes GMOC and uses train traffic control as the application area for evaluating its utility. The GMOC model has its origin in control theory and relates to concepts of dy...

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

    Science.gov (United States)

    Chen, Wei; Li, Xin

    2016-11-01

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

  2. Integrated Control Modeling for Propulsion Systems Using NPSS

    Science.gov (United States)

    Parker, Khary I.; Felder, James L.; Lavelle, Thomas M.; Withrow, Colleen A.; Yu, Albert Y.; Lehmann, William V. A.

    2004-01-01

    The Numerical Propulsion System Simulation (NPSS), an advanced engineering simulation environment used to design and analyze aircraft engines, has been enhanced by integrating control development tools into it. One of these tools is a generic controller interface that allows NPSS to communicate with control development software environments such as MATLAB and EASY5. The other tool is a linear model generator (LMG) that gives NPSS the ability to generate linear, time-invariant state-space models. Integrating these tools into NPSS enables it to be used for control system development. This paper will discuss the development and integration of these tools into NPSS. In addition, it will show a comparison of transient model results of a generic, dual-spool, military-type engine model that has been implemented in NPSS and Simulink. It will also show the linear model generator s ability to approximate the dynamics of a nonlinear NPSS engine model.

  3. Multilevel flow modelling of process plant for diagnosis and control

    International Nuclear Information System (INIS)

    Lind, M.

    1982-08-01

    The paper describes the multilevel flow modelling methodology which can be used to construct functional models of energy and material processing systems. The models describe mass and energy flow topology on different levels of abstraction and represent the hierarchical functional structure of complex systems. A model of a nuclear power plant (PWR) is presented in the paper for illustration. Due to the consistency of the method, multilevel flow models provide specifications of plant goals and functions and may be used as a basis for design of computer-based support systems for the plant operator. Plant control requirements can be derived from the models and due to independence of the actual controller implementation the method may be used as basic for design of control strategies and for the allocation of control tasks to the computer and the plant operator. (author)

  4. Multilevel Flow Modelling of Process Plant for Diagnosis and Control

    DEFF Research Database (Denmark)

    Lind, Morten

    1982-01-01

    The paper describes the multilevel flow modelling methodology which can be used to construct functional models of energy and material processing systems. The models describe mass and energy flow topology on different levels of abstraction and represent the hierarchical functional structure...... of complex systems. A model of a nuclear power plant (PWR) is presented in the paper for illustration. Due to the consistency of the method, multilevel flow models provide specifications of plant goals and functions and may be used as a basis for design of computer-based support systems for the plant...... operator. Plant control requirements can be derived from the models and due to independence of the actual controller implementation the method may be used as a basis for design of control strategies and for the allocation of control tasks to the computer and the plant operator....

  5. Robot modelling; Control and applications with software

    Energy Technology Data Exchange (ETDEWEB)

    Ranky, P G; Ho, C Y

    1985-01-01

    This book provides a ''picture'' of robotics covering both the theoretical aspect of modeling as well as the practical and design aspects of: robot programming; robot tooling and automated hand changing; implementation planning; testing; and software design for robot systems. The authors present an introduction to robotics with a systems approach. They describe not only the tasks relating to a single robot (or arm) but also systems of robots working together on a product or several products.

  6. Modeling and control of precision actuators

    CERN Document Server

    Kiong, Tan Kok

    2013-01-01

    IntroductionGrowing Interest in Precise ActuatorsTypes of Precise ActuatorsApplications of Precise ActuatorsNonlinear Dynamics and ModelingHysteresisCreepFrictionForce RipplesIdentification and Compensation of Preisach Hysteresis in Piezoelectric ActuatorsSVD-Based Identification and Compensation of Preisach HysteresisHigh-Bandwidth Identification and Compensation of Hysteretic Dynamics in Piezoelectric ActuatorsConcluding RemarksIdentification and Compensation of Frict

  7. Linear control theory for gene network modeling.

    Science.gov (United States)

    Shin, Yong-Jun; Bleris, Leonidas

    2010-09-16

    Systems biology is an interdisciplinary field that aims at understanding complex interactions in cells. Here we demonstrate that linear control theory can provide valuable insight and practical tools for the characterization of complex biological networks. We provide the foundation for such analyses through the study of several case studies including cascade and parallel forms, feedback and feedforward loops. We reproduce experimental results and provide rational analysis of the observed behavior. We demonstrate that methods such as the transfer function (frequency domain) and linear state-space (time domain) can be used to predict reliably the properties and transient behavior of complex network topologies and point to specific design strategies for synthetic networks.

  8. Control of spatial discretisation in coastal oil spill modelling

    OpenAIRE

    Li, Yang

    2007-01-01

    Spatial discretisation plays an important role in many numerical environmental models. This paper studies the control of spatial discretisation in coastal oil spill modelling with a view to assure the quality of modelling outputs for given spatial data inputs. Spatial data analysis techniques are effective for investigating and improving the spatial discretisation in different phases of the modelling. Proposed methods are implemented and tested with experimental models. A new “Automatic Searc...

  9. Modeling Smart Energy Systems for Model Predictive Control

    DEFF Research Database (Denmark)

    Halvgaard, Rasmus; Poulsen, Niels Kjølstad; Madsen, Henrik

    2012-01-01

    as it is produced requires a very exible and controllable power consumption. Examples of controllable electric loads are heat pumps in buildings and Electric Vehicles (EVs) that are expected to play a large role in the future danish energy system. These units in a smart energy system can potentially oer exibility...... on a time scale ranging from seconds to several days by moving power consumption, exploiting thermal inertia or battery storage capacity, respectively. Using advanced control algorithms these systems are able to reduce their own electricity costs by planning ahead and moving consumption to periods...... future price should also be available in order for the individual units to plan ahead in the most feasible way. This is necessary since Economic MPCs do not respond to the absolute cost of electricity, but to variations of the price over the prediction horizon. Economic MPC is ideal for price responsive...

  10. Modeling and Control of Multivariable Process Using Intelligent Techniques

    Directory of Open Access Journals (Sweden)

    Subathra Balasubramanian

    2010-10-01

    Full Text Available For nonlinear dynamic systems, the first principles based modeling and control is difficult to implement. In this study, a fuzzy controller and recurrent fuzzy controller are developed for MIMO process. Fuzzy logic controller is a model free controller designed based on the knowledge about the process. In fuzzy controller there are two types of rule-based fuzzy models are available: one the linguistic (Mamdani model and the other is Takagi–Sugeno model. Of these two, Takagi-Sugeno model (TS has attracted most attention. The fuzzy controller application is limited to static processes due to their feedforward structure. But, most of the real-time processes are dynamic and they require the history of input/output data. In order to store the past values a memory unit is needed, which is introduced by the recurrent structure. The proposed recurrent fuzzy structure is used to develop a controller for the two tank heating process. Both controllers are designed and implemented in a real time environment and their performance is compared.

  11. Fuzzy Adaptive Model Following Speed Control for Vector Controlled Permanent Magnet Synchronous Motor

    Directory of Open Access Journals (Sweden)

    Baghdad BELABES

    2008-12-01

    Full Text Available In this paper a hybrid controller combining a linear model following controller (LMFC and fuzzy logic control (FLC for speed vector controlled permanent magnet synchronous motor (PMSM is described on this study. The FLC is introduced at the adaptive mechanism level. First, an LMFC system is designed to allow the plant states to be controlled to follow the states produced by a reference model. In the nominal conditions, the model following is perfect and the adaptive mechanism based on the fuzzy logic is idle. Secondly, when parameter variations or external disturbances occur, an augmented signal will be generated by FLC mechanism to preserve the desired model following control performance. The effectiveness and robustness of the proposed controller is demonstrated by some simulation results.

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

    International Nuclear Information System (INIS)

    Mohd Sabri Minhat; Izhar Abu Hussin; Ridzuan Abdul Mutalib

    2014-01-01

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

  13. Modeling Pediatric Brain Trauma: Piglet Model of Controlled Cortical Impact.

    Science.gov (United States)

    Pareja, Jennifer C Munoz; Keeley, Kristen; Duhaime, Ann-Christine; Dodge, Carter P

    2016-01-01

    The brain has different responses to traumatic injury as a function of its developmental stage. As a model of injury to the immature brain, the piglet shares numerous similarities in regards to morphology and neurodevelopmental sequence compared to humans. This chapter describes a piglet scaled focal contusion model of traumatic brain injury that accounts for the changes in mass and morphology of the brain as it matures, facilitating the study of age-dependent differences in response to a comparable mechanical trauma.

  14. An optimal control model of crop thinning in viticulture

    OpenAIRE

    Schamel Guenter H.; Schubert Stefan F.

    2016-01-01

    We develop an economic model of cluster thinning in viticulture to control for grape quantity harvested and grape quality, applying a simple optimal control model with the aim to raise grape quality and related economic profits. The model maximizes vineyard owner profits and allows to discuss two relevant scenarios using a phase diagram analysis: (1) when the initial grape quantity is sufficiently small, thinning grapes will not be optimal and (2) when the initial grape quantity is high enoug...

  15. Uncertainty Quantification in Control Problems for Flocking Models

    Directory of Open Access Journals (Sweden)

    Giacomo Albi

    2015-01-01

    Full Text Available The optimal control of flocking models with random inputs is investigated from a numerical point of view. The effect of uncertainty in the interaction parameters is studied for a Cucker-Smale type model using a generalized polynomial chaos (gPC approach. Numerical evidence of threshold effects in the alignment dynamic due to the random parameters is given. The use of a selective model predictive control permits steering of the system towards the desired state even in unstable regimes.

  16. Code Development for Control Design Applications: Phase I: Structural Modeling

    International Nuclear Information System (INIS)

    Bir, G. S.; Robinson, M.

    1998-01-01

    The design of integrated controls for a complex system like a wind turbine relies on a system model in an explicit format, e.g., state-space format. Current wind turbine codes focus on turbine simulation and not on system characterization, which is desired for controls design as well as applications like operating turbine model analysis, optimal design, and aeroelastic stability analysis. This paper reviews structural modeling that comprises three major steps: formation of component equations, assembly into system equations, and linearization

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

    OpenAIRE

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

    2017-01-01

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

  18. Model predictive control for spacecraft rendezvous in elliptical orbit

    Science.gov (United States)

    Li, Peng; Zhu, Zheng H.

    2018-05-01

    This paper studies the control of spacecraft rendezvous with attitude stable or spinning targets in an elliptical orbit. The linearized Tschauner-Hempel equation is used to describe the motion of spacecraft and the problem is formulated by model predictive control. The control objective is to maximize control accuracy and smoothness simultaneously to avoid unexpected change or overshoot of trajectory for safe rendezvous. It is achieved by minimizing the weighted summations of control errors and increments. The effects of two sets of horizons (control and predictive horizons) in the model predictive control are examined in terms of fuel consumption, rendezvous time and computational effort. The numerical results show the proposed control strategy is effective.

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

    Science.gov (United States)

    DeCastro, Jonathan A.

    2006-01-01

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

  20. Modeling and control simulation of the China CLEAR-IB

    International Nuclear Information System (INIS)

    Yan, Shoujun; Wan, Jiashuang; Wang, Pengfei; Fang, Huawei; Sun, Changyi; Zhao, Fuyu

    2014-01-01

    Highlights: • A model for the reactor for CLEAR-IB was developed. • A PI controller was designed to control the power. • A control strategy was adopted to control the water enthalpy of air cooler. • Dynamic simulation of the whole system was performed. - Abstract: To investigate the dynamic and control characteristics of the plant, a model for the main components of the reactor and the most relevant interactions among them is developed. The system comprises of the primary system with lead bismuth eutectic (LBE) as the coolant, the secondary circuit with steam water mixture as the coolant and the associated air cooling system for an effective rejection of thermal power to the environment as a final heat sink. A Proportional-Integral (PI) controller is designed to keep the power following the set value as quickly as possible. To keep outlet coolant of air coolers and inlet coolant of HXs being saturated water, a control strategy based on a simultaneous feed-forward and feedback scheme has been adopted. Based on the developed model and control strategy, dynamic simulation of the whole system in the cases of step changes of external source and load is performed. The simulation results show that the proposed model is accurate enough to describe the dynamic behaviors of the plant in spite of its simplicity. It has also been demonstrated that the developed controllers for the CLEAR-IB can provide superior reactor control capabilities due to the efficiency of the control strategy adopted

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

    DEFF Research Database (Denmark)

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

    2012-01-01

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

  2. Two problems from the theory of semiotic control models. I. Representations of semiotic models

    Energy Technology Data Exchange (ETDEWEB)

    Osipov, G S

    1981-11-01

    Two problems from the theory of semiotic control models are being stated, in particular the representation of models and the semantic analysis of themtheory of semiotic control models are being stated, in particular the representation of models and the semantic analysis of them. Algebraic representation of semiotic models, covering of representations, their reduction and equivalence are discussed. The interrelations between functional and structural characteristics of semiotic models are investigated. 20 references.

  3. Nonconvex Model Predictive Control for Commercial Refrigeration

    DEFF Research Database (Denmark)

    Hovgaard, Tobias Gybel; Larsen, Lars F.S.; Jørgensen, John Bagterp

    2013-01-01

    function, however, is nonconvex due to the temperature dependence of thermodynamic efficiency. To handle this nonconvexity we propose a sequential convex optimization method, which typically converges in fewer than 5 or so iterations. We employ a fast convex quadratic programming solver to carry out...... the iterations, which is more than fast enough to run in real-time. We demonstrate our method on a realistic model, with a full year simulation and 15 minute time periods, using historical electricity prices and weather data, as well as random variations in thermal load. These simulations show substantial cost...... capacity associated with large penetration of intermittent renewable energy sources in a future smart grid....

  4. Version control of pathway models using XML patches.

    Science.gov (United States)

    Saffrey, Peter; Orton, Richard

    2009-03-17

    Computational modelling has become an important tool in understanding biological systems such as signalling pathways. With an increase in size complexity of models comes a need for techniques to manage model versions and their relationship to one another. Model version control for pathway models shares some of the features of software version control but has a number of differences that warrant a specific solution. We present a model version control method, along with a prototype implementation, based on XML patches. We show its application to the EGF/RAS/RAF pathway. Our method allows quick and convenient storage of a wide range of model variations and enables a thorough explanation of these variations. Trying to produce these results without such methods results in slow and cumbersome development that is prone to frustration and human error.

  5. A STRUCTURAL MODEL OF AN EXCAVATOR WORKFLOW CONTROL SYSTEM

    Directory of Open Access Journals (Sweden)

    A. Gurko

    2016-12-01

    Full Text Available Earthwork improving is connected with excavators automation. In this paper, on the basis of the analysis of problems that a hydraulic excavator control system have to solve, the hierarchical structure of a control system have been proposed. The decomposition of the control process had been executed that allowed to develop the structural model which reflects the characteristics of a multilevel space-distributed control system of an excavator workflow.

  6. Linear control theory for gene network modeling.

    Directory of Open Access Journals (Sweden)

    Yong-Jun Shin

    Full Text Available Systems biology is an interdisciplinary field that aims at understanding complex interactions in cells. Here we demonstrate that linear control theory can provide valuable insight and practical tools for the characterization of complex biological networks. We provide the foundation for such analyses through the study of several case studies including cascade and parallel forms, feedback and feedforward loops. We reproduce experimental results and provide rational analysis of the observed behavior. We demonstrate that methods such as the transfer function (frequency domain and linear state-space (time domain can be used to predict reliably the properties and transient behavior of complex network topologies and point to specific design strategies for synthetic networks.

  7. Modeling and Control of Primary Parallel Isolated Boost Converter

    DEFF Research Database (Denmark)

    Mira Albert, Maria del Carmen; Hernandez Botella, Juan Carlos; Sen, Gökhan

    2012-01-01

    In this paper state space modeling and closed loop controlled operation have been presented for primary parallel isolated boost converter (PPIBC) topology as a battery charging unit. Parasitic resistances have been included to have an accurate dynamic model. The accuracy of the model has been...

  8. Modeling and nonlinear heading control for sailing yachts

    DEFF Research Database (Denmark)

    Xiao, Lin; Jouffroy, Jerome

    2014-01-01

    This paper presents a study on the development and testing of a model-based heading controller for a sailing yacht. Using Fossen’s compact notation for marine vehicles, we first describe a nonlinear four-degree-of-freedom (DOF) dynamic model for a sailing yacht, including roll. Our model also...

  9. Modeling and nonlinear heading control for sailing yachts

    DEFF Research Database (Denmark)

    Xiao, Lin; Jouffroy, Jerome

    2011-01-01

    This paper presents a study on the development and testing of a model-based heading controller for a sailing yacht. Using Fossen's compact notation for marine vehicles, we first describe a nonlinear 4-DOF dynamic model for a sailing yacht, including roll. Starting from this model, we then design...

  10. Modelling of control system architecture for next-generation accelerators

    International Nuclear Information System (INIS)

    Liu, Shi-Yao; Kurokawa, Shin-ichi

    1990-01-01

    Functional, hardware and software system architectures define the fundamental structure of control systems. Modelling is a protocol of system architecture used in system design. This paper reviews various modellings adopted in past ten years and suggests a new modelling for next generation accelerators. (author)

  11. Modelling and controller design for a UV disinfection plant

    NARCIS (Netherlands)

    van Mourik, S.; Geurts, Bernardus J.; Zwart, Heiko J.

    2007-01-01

    A mathematical model describing fluid flow and concentration dynamics of microorganisms inside a UV photoreactor is developed. Using physical arguments and techniques from system theory, we approximate this model by a first order linear one. For this reduced model, we design a controller. The

  12. Integration of Design and Control Through Model Analysis

    DEFF Research Database (Denmark)

    Russel, Boris Mariboe; Henriksen, Jens Peter; Jørgensen, Sten Bay

    2000-01-01

    of the phenomena models representing the process model identify the relationships between the important process and design variables, which help to understand, define and address some of the issues related to integration of design and control issues. The model analysis is highlighted through examples involving...... processes with mass and/or energy recycle. (C) 2000 Elsevier Science Ltd. All rights reserved....

  13. Task Delegation Based Access Control Models for Workflow Systems

    Science.gov (United States)

    Gaaloul, Khaled; Charoy, François

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

  14. A model of a control-room crew

    International Nuclear Information System (INIS)

    Spurgin, A.J.; Beveridge, R.L.

    1986-01-01

    This paper discusses the development of a model of a control-room crew based on observations of crews and concepts developed by cognitive psychologists. The model can help define, among other things, the requirements for SPDS or other operator aids. The paper discusses the relationship of the shift supervisor, the control board operators, the control and instrumentation systems and the written procedures in the control of the plant during normal and abnormal plant transients. These relationships cover the communications between crew members, use of the control equipment by the board operators, use of information, such as the SPDS, by the shift supervisor and integration of crew actions by the use of the procedures. Also discussed are the potential causes of erroneous actions by the crew in accident situations. The model is at this time purely qualitative, but it can be considered to be the basis for the development of a mathematical model

  15. Fuzzy model predictive control algorithm applied in nuclear power plant

    International Nuclear Information System (INIS)

    Zuheir, Ahmad

    2006-01-01

    The aim of this paper is to design a predictive controller based on a fuzzy model. The Takagi-Sugeno fuzzy model with an Adaptive B-splines neuro-fuzzy implementation is used and incorporated as a predictor in a predictive controller. An optimization approach with a simplified gradient technique is used to calculate predictions of the future control actions. In this approach, adaptation of the fuzzy model using dynamic process information is carried out to build the predictive controller. The easy description of the fuzzy model and the easy computation of the gradient sector during the optimization procedure are the main advantages of the computation algorithm. The algorithm is applied to the control of a U-tube steam generation unit (UTSG) used for electricity generation. (author)

  16. Modeling and simulation of Indus-2 RF feedback control system

    International Nuclear Information System (INIS)

    Sharma, D.; Bagduwal, P.S.; Tiwari, N.; Lad, M.; Hannurkar, P.R.

    2012-01-01

    Indus-2 synchrotron radiation source has four RF stations along with their feedback control systems. For higher beam energy and current operation amplitude and phase feedback control systems of Indus-2 are being upgraded. To understand the behaviour of amplitude and phase control loop under different operating conditions, modelling and simulation of RF feedback control system is done. RF cavity baseband I/Q model has been created due to its close correspondence with actual implementation and better computational efficiency which makes the simulation faster. Correspondence between cavity baseband and RF model is confirmed by comparing their simulation results. Low Level RF (LLRF) feedback control system simulation is done using the same cavity baseband I/Q model. Error signals are intentionally generated and response of the closed loop system is observed. Simulation will help us in optimizing parameters of upgraded LLRF system for higher beam energy and current operation. (author)

  17. ANS main control complex three-dimensional computer model development

    International Nuclear Information System (INIS)

    Cleaves, J.E.; Fletcher, W.M.

    1993-01-01

    A three-dimensional (3-D) computer model of the Advanced Neutron Source (ANS) main control complex is being developed. The main control complex includes the main control room, the technical support center, the materials irradiation control room, computer equipment rooms, communications equipment rooms, cable-spreading rooms, and some support offices and breakroom facilities. The model will be used to provide facility designers and operations personnel with capabilities for fit-up/interference analysis, visual ''walk-throughs'' for optimizing maintain-ability, and human factors and operability analyses. It will be used to determine performance design characteristics, to generate construction drawings, and to integrate control room layout, equipment mounting, grounding equipment, electrical cabling, and utility services into ANS building designs. This paper describes the development of the initial phase of the 3-D computer model for the ANS main control complex and plans for its development and use

  18. Dynamic coordinated control laws in multiple agent models

    International Nuclear Information System (INIS)

    Morgan, David S.; Schwartz, Ira B.

    2005-01-01

    We present an active control scheme of a kinetic model of swarming. It has been shown previously that the global control scheme for the model, presented in [Systems Control Lett. 52 (2004) 25], gives rise to spontaneous collective organization of agents into a unified coherent swarm, via steering controls and utilizing long-range attractive and short-range repulsive interactions. We extend these results by presenting control laws whereby a single swarm is broken into independently functioning subswarm clusters. The transition between one coordinated swarm and multiple clustered subswarms is managed simply with a homotopy parameter. Additionally, we present as an alternate formulation, a local control law for the same model, which implements dynamic barrier avoidance behavior, and in which swarm coherence emerges spontaneously

  19. Control Oriented Modeling of a De-oiling Hydrocyclone

    DEFF Research Database (Denmark)

    Løhndorf, Petar Durdevic; Pedersen, Simon; Bram, Mads Valentin

    2015-01-01

    -oiling hydrocyclone based on experimental data that can support systematic analysis and control design of hydrocyclone systems. The most widely used control solution of a hydrocyclone is a Pressure Drop Ratio (PDR) control strategy, which is often empirically designed and experimentally tuned in a case-by-case manner......Deoiling hydrocyclones are an important part of the downstream water treatment in offshore oil & gas production, they ensure a low discharge of oil and thus a higher yield of produced oil. This work investigates the possibility of developing a simple control-oriented model of a de....... There is a lack of a systematic and deep-insight analysis of the capability, stability and limitations of these control solutions, as there are few control-oriented models available for de-oiling hydrocyclone systems. This paper proposes a method of retrieving a set of simple 1st-order transfer function models...

  20. Desiccant wheel thermal performance modeling for indoor humidity optimal control

    International Nuclear Information System (INIS)

    Wang, Nan; Zhang, Jiangfeng; Xia, Xiaohua

    2013-01-01

    Highlights: • An optimal humidity control model is formulated to control the indoor humidity. • MPC strategy is used to implement the optimal operation solution. • Practical applications of the MPC strategy is illustrated by the case study. - Abstract: Thermal comfort is an important concern in the energy efficiency improvement of commercial buildings. Thermal comfort research focuses mostly on temperature control, but humidity control is an important aspect to maintain indoor comfort too. In this paper, an optimal humidity control model (OHCM) is presented. Model predictive control (MPC) strategy is applied to implement the optimal operation of the desiccant wheel during working hours of a commercial building. The OHCM is revised to apply the MPC strategy. A case is studied to illustrate the practical applications of the MPC strategy

  1. Selection of References in Wind Turbine Model Predictive Control Design

    DEFF Research Database (Denmark)

    Odgaard, Peter Fogh; Hovgaard, Tobias

    2015-01-01

    a model predictive controller for a wind turbine. One of the important aspects for a tracking control problem is how to setup the optimal reference tracking problem, as it might be relevant to track, e.g., the three concurrent references: optimal pitch angle, optimal rotational speed, and optimal power......Lowering the cost of energy is one of the major focus areas in the wind turbine industry. Recent research has indicated that wind turbine controllers based on model predictive control methods can be useful in obtaining this objective. A number of design considerations have to be made when designing....... The importance if the individual references differ depending in particular on the wind speed. In this paper we investigate the performance of a reference tracking model predictive controller with two different setups of the used optimal reference signals. The controllers are evaluated using an industrial high...

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

    International Nuclear Information System (INIS)

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

    1990-01-01

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

  3. Controlled Nonlinear Stochastic Delay Equations: Part I: Modeling and Approximations

    International Nuclear Information System (INIS)

    Kushner, Harold J.

    2012-01-01

    This two-part paper deals with “foundational” issues that have not been previously considered in the modeling and numerical optimization of nonlinear stochastic delay systems. There are new classes of models, such as those with nonlinear functions of several controls (such as products), each with is own delay, controlled random Poisson measure driving terms, admissions control with delayed retrials, and others. There are two basic and interconnected themes for these models. The first, dealt with in this part, concerns the definition of admissible control. The classical definition of an admissible control as a nonanticipative relaxed control is inadequate for these models and needs to be extended. This is needed for the convergence proofs of numerical approximations for optimal controls as well as to have a well-defined model. It is shown that the new classes of admissible controls do not enlarge the range of the value functions, is closed (together with the associated paths) under weak convergence, and is approximatable by ordinary controls. The second theme, dealt with in Part II, concerns transportation equation representations, and their role in the development of numerical algorithms with much reduced memory and computational requirements.

  4. Power electronic converters modeling and control with case studies

    CERN Document Server

    Bacha, Seddik; Bratcu, Antoneta Iuliana

    2014-01-01

    Modern power electronic converters are involved in a very broad spectrum of applications: switched-mode power supplies, electrical-machine-motion-control, active power filters, distributed power generation, flexible AC transmission systems, renewable energy conversion systems and vehicular technology, among them. Power Electronics Converters Modeling and Control teaches the reader how to analyze and model the behavior of converters and so to improve their design and control. Dealing with a set of confirmed algorithms specifically developed for use with power converters, this text is in two parts: models and control methods. The first is a detailed exposition of the most usual power converter models: ·        switched and averaged models; ·        small/large-signal models; and ·        time/frequency models. The second focuses on three groups of control methods: ·        linear control approaches normally associated with power converters; ·        resonant controllers b...

  5. Robust Control for the Segway with Unknown Control Coefficient and Model Uncertainties

    Directory of Open Access Journals (Sweden)

    Byung Woo Kim

    2016-06-01

    Full Text Available The Segway, which is a popular vehicle nowadays, is an uncertain nonlinear system and has an unknown time-varying control coefficient. Thus, we should consider the unknown time-varying control coefficient and model uncertainties to design the controller. Motivated by this observation, we propose a robust control for the Segway with unknown control coefficient and model uncertainties. To deal with the time-varying unknown control coefficient, we employ the Nussbaum gain technique. We introduce an auxiliary variable to solve the underactuated problem. Due to the prescribed performance control technique, the proposed controller does not require the adaptive technique, neural network, and fuzzy logic to compensate the uncertainties. Therefore, it can be simple. From the Lyapunov stability theory, we prove that all signals in the closed-loop system are bounded. Finally, we provide the simulation results to demonstrate the effectiveness of the proposed control scheme.

  6. Control oriented system analysis and feedback control of a numerical sawtooth instability model

    NARCIS (Netherlands)

    Witvoet, G.; Westerhof, E.; Steinbuch, M.; Baar, de M.R.; Doelman, N.J.; Prater, R.

    2010-01-01

    A combined Porcelli-Kadomtsev numerical sawtooth instability model is analyzed using control oriented identification techniques. The resulting discrete time linear models describe the system’s behavior from crash to crash and is used in the design of a simple discrete time feedback controller, which

  7. Modeling, Prediction, and Control of Heating Temperature for Tube Billet

    Directory of Open Access Journals (Sweden)

    Yachun Mao

    2015-01-01

    Full Text Available Annular furnaces have multivariate, nonlinear, large time lag, and cross coupling characteristics. The prediction and control of the exit temperature of a tube billet are important but difficult. We establish a prediction model for the final temperature of a tube billet through OS-ELM-DRPLS method. We address the complex production characteristics, integrate the advantages of PLS and ELM algorithms in establishing linear and nonlinear models, and consider model update and data lag. Based on the proposed model, we design a prediction control algorithm for tube billet temperature. The algorithm is validated using the practical production data of Baosteel Co., Ltd. Results show that the model achieves the precision required in industrial applications. The temperature of the tube billet can be controlled within the required temperature range through compensation control method.

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

    DEFF Research Database (Denmark)

    Zemtsov, Nikita; Hlava, Jaroslav; Frantsuzova, Galina

    2017-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Maruthai Suresh

    2009-10-01

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

  10. 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.

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

    NARCIS (Netherlands)

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

    2017-01-01

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

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

    NARCIS (Netherlands)

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

    2017-01-01

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

  13. Direct Model Reference Adaptive Control for a Magnetic Bearing

    Energy Technology Data Exchange (ETDEWEB)

    Durling, Mike [Rensselaer Polytechnic Inst., Troy, NY (United States)

    1999-11-01

    A Direct Model Reference Adaptive Controller (DMRAC) is applied to a magnetic bearing test stand. The bearing of interest is the MBC 500 Magnetic Bearing System manufactured by Magnetic Moments, LLC. The bearing model is presented in state space form and the system transfer function is measured directly using a closed-loop swept sine technique. Next, the bearing models are used to design a phase-lead controller, notch filter and then a DMRAC. The controllers are tuned in simulations and finally are implemented using a combination of MATLAB, SIMULINK and dSPACE. The results show a successful implementation of a DMRAC on the magnetic bearing hardware.

  14. Fuzzy Universal Model Approximator for Distributed Solar Collector Field Control

    KAUST Repository

    Elmetennani, Shahrazed

    2014-07-01

    This paper deals with the control of concentrating parabolic solar collectors by forcing the outlet oil temperature to track a set reference. A fuzzy universal approximate model is introduced in order to accurately reproduce the behavior of the system dynamics. The proposed model is a low order state space representation derived from the partial differential equation describing the oil temperature evolution using fuzzy transform theory. The resulting set of ordinary differential equations simplifies the system analysis and the control law design and is suitable for real time control implementation. Simulation results show good performance of the proposed model.

  15. Dynamic modeling, simulation and control of energy generation

    CERN Document Server

    Vepa, Ranjan

    2013-01-01

    This book addresses the core issues involved in the dynamic modeling, simulation and control of a selection of energy systems such as gas turbines, wind turbines, fuel cells and batteries. The principles of modeling and control could be applied to other non-convention methods of energy generation such as solar energy and wave energy.A central feature of Dynamic Modeling, Simulation and Control of Energy Generation is that it brings together diverse topics in thermodynamics, fluid mechanics, heat transfer, electro-chemistry, electrical networks and electrical machines and focuses on their appli

  16. Integration of Design and Control through Model Analysis

    DEFF Research Database (Denmark)

    Russel, Boris Mariboe; Henriksen, Jens Peter; Jørgensen, Sten Bay

    2002-01-01

    A systematic computer aided analysis of the process model is proposed as a pre-solution step for integration of design and control problems. The process model equations are classified in terms of balance equations, constitutive equations and conditional equations. Analysis of the phenomena models...... (structure selection) issues for the integrated problems are considered. (C) 2002 Elsevier Science Ltd. All rights reserved....... representing the constitutive equations identify the relationships between the important process and design variables, which help to understand, define and address some of the issues related to integration of design and control. Furthermore, the analysis is able to identify a set of process (control) variables...

  17. An analysis of the control hierarchy modelling of the CMS detector control system

    NARCIS (Netherlands)

    Hwong, Y.L.; Groote, J.F.; Willemse, T.A.C.

    2009-01-01

    The high level Detector Control System (DCS) of the CMS experiment is modelled using Finite State Machines (FSM), which cover the control application behaviours of all the sub-detectors and support services. The Joint Controls Project (JCOP) at CERN has chosen the SMI++ framework for this purpose.

  18. A LIDAR-assisted model predictive controller added on a traditional wind turbine controller

    DEFF Research Database (Denmark)

    Mirzaei, Mahmood; Hansen, Morten Hartvig

    2016-01-01

    control and opens the market of retrofitting existing wind turbines with the new technology. In this paper, we suggest a model predictive controller (MPC) that is added to the basic gain scheduled PI controller of a WT to enhance the performance of the closed loop system using LIDAR measurements...

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

    Directory of Open Access Journals (Sweden)

    Christer Dalen

    2017-10-01

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

  20. Modeling and Control of a teletruck using electronic load sensing

    DEFF Research Database (Denmark)

    Hansen, Rico Hjerm; Iversen, Asger Malte; Jensen, Mads Schmidt

    2010-01-01

    system is most commonly controlled using a hydro-mechanical control scheme called Hydraulic Load Sensing (HLS). However, with the demands for increased efficiency and controllability the HLS solutions are reaching their limits. Motivated by availability of electronic controllable fluid power...... components and the potential of increased dynamic performance and efficiency, this paper investigates how HLS can be replaced with electronic control, i.e. Electronic Load Sensing (ELS). The investigation is performed by taking a specific application, a teletruck, and replace the HLS control with ELS. To aid...... the controller design for the ELS system, a complete model of the teletruck’s articulated arm and fluid power system is developed. To show the feasibility, a preliminary control structure for the ELS system is developed. The controller is tested on the machine, validating that features such as pump pressure...

  1. Wind power electric systems modeling, simulation and control

    CERN Document Server

    Rekioua, Djamila

    2014-01-01

    The book helps readers understand key concepts in standalone and grid connected wind energy systems and features analysis into the modeling and optimization of commonly used configurations through the implementation of different control strategies.Utilizing several electrical machinery control approaches, such as vector control and direct torque control 'Wind Power Electric Systems' equips readers with the means to understand, assess and develop their own wind energy systems and to evaluate the performance of such systems.Mathematical models are provided for each system and a corresponding MAT

  2. Model-based expert systems for linac computer controls

    International Nuclear Information System (INIS)

    Lee, M.J.

    1988-09-01

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

  3. Pilot-model analysis and simulation study of effect of control task desired control response

    Science.gov (United States)

    Adams, J. J.; Gera, J.; Jaudon, J. B.

    1978-01-01

    A pilot model analysis was performed that relates pilot control compensation, pilot aircraft system response, and aircraft response characteristics for longitudinal control. The results show that a higher aircraft short period frequency is required to achieve superior pilot aircraft system response in an altitude control task than is required in an attitude control task. These results were confirmed by a simulation study of target tracking. It was concluded that the pilot model analysis provides a theoretical basis for determining the effect of control task on pilot opinions.

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

    Directory of Open Access Journals (Sweden)

    Guoliang Zhao

    2013-01-01

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

  5. Semiotic aspects of control and modeling relations in complex systems

    Energy Technology Data Exchange (ETDEWEB)

    Joslyn, C.

    1996-08-01

    A conceptual analysis of the semiotic nature of control is provided with the goal of elucidating its nature in complex systems. Control is identified as a canonical form of semiotic relation of a system to its environment. As a form of constraint between a system and its environment, its necessary and sufficient conditions are established, and the stabilities resulting from control are distinguished from other forms of stability. These result from the presence of semantic coding relations, and thus the class of control systems is hypothesized to be equivalent to that of semiotic systems. Control systems are contrasted with models, which, while they have the same measurement functions as control systems, do not necessarily require semantic relations because of the lack of the requirement of an interpreter. A hybrid construction of models in control systems is detailed. Towards the goal of considering the nature of control in complex systems, the possible relations among collections of control systems are considered. Powers arguments on conflict among control systems and the possible nature of control in social systems are reviewed, and reconsidered based on our observations about hierarchical control. Finally, we discuss the necessary semantic functions which must be present in complex systems for control in this sense to be present at all.

  6. ARTIFICIAL NEURAL NETWORK AND FUZZY LOGIC CONTROLLER FOR GTAW MODELING AND CONTROL

    Institute of Scientific and Technical Information of China (English)

    2002-01-01

    An artificial neural network(ANN) and a self-adjusting fuzzy logic controller(FLC) for modeling and control of gas tungsten arc welding(GTAW) process are presented. The discussion is mainly focused on the modeling and control of the weld pool depth with ANN and the intelligent control for weld seam tracking with FLC. The proposed neural network can produce highly complex nonlinear multi-variable model of the GTAW process that offers the accurate prediction of welding penetration depth. A self-adjusting fuzzy controller used for seam tracking adjusts the control parameters on-line automatically according to the tracking errors so that the torch position can be controlled accurately.

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

    CERN Document Server

    Grancharova, Alexandra; Pereira, Fernando

    2015-01-01

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

  8. The Robust Control Mixer Method for Reconfigurable Control Design By Using Model Matching Strategy

    DEFF Research Database (Denmark)

    Yang, Z.; Blanke, Mogens; Verhagen, M.

    2001-01-01

    This paper proposes a robust reconfigurable control synthesis method based on the combination of the control mixer method and robust H1 con- trol techniques through the model-matching strategy. The control mixer modules are extended from the conventional matrix-form into the LTI sys- tem form....... By regarding the nominal control system as the desired model, an augmented control system is constructed through the model-matching formulation, such that the current robust control techniques can be usedto synthesize these dynamical modules. One extension of this method with respect to the performance...... recovery besides the functionality recovery is also discussed under this framework. Comparing with the conventional control mixer method, the proposed method considers the recon gured system's stability, performance and robustness simultaneously. Finally, the proposed method is illustrated by a case study...

  9. Robust Model Predictive Control of a Wind Turbine

    DEFF Research Database (Denmark)

    Mirzaei, Mahmood; Poulsen, Niels Kjølstad; Niemann, Hans Henrik

    2012-01-01

    In this work the problem of robust model predictive control (robust MPC) of a wind turbine in the full load region is considered. A minimax robust MPC approach is used to tackle the problem. Nonlinear dynamics of the wind turbine are derived by combining blade element momentum (BEM) theory...... of the uncertain system is employed and a norm-bounded uncertainty model is used to formulate a minimax model predictive control. The resulting optimization problem is simplified by semidefinite relaxation and the controller obtained is applied on a full complexity, high fidelity wind turbine model. Finally...... and first principle modeling of the turbine flexible structure. Thereafter the nonlinear model is linearized using Taylor series expansion around system operating points. Operating points are determined by effective wind speed and an extended Kalman filter (EKF) is employed to estimate this. In addition...

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

    Science.gov (United States)

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

    2009-12-01

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

  11. The Quadrotor Dynamic Modeling and Indoor Target Tracking Control Method

    Directory of Open Access Journals (Sweden)

    Dewei Zhang

    2014-01-01

    Full Text Available A reliable nonlinear dynamic model of the quadrotor is presented. The nonlinear dynamic model includes actuator dynamic and aerodynamic effect. Since the rotors run near a constant hovering speed, the dynamic model is simplified at hovering operating point. Based on the simplified nonlinear dynamic model, the PID controllers with feedback linearization and feedforward control are proposed using the backstepping method. These controllers are used to control both the attitude and position of the quadrotor. A fully custom quadrotor is developed to verify the correctness of the dynamic model and control algorithms. The attitude of the quadrotor is measured by inertia measurement unit (IMU. The position of the quadrotor in a GPS-denied environment, especially indoor environment, is estimated from the downward camera and ultrasonic sensor measurements. The validity and effectiveness of the proposed dynamic model and control algorithms are demonstrated by experimental results. It is shown that the vehicle achieves robust vision-based hovering and moving target tracking control.

  12. Adaptive control using neural networks and approximate models.

    Science.gov (United States)

    Narendra, K S; Mukhopadhyay, S

    1997-01-01

    The NARMA model is an exact representation of the input-output behavior of finite-dimensional nonlinear discrete-time dynamical systems in a neighborhood of the equilibrium state. However, it is not convenient for purposes of adaptive control using neural networks due to its nonlinear dependence on the control input. Hence, quite often, approximate methods are used for realizing the neural controllers to overcome computational complexity. In this paper, we introduce two classes of models which are approximations to the NARMA model, and which are linear in the control input. The latter fact substantially simplifies both the theoretical analysis as well as the practical implementation of the controller. Extensive simulation studies have shown that the neural controllers designed using the proposed approximate models perform very well, and in many cases even better than an approximate controller designed using the exact NARMA model. In view of their mathematical tractability as well as their success in simulation studies, a case is made in this paper that such approximate input-output models warrant a detailed study in their own right.

  13. Modeling and control for closed environment plant production systems

    Science.gov (United States)

    Fleisher, David H.; Ting, K. C.; Janes, H. W. (Principal Investigator)

    2002-01-01

    A computer program was developed to study multiple crop production and control in controlled environment plant production systems. The program simulates crop growth and development under nominal and off-nominal environments. Time-series crop models for wheat (Triticum aestivum), soybean (Glycine max), and white potato (Solanum tuberosum) are integrated with a model-based predictive controller. The controller evaluates and compensates for effects of environmental disturbances on crop production scheduling. The crop models consist of a set of nonlinear polynomial equations, six for each crop, developed using multivariate polynomial regression (MPR). Simulated data from DSSAT crop models, previously modified for crop production in controlled environments with hydroponics under elevated atmospheric carbon dioxide concentration, were used for the MPR fitting. The model-based predictive controller adjusts light intensity, air temperature, and carbon dioxide concentration set points in response to environmental perturbations. Control signals are determined from minimization of a cost function, which is based on the weighted control effort and squared-error between the system response and desired reference signal.

  14. Application of H∞ control theory to power control of a nonlinear reactor model

    International Nuclear Information System (INIS)

    Suzuki, Katsuo; Shimazaki, Junya; Shinohara, Yoshikuni

    1993-01-01

    The H∞ control theory is applied to the compensator design of a nonlinear nuclear reactor model, and the results are compared with standard linear quadratic Gaussian (LQG) control. The reactor model is assumed to be provided with a control rod drive system having the compensation of rod position feedback. The nonlinearity of the reactor model exerts a great influence on the stability of the control system, and hence, it is desirable for a power control system of a nuclear reactor to achieve robust stability and to improve the sensitivity of the feedback control system. A computer simulation based on a power control system synthesized by LQG control was performed revealing that the control system has some stationary offset and less stability. Therefore, here, attention is given to the development of a methodology for robust control that can withstand exogenous disturbances and nonlinearity in view of system parameter changes. The developed methodology adopts H∞ control theory in the feedback system and shows interesting features of robustness. The results of the computer simulation indicate that the feedback control system constructed by the developed H∞ compensator possesses sufficient robustness of control on the stability and disturbance attenuation, which are essential for the safe operation of a nuclear reactor

  15. Case Studies in Modelling, Control in Food Processes.

    Science.gov (United States)

    Glassey, J; Barone, A; Montague, G A; Sabou, V

    This chapter discusses the importance of modelling and control in increasing food process efficiency and ensuring product quality. Various approaches to both modelling and control in food processing are set in the context of the specific challenges in this industrial sector and latest developments in each area are discussed. Three industrial case studies are used to demonstrate the benefits of advanced measurement, modelling and control in food processes. The first case study illustrates the use of knowledge elicitation from expert operators in the process for the manufacture of potato chips (French fries) and the consequent improvements in process control to increase the consistency of the resulting product. The second case study highlights the economic benefits of tighter control of an important process parameter, moisture content, in potato crisp (chips) manufacture. The final case study describes the use of NIR spectroscopy in ensuring effective mixing of dry multicomponent mixtures and pastes. Practical implementation tips and infrastructure requirements are also discussed.

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

    Directory of Open Access Journals (Sweden)

    Zhiyong Yang

    2008-11-01

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

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

    Directory of Open Access Journals (Sweden)

    Zhiyong Yang

    2008-03-01

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

  18. REALIGNED MODEL PREDICTIVE CONTROL OF A PROPYLENE DISTILLATION COLUMN

    Directory of Open Access Journals (Sweden)

    A. I. Hinojosa

    Full Text Available Abstract In the process industry, advanced controllers usually aim at an economic objective, which usually requires closed-loop stability and constraints satisfaction. In this paper, the application of a MPC in the optimization structure of an industrial Propylene/Propane (PP splitter is tested with a controller based on a state space model, which is suitable for heavily disturbed environments. The simulation platform is based on the integration of the commercial dynamic simulator Dynsim® and the rigorous steady-state optimizer ROMeo® with the real-time facilities of Matlab. The predictive controller is the Infinite Horizon Model Predictive Control (IHMPC, based on a state-space model that that does not require the use of a state observer because the non-minimum state is built with the past inputs and outputs. The controller considers the existence of zone control of the outputs and optimizing targets for the inputs. We verify that the controller is efficient to control the propylene distillation system in a disturbed scenario when compared with a conventional controller based on a state observer. The simulation results show a good performance in terms of stability of the controller and rejection of large disturbances in the composition of the feed of the propylene distillation column.

  19. Toward Balance Recovery With Leg Prostheses Using Neuromuscular Model Control

    Science.gov (United States)

    Geyer, Hartmut

    2016-01-01

    Objective Lower limb amputees are at high risk of falling as current prosthetic legs provide only limited functionality for recovering balance after unexpected disturbances. For instance, the most established control method used on powered leg prostheses tracks local joint impedance functions without taking the global function of the leg in balance recovery into account. Here we explore an alternative control policy for powered transfemoral prostheses that considers the global leg function and is based on a neuromuscular model of human locomotion. Methods We adapt this model to describe and simulate an amputee walking with a powered prosthesis using the proposed control, and evaluate the gait robustness when confronted with rough ground and swing leg disturbances. We then implement and partially evaluate the resulting controller on a leg prosthesis prototype worn by a non-amputee user. Results In simulation, the proposed prosthesis control leads to gaits that are more robust than those obtained by the impedance control method. The initial hardware experiments with the prosthesis prototype show that the proposed control reproduces normal walking patterns qualitatively and effectively responds to disturbances in early and late swing. However, the response to mid-swing disturbances neither replicates human responses nor averts falls. Conclusions The neuromuscular model control is a promising alternative to existing prosthesis controls, although further research will need to improve on the initial implementation and determine how well these results transfer to amputee gait. Significance This work provides a potential avenue for future development of control policies that help improve amputee balance recovery. PMID:26315935

  20. Finite-Control-Set Model Predictive Control (FCS-MPC) for Islanded Hybrid Microgrids

    OpenAIRE

    Yi, Zhehan; Babqi, Abdulrahman J.; Wang, Yishen; Shi, Di; Etemadi, Amir H.; Wang, Zhiwei; Huang, Bibin

    2018-01-01

    Microgrids consisting of multiple distributed energy resources (DERs) provide a promising solution to integrate renewable energies, e.g., solar photovoltaic (PV) systems. Hybrid AC/DC microgrids leverage the merits of both AC and DC power systems. In this paper, a control strategy for islanded multi-bus hybrid microgrids is proposed based on the Finite-Control-Set Model Predictive Control (FCS-MPC) technologies. The control loops are expedited by predicting the future states and determining t...

  1. Active vibration control using state space LQG and internal model control methods

    DEFF Research Database (Denmark)

    Mørkholt, Jakob; Elliott, S.J.

    1998-01-01

    Two ways of designing discrete time robust H2-controllers for feedback broadband active vibration control are compared through computer simulations. The methods are based on different models of disturbance and plant transfer functions, but yield controllers with identical properties. Two simple...... ways of introducing robustness into the H2-design are compared, and finally an efficient way of designing a practical IIR-controller is proposed....

  2. Modelling primate control of grasping for robotics applications

    CSIR Research Space (South Africa)

    Kleinhans, A

    2014-09-01

    Full Text Available The neural circuits that control grasping and perform related visual processing have been studied extensively in Macaque monkeys. We are developing a computational model of this system, in order to better understand its function, and to explore...

  3. Simulation modelling for new gas turbine fuel controller creation.

    Science.gov (United States)

    Vendland, L. E.; Pribylov, V. G.; Borisov, Yu A.; Arzamastsev, M. A.; Kosoy, A. A.

    2017-11-01

    State of the art gas turbine fuel flow control systems are based on throttle principle. Major disadvantage of such systems is that they require high pressure fuel intake. Different approach to fuel flow control is to use regulating compressor. And for this approach because of controller and gas turbine interaction a specific regulating compressor is required. Difficulties emerge as early as the requirement definition stage. To define requirements for new object, his properties must be known. Simulation modelling helps to overcome these difficulties. At the requirement definition stage the most simplified mathematical model is used. Mathematical models will get more complex and detailed as we advance in planned work. If future adjusting of regulating compressor physical model to work with virtual gas turbine and physical control system is planned.

  4. Modelling and control of a nonlinear magnetostrictive actuator system

    Science.gov (United States)

    Ramli, M. H. M.; Majeed, A. P. P. Abdul; Anuar, M. A. M.; Mohamed, Z.

    2018-04-01

    This paper explores the implementation of a feedforward control method to a nonlinear control system, in particular, Magnetostrictive Actuators (MA) that has excellent properties of energy conversion between the mechanical and magnetic form through magnetostriction effects which could be used in actuating and sensing application. MA is known to exhibit hysteresis behaviour and it is rate dependent (the level of hysteresis depends closely on the rate of input excitation frequency). This is, nonetheless, an undesirable behaviour and has to be eliminated in realising high precision application. The MA is modelled by a phenomenological modelling approach via Prandtl-Ishlinskii (P-I) operator to characterise the hysteresis nonlinearities. A feedforward control strategy is designed and implemented to linearize and eliminate the hysteresis by model inversion. The results show that the P-I operator has the capability to model the hysteretic nonlinearity of MA with an acceptable accuracy. Furthermore, the proposed control scheme has demonstrated to be effective in providing superior trajectory tracking.

  5. Cognitive Models for Learning to Control Dynamic Systems

    National Research Council Canada - National Science Library

    Eberhart, Russ; Hu, Xiaohui; Chen, Yaobin

    2008-01-01

    Report developed under STTR contract for topic "Cognitive models for learning to control dynamic systems" demonstrated a swarm intelligence learning algorithm and its application in unmanned aerial vehicle (UAV) mission planning...

  6. Urban Runoff: Model Ordinances for Erosion and Sediment Control

    Science.gov (United States)

    The model ordinance in this section borrows language from the erosion and sediment control ordinance features that might help prevent erosion and sedimentation and protect natural resources more fully.

  7. Modeling Reaction Control System Effects on Mars Odyssey

    National Research Council Canada - National Science Library

    Hanna, Jill

    2002-01-01

    ...) simulations to determine rotational motion of the spacecraft. The main objective of this study was to assess the reaction control system models and their effects on the atmospheric flight of Odyssey...

  8. Rotor-Flying Manipulator: Modeling, Analysis, and Control

    Directory of Open Access Journals (Sweden)

    Bin Yang

    2014-01-01

    Full Text Available Equipping multijoint manipulators on a mobile robot is a typical redesign scheme to make the latter be able to actively influence the surroundings and has been extensively used for many ground robots, underwater robots, and space robotic systems. However, the rotor-flying robot (RFR is difficult to be made such redesign. This is mainly because the motion of the manipulator will bring heavy coupling between itself and the RFR system, which makes the system model highly complicated and the controller design difficult. Thus, in this paper, the modeling, analysis, and control of the combined system, called rotor-flying multijoint manipulator (RF-MJM, are conducted. Firstly, the detailed dynamics model is constructed and analyzed. Subsequently, a full-state feedback linear quadratic regulator (LQR controller is designed through obtaining linearized model near steady state. Finally, simulations are conducted and the results are analyzed to show the basic control performance.

  9. Model-free adaptive control of advanced power plants

    Science.gov (United States)

    Cheng, George Shu-Xing; Mulkey, Steven L.; Wang, Qiang

    2015-08-18

    A novel 3-Input-3-Output (3.times.3) Model-Free Adaptive (MFA) controller with a set of artificial neural networks as part of the controller is introduced. A 3.times.3 MFA control system using the inventive 3.times.3 MFA controller is described to control key process variables including Power, Steam Throttle Pressure, and Steam Temperature of boiler-turbine-generator (BTG) units in conventional and advanced power plants. Those advanced power plants may comprise Once-Through Supercritical (OTSC) Boilers, Circulating Fluidized-Bed (CFB) Boilers, and Once-Through Supercritical Circulating Fluidized-Bed (OTSC CFB) Boilers.

  10. Simulation model of an active stall wind turbine controller

    Energy Technology Data Exchange (ETDEWEB)

    Jauch, C.; Hansen, A.D.; Soerensen, P. [Risoe National Lab., Wind Energy Dept., Rosilde (Denmark); Blaabjerg, F. [Aalborg Univ., Inst. of Energy Technology (Denmark)

    2004-07-01

    This paper describes an active stall wind turbine controller. The objective is to develop a general model of an active stall controller in order to simulate the operation of grid connected active stall wind turbines. The active stall turbine concept and its control strategies are presented and evaluated on the basis of simulations. The presented controller is described for continuous operation under all wind speeds from start-up wind speed to shut doven wind speed. Due to its parametric implementation it is general i.e. it can represent different active stall wind turbine controllers and can be implemented in different simulation tools. (au)

  11. 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...

  12. Computational Models Used to Assess US Tobacco Control Policies.

    Science.gov (United States)

    Feirman, Shari P; Glasser, Allison M; Rose, Shyanika; Niaura, Ray; Abrams, David B; Teplitskaya, Lyubov; Villanti, Andrea C

    2017-11-01

    Simulation models can be used to evaluate existing and potential tobacco control interventions, including policies. The purpose of this systematic review was to synthesize evidence from computational models used to project population-level effects of tobacco control interventions. We provide recommendations to strengthen simulation models that evaluate tobacco control interventions. Studies were eligible for review if they employed a computational model to predict the expected effects of a non-clinical US-based tobacco control intervention. We searched five electronic databases on July 1, 2013 with no date restrictions and synthesized studies qualitatively. Six primary non-clinical intervention types were examined across the 40 studies: taxation, youth prevention, smoke-free policies, mass media campaigns, marketing/advertising restrictions, and product regulation. Simulation models demonstrated the independent and combined effects of these interventions on decreasing projected future smoking prevalence. Taxation effects were the most robust, as studies examining other interventions exhibited substantial heterogeneity with regard to the outcomes and specific policies examined across models. Models should project the impact of interventions on overall tobacco use, including nicotine delivery product use, to estimate preventable health and cost-saving outcomes. Model validation, transparency, more sophisticated models, and modeling policy interactions are also needed to inform policymakers to make decisions that will minimize harm and maximize health. In this systematic review, evidence from multiple studies demonstrated the independent effect of taxation on decreasing future smoking prevalence, and models for other tobacco control interventions showed that these strategies are expected to decrease smoking, benefit population health, and are reasonable to implement from a cost perspective. Our recommendations aim to help policymakers and researchers minimize harm and

  13. Mathematical models for therapeutic approaches to control HIV disease transmission

    CERN Document Server

    Roy, Priti Kumar

    2015-01-01

    The book discusses different therapeutic approaches based on different mathematical models to control the HIV/AIDS disease transmission. It uses clinical data, collected from different cited sources, to formulate the deterministic as well as stochastic mathematical models of HIV/AIDS. It provides complementary approaches, from deterministic and stochastic points of view, to optimal control strategy with perfect drug adherence and also tries to seek viewpoints of the same issue from different angles with various mathematical models to computer simulations. The book presents essential methods and techniques for students who are interested in designing epidemiological models on HIV/AIDS. It also guides research scientists, working in the periphery of mathematical modeling, and helps them to explore a hypothetical method by examining its consequences in the form of a mathematical modelling and making some scientific predictions. The model equations, mathematical analysis and several numerical simulations that are...

  14. Control-oriented modeling and adaptive backstepping control for a nonminimum phase hypersonic vehicle.

    Science.gov (United States)

    Ye, Linqi; Zong, Qun; Tian, Bailing; Zhang, Xiuyun; Wang, Fang

    2017-09-01

    In this paper, the nonminimum phase problem of a flexible hypersonic vehicle is investigated. The main challenge of nonminimum phase is the prevention of dynamic inversion methods to nonlinear control design. To solve this problem, we make research on the relationship between nonminimum phase and backstepping control, finding that a stable nonlinear controller can be obtained by changing the control loop on the basis of backstepping control. By extending the control loop to cover the internal dynamics in it, the internal states are directly controlled by the inputs and simultaneously serve as virtual control for the external states, making it possible to guarantee output tracking as well as internal stability. Then, based on the extended control loop, a simplified control-oriented model is developed to enable the applicability of adaptive backstepping method. It simplifies the design process and releases some limitations caused by direct use of the no simplified control-oriented model. Next, under proper assumptions, asymptotic stability is proved for constant commands, while bounded stability is proved for varying commands. The proposed method is compared with approximate backstepping control and dynamic surface control and is shown to have superior tracking accuracy as well as robustness from the simulation results. This paper may also provide a beneficial guidance for control design of other complex systems. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

  15. Tensegrity Models and Shape Control of Vehicle Formations

    OpenAIRE

    Nabet, Benjamin; Leonard, Naomi Ehrich

    2009-01-01

    Using dynamic models of tensegrity structures, we derive provable, distributed control laws for stabilizing and changing the shape of a formation of vehicles in the plane. Tensegrity models define the desired, controlled, multi-vehicle system dynamics, where each node in the tensegrity structure maps to a vehicle and each interconnecting strut or cable in the structure maps to a virtual interconnection between vehicles. Our method provides a smooth map from any desired planar formation shape ...

  16. Rate-control algorithms testing by using video source model

    DEFF Research Database (Denmark)

    Belyaev, Evgeny; Turlikov, Andrey; Ukhanova, Anna

    2008-01-01

    In this paper the method of rate control algorithms testing by the use of video source model is suggested. The proposed method allows to significantly improve algorithms testing over the big test set.......In this paper the method of rate control algorithms testing by the use of video source model is suggested. The proposed method allows to significantly improve algorithms testing over the big test set....

  17. Economic Model Predictive Control for Spray Drying Plants

    DEFF Research Database (Denmark)

    Petersen, Lars Norbert

    and a complexity reduced control model is used for state estimation and prediction in the controllers. These models facilitate development and comparison of control strategies. We develop two MPC strategies; a linear tracking MPC with a Real-Time Optimization layer (MPC with RTO) and an Economic Nonlinear MPC (E...... horizon, out of which only the first input is applied to the dryer. This procedure is repeated at each sample instant and is solved numerically in real-time. The MPC with RTO tracks a target that optimizes the cost of operation at steady-state. The E-MPC optimizes the cost of operation directly by having...... this objective directly in the controller. The need for the RTO layer is then eliminated. We demonstrate the application of the proposed MPC with RTO to control an industrial GEA MSDTM-1250 spray dryer, which produces approximately 7500 kg/hr of enriched milk powder. Compared to the conventional PI controller...

  18. Optimal Model-Based Control in HVAC Systems

    DEFF Research Database (Denmark)

    Komareji, Mohammad; Stoustrup, Jakob; Rasmussen, Henrik

    2008-01-01

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

  19. Control architecture of power systems: Modeling of purpose and function

    DEFF Research Database (Denmark)

    Heussen, Kai; Saleem, Arshad; Lind, Morten

    2009-01-01

    Many new technologies with novel control capabilities have been developed in the context of “smart grid” research. However, often it is not clear how these capabilities should best be integrated in the overall system operation. New operation paradigms change the traditional control architecture...... of power systems and it is necessary to identify requirements and functions. How does new control architecture fit with the old architecture? How can power system functions be specified independent of technology? What is the purpose of control in power systems? In this paper, a method suitable...... for semantically consistent modeling of control architecture is presented. The method, called Multilevel Flow Modeling (MFM), is applied to the case of system balancing. It was found that MFM is capable of capturing implicit control knowledge, which is otherwise difficult to formalize. The method has possible...

  20. Study of Model Predictive Control for Path-Following Autonomous Ground Vehicle Control under Crosswind Effect

    Directory of Open Access Journals (Sweden)

    Fitri Yakub

    2016-01-01

    Full Text Available We present a comparative study of model predictive control approaches of two-wheel steering, four-wheel steering, and a combination of two-wheel steering with direct yaw moment control manoeuvres for path-following control in autonomous car vehicle dynamics systems. Single-track mode, based on a linearized vehicle and tire model, is used. Based on a given trajectory, we drove the vehicle at low and high forward speeds and on low and high road friction surfaces for a double-lane change scenario in order to follow the desired trajectory as close as possible while rejecting the effects of wind gusts. We compared the controller based on both simple and complex bicycle models without and with the roll vehicle dynamics for different types of model predictive control manoeuvres. The simulation result showed that the model predictive control gave a better performance in terms of robustness for both forward speeds and road surface variation in autonomous path-following control. It also demonstrated that model predictive control is useful to maintain vehicle stability along the desired path and has an ability to eliminate the crosswind effect.

  1. Model predictive control of wind energy conversion systems

    CERN Document Server

    Yaramasu, Venkata Narasimha R

    2017-01-01

    The authors provide a comprehensive analysis on the model predictive control of power converters employed in a wide variety of variable-speed wind energy conversion systems (WECS). The contents of this book includes an overview of wind energy system configurations, power converters for variable-speed WECS, digital control techniques, MPC, modeling of power converters and wind generators for MPC design. Other topics include the mapping of continuous-time models to discrete-time models by various exact, approximate, and quasi-exact discretization methods, modeling and control of wind turbine grid-side two-level and multilevel voltage source converters. The authors also focus on the MPC of several power converter configurations for full variable-speed permanent magnet synchronous generator based WECS, squirrel-cage induction generator based WECS, and semi-variable-speed doubly fed induction generator based WECS.

  2. Type-2 fuzzy logic uncertain systems’ modeling and control

    CERN Document Server

    Antão, Rómulo

    2017-01-01

    This book focuses on a particular domain of Type-2 Fuzzy Logic, related to process modeling and control applications. It deepens readers’understanding of Type-2 Fuzzy Logic with regard to the following three topics: using simpler methods to train a Type-2 Takagi-Sugeno Fuzzy Model; using the principles of Type-2 Fuzzy Logic to reduce the influence of modeling uncertainties on a locally linear n-step ahead predictor; and developing model-based control algorithms according to the Generalized Predictive Control principles using Type-2 Fuzzy Sets. Throughout the book, theory is always complemented with practical applications and readers are invited to take their learning process one step farther and implement their own applications using the algorithms’ source codes (provided). As such, the book offers avaluable referenceguide for allengineers and researchers in the field ofcomputer science who are interested in intelligent systems, rule-based systems and modeling uncertainty.

  3. Absorption Cycle Heat Pump Model for Control Design

    DEFF Research Database (Denmark)

    Vinther, Kasper; Just Nielsen, Rene; Nielsen, Kirsten Mølgaard

    2015-01-01

    Heat pumps have recently received increasing interest due to green energy initiatives and increasing energy prices. In this paper, a nonlinear dynamic model of a single-effect LiBr-water absorption cycle heat pump is derived for simulation and control design purposes. The model is based on an act......Heat pumps have recently received increasing interest due to green energy initiatives and increasing energy prices. In this paper, a nonlinear dynamic model of a single-effect LiBr-water absorption cycle heat pump is derived for simulation and control design purposes. The model is based...... to operational data and different scenarios are simulated to investigate the operational stability of the heat pump. Finally, this paper provides suggestions and examples of derivation of lower order linear models for control design. © Copyright IEEE - All rights reserved....

  4. Robust nonlinear control of nuclear reactors under model uncertainty

    International Nuclear Information System (INIS)

    Park, Moon Ghu

    1993-02-01

    A nonlinear model-based control method is developed for the robust control of a nuclear reactor. The nonlinear plant model is used to design a unique control law which covers a wide operating range. The robustness is a crucial factor for the fully automatic control of reactor power due to time-varying, uncertain parameters, and state estimation error, or unmodeled dynamics. A variable structure control (VSC) method is introduced which consists of an adaptive performance specification (fime control) after the tracking error reaches the narrow boundary-layer by a time-optimal control (coarse control). Variable structure control is a powerful method for nonlinear system controller design which has inherent robustness to parameter variations or external disturbances using the known uncertainty bounds, and it requires very low computational efforts. In spite of its desirable properties, conventional VSC presents several important drawbacks that limit its practical applicability. One of the most undesirable phenomena is chattering, which implies extremely high control activity and may excite high-frequency unmodeled dynamics. This problem is due to the neglected actuator time-delay or sampling effects. The problem was partially remedied by replacing chattering control by a smooth control inter-polation in a boundary layer neighnboring a time-varying sliding surface. But, for the nuclear reactor systems which has very fast dynamic response, the sampling effect may destroy the narrow boundary layer when a large uncertainty bound is used. Due to the very short neutron life time, large uncertainty bound leads to the high gain in feedback control. To resolve this problem, a derivative feedback is introduced that gives excellent performance by reducing the uncertainty bound. The stability of tracking error dynamics is guaranteed by the second method of Lyapunov using the two-level uncertainty bounds that are obtained from the knowledge of uncertainty bound and the estimated

  5. Linearized models for a new magnetic control in MAST

    Energy Technology Data Exchange (ETDEWEB)

    Artaserse, G., E-mail: giovanni.artaserse@enea.it [Associazione Euratom-ENEA sulla Fusione, Via Enrico Fermi 45, I-00044 Frascati (RM) (Italy); Maviglia, F.; Albanese, R. [Associazione Euratom-ENEA-CREATE sulla Fusione, Via Claudio 21, I-80125 Napoli (Italy); McArdle, G.J.; Pangione, L. [EURATOM/CCFE Fusion Association, Culham Science Centre, Abingdon, Oxon, OX14 3DB (United Kingdom)

    2013-10-15

    Highlights: ► We applied linearized models for a new magnetic control on MAST tokamak. ► A suite of procedures, conceived to be machine independent, have been used. ► We carried out model-based simulations, taking into account eddy currents effects. ► Comparison with the EFIT flux maps and the experimental magnetic signals are shown. ► A current driven model for the dynamic simulations of the experimental data have been performed. -- Abstract: The aim of this work is to provide reliable linearized models for the design and assessment of a new magnetic control system for MAST (Mega Ampère Spherical Tokamak) using rtEFIT, which can easily be exported to MAST Upgrade. Linearized models for magnetic control have been obtained using the 2D axisymmetric finite element code CREATE L. MAST linearized models include equivalent 2D axisymmetric schematization of poloidal field (PF) coils, vacuum vessel, and other conducting structures. A plasmaless and a double null configuration have been chosen as benchmark cases for the comparison with experimental data and EFIT reconstructions. Good agreement has been found with the EFIT flux map and the experimental signals coming from magnetic probes with only few mismatches probably due to broken sensors. A suite of procedures (equipped with a user friendly interface to be run even remotely) to provide linearized models for magnetic control is now available on the MAST linux machines. A new current driven model has been used to obtain a state space model having the PF coil currents as inputs. Dynamic simulations of experimental data have been carried out using linearized models, including modelling of the effects of the passive structures, showing a fair agreement. The modelling activity has been useful also to reproduce accurately the interaction between plasma current and radial position control loops.

  6. Linearized models for a new magnetic control in MAST

    International Nuclear Information System (INIS)

    Artaserse, G.; Maviglia, F.; Albanese, R.; McArdle, G.J.; Pangione, L.

    2013-01-01

    Highlights: ► We applied linearized models for a new magnetic control on MAST tokamak. ► A suite of procedures, conceived to be machine independent, have been used. ► We carried out model-based simulations, taking into account eddy currents effects. ► Comparison with the EFIT flux maps and the experimental magnetic signals are shown. ► A current driven model for the dynamic simulations of the experimental data have been performed. -- Abstract: The aim of this work is to provide reliable linearized models for the design and assessment of a new magnetic control system for MAST (Mega Ampère Spherical Tokamak) using rtEFIT, which can easily be exported to MAST Upgrade. Linearized models for magnetic control have been obtained using the 2D axisymmetric finite element code CREATE L. MAST linearized models include equivalent 2D axisymmetric schematization of poloidal field (PF) coils, vacuum vessel, and other conducting structures. A plasmaless and a double null configuration have been chosen as benchmark cases for the comparison with experimental data and EFIT reconstructions. Good agreement has been found with the EFIT flux map and the experimental signals coming from magnetic probes with only few mismatches probably due to broken sensors. A suite of procedures (equipped with a user friendly interface to be run even remotely) to provide linearized models for magnetic control is now available on the MAST linux machines. A new current driven model has been used to obtain a state space model having the PF coil currents as inputs. Dynamic simulations of experimental data have been carried out using linearized models, including modelling of the effects of the passive structures, showing a fair agreement. The modelling activity has been useful also to reproduce accurately the interaction between plasma current and radial position control loops

  7. Model Predictive Control of Mineral Column Flotation Process

    Directory of Open Access Journals (Sweden)

    Yahui Tian

    2018-06-01

    Full Text Available Column flotation is an efficient method commonly used in the mineral industry to separate useful minerals from ores of low grade and complex mineral composition. Its main purpose is to achieve maximum recovery while ensuring desired product grade. This work addresses a model predictive control design for a mineral column flotation process modeled by a set of nonlinear coupled heterodirectional hyperbolic partial differential equations (PDEs and ordinary differential equations (ODEs, which accounts for the interconnection of well-stirred regions represented by continuous stirred tank reactors (CSTRs and transport systems given by heterodirectional hyperbolic PDEs, with these two regions combined through the PDEs’ boundaries. The model predictive control considers both optimality of the process operations and naturally present input and state/output constraints. For the discrete controller design, spatially varying steady-state profiles are obtained by linearizing the coupled ODE–PDE model, and then the discrete system is obtained by using the Cayley–Tustin time discretization transformation without any spatial discretization and/or without model reduction. The model predictive controller is designed by solving an optimization problem with input and state/output constraints as well as input disturbance to minimize the objective function, which leads to an online-solvable finite constrained quadratic regulator problem. Finally, the controller performance to keep the output at the steady state within the constraint range is demonstrated by simulation studies, and it is concluded that the optimal control scheme presented in this work makes this flotation process more efficient.

  8. Automatic Welding Control Using a State Variable Model.

    Science.gov (United States)

    1979-06-01

    A-A10 610 NAVEAL POSTGRADUATE SCH4O.M CEAY CA0/ 13/ SAUTOMATIC WELDING CONTROL USING A STATE VARIABLE MODEL.W()JUN 79 W V "my UNCLASSIFIED...taverse Drive Unit // Jbint Path /Fixed Track 34 (servomotor positioning). Additional controls of heave (vertical), roll (angular rotation about the

  9. Model Prediction Control For Water Management Using Adaptive Prediction Accuracy

    NARCIS (Netherlands)

    Tian, X.; Negenborn, R.R.; Van Overloop, P.J.A.T.M.; Mostert, E.

    2014-01-01

    In the field of operational water management, Model Predictive Control (MPC) has gained popularity owing to its versatility and flexibility. The MPC controller, which takes predictions, time delay and uncertainties into account, can be designed for multi-objective management problems and for

  10. An Integrated Model of Cognitive Control in Task Switching

    Science.gov (United States)

    Altmann, Erik M.; Gray, Wayne D.

    2008-01-01

    A model of cognitive control in task switching is developed in which controlled performance depends on the system maintaining access to a code in episodic memory representing the most recently cued task. The main constraint on access to the current task code is proactive interference from old task codes. This interference and the mechanisms that…

  11. A review on modeling, identification and servo control of robotic ...

    African Journals Online (AJOL)

    user

    This article reviews modeling, identification, and low level control of the robotic excavator. ... The oil viscosity, oil flow through the spool valves, and variable loading, ..... squares, to identify all the unknown individual parameters for a unmanned ..... Robust low level control of robotic excavation, PhD Thesis, The University of ...

  12. Modeling and Velocity Tracking Control for Tape Drive System ...

    African Journals Online (AJOL)

    Modeling and Velocity Tracking Control for Tape Drive System. ... Journal of Applied Sciences and Environmental Management ... The result of the study revealed that 7.07, 8 and 10 of koln values met the design goal and also resulted in optimal control performance with the following characteristics 7.31%,7.71% , 9.41% ...

  13. Model tracking dual stochastic controller design under irregular internal noises

    International Nuclear Information System (INIS)

    Lee, Jong Bok; Heo, Hoon; Cho, Yun Hyun; Ji, Tae Young

    2006-01-01

    Although many methods about the control of irregular external noise have been introduced and implemented, it is still necessary to design a controller that will be more effective and efficient methods to exclude for various noises. Accumulation of errors due to model tracking, internal noises (thermal noise, shot noise and l/f noise) that come from elements such as resistor, diode and transistor etc. in the circuit system and numerical errors due to digital process often destabilize the system and reduce the system performance. New stochastic controller is adopted to remove those noises using conventional controller simultaneously. Design method of a model tracking dual controller is proposed to improve the stability of system while removing external and internal noises. In the study, design process of the model tracking dual stochastic controller is introduced that improves system performance and guarantees robustness under irregular internal noises which can be created internally. The model tracking dual stochastic controller utilizing F-P-K stochastic control technique developed earlier is implemented to reveal its performance via simulation

  14. A Ship Propulsion System Model for Fault-tolerant Control

    DEFF Research Database (Denmark)

    Izadi-Zamanabadi, Roozbeh; Blanke, M.

    This report presents a propulsion system model for a low speed marine vehicle, which can be used as a test benchmark for Fault-Tolerant Control purposes. The benchmark serves the purpose of offering realistic and challenging problems relevant in both FDI and (autonomous) supervisory control area...

  15. Engine modeling and control modeling and electronic management of internal combustion engines

    CERN Document Server

    Isermann, Rolf

    2014-01-01

    The increasing demands for internal combustion engines with regard to fuel consumption, emissions and driveability lead to more actuators, sensors and complex control functions. A systematic implementation of the electronic control systems requires mathematical models from basic design through simulation to calibration. The book treats physically-based as well as models based experimentally on test benches for gasoline (spark ignition) and diesel (compression ignition) engines and uses them for the design of the different control functions. The main topics are: - Development steps for engine control - Stationary and dynamic experimental modeling - Physical models of intake, combustion, mechanical system, turbocharger, exhaust, cooling, lubrication, drive train - Engine control structures, hardware, software, actuators, sensors, fuel supply, injection system, camshaft - Engine control methods, static and dynamic feedforward and feedback control, calibration and optimization, HiL, RCP, control software developm...

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

    International Nuclear Information System (INIS)

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

    1989-10-01

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

  17. Recent Advances in Explicit Multiparametric Nonlinear Model Predictive Control

    KAUST Repository

    Domínguez, Luis F.

    2011-01-19

    In this paper we present recent advances in multiparametric nonlinear programming (mp-NLP) algorithms for explicit nonlinear model predictive control (mp-NMPC). Three mp-NLP algorithms for NMPC are discussed, based on which novel mp-NMPC controllers are derived. The performance of the explicit controllers are then tested and compared in a simulation example involving the operation of a continuous stirred-tank reactor (CSTR). © 2010 American Chemical Society.

  18. Learning and Control Model of the Arm for Loading

    Science.gov (United States)

    Kim, Kyoungsik; Kambara, Hiroyuki; Shin, Duk; Koike, Yasuharu

    We propose a learning and control model of the arm for a loading task in which an object is loaded onto one hand with the other hand, in the sagittal plane. Postural control during object interactions provides important points to motor control theories in terms of how humans handle dynamics changes and use the information of prediction and sensory feedback. For the learning and control model, we coupled a feedback-error-learning scheme with an Actor-Critic method used as a feedback controller. To overcome sensory delays, a feedforward dynamics model (FDM) was used in the sensory feedback path. We tested the proposed model in simulation using a two-joint arm with six muscles, each with time delays in muscle force generation. By applying the proposed model to the loading task, we showed that motor commands started increasing, before an object was loaded on, to stabilize arm posture. We also found that the FDM contributes to the stabilization by predicting how the hand changes based on contexts of the object and efferent signals. For comparison with other computational models, we present the simulation results of a minimum-variance model.

  19. Modeling and Model Predictive Power and Rate Control of Wireless Communication Networks

    Directory of Open Access Journals (Sweden)

    Cunwu Han

    2014-01-01

    Full Text Available A novel power and rate control system model for wireless communication networks is presented, which includes uncertainties, input constraints, and time-varying delays in both state and control input. A robust delay-dependent model predictive power and rate control method is proposed, and the state feedback control law is obtained by solving an optimization problem that is derived by using linear matrix inequality (LMI techniques. Simulation results are given to illustrate the effectiveness of the proposed method.

  20. Modeling and control of magnetorheological fluid dampers using neural networks

    Science.gov (United States)

    Wang, D. H.; Liao, W. H.

    2005-02-01

    Due to the inherent nonlinear nature of magnetorheological (MR) fluid dampers, one of the challenging aspects for utilizing these devices to achieve high system performance is the development of accurate models and control algorithms that can take advantage of their unique characteristics. In this paper, the direct identification and inverse dynamic modeling for MR fluid dampers using feedforward and recurrent neural networks are studied. The trained direct identification neural network model can be used to predict the damping force of the MR fluid damper on line, on the basis of the dynamic responses across the MR fluid damper and the command voltage, and the inverse dynamic neural network model can be used to generate the command voltage according to the desired damping force through supervised learning. The architectures and the learning methods of the dynamic neural network models and inverse neural network models for MR fluid dampers are presented, and some simulation results are discussed. Finally, the trained neural network models are applied to predict and control the damping force of the MR fluid damper. Moreover, validation methods for the neural network models developed are proposed and used to evaluate their performance. Validation results with different data sets indicate that the proposed direct identification dynamic model using the recurrent neural network can be used to predict the damping force accurately and the inverse identification dynamic model using the recurrent neural network can act as a damper controller to generate the command voltage when the MR fluid damper is used in a semi-active mode.

  1. Empirical Reduced-Order Modeling for Boundary Feedback Flow Control

    Directory of Open Access Journals (Sweden)

    Seddik M. Djouadi

    2008-01-01

    Full Text Available This paper deals with the practical and theoretical implications of model reduction for aerodynamic flow-based control problems. Various aspects of model reduction are discussed that apply to partial differential equation- (PDE- based models in general. Specifically, the proper orthogonal decomposition (POD of a high dimension system as well as frequency domain identification methods are discussed for initial model construction. Projections on the POD basis give a nonlinear Galerkin model. Then, a model reduction method based on empirical balanced truncation is developed and applied to the Galerkin model. The rationale for doing so is that linear subspace approximations to exact submanifolds associated with nonlinear controllability and observability require only standard matrix manipulations utilizing simulation/experimental data. The proposed method uses a chirp signal as input to produce the output in the eigensystem realization algorithm (ERA. This method estimates the system's Markov parameters that accurately reproduce the output. Balanced truncation is used to show that model reduction is still effective on ERA produced approximated systems. The method is applied to a prototype convective flow on obstacle geometry. An H∞ feedback flow controller is designed based on the reduced model to achieve tracking and then applied to the full-order model with excellent performance.

  2. Automated Model Fit Method for Diesel Engine Control Development

    NARCIS (Netherlands)

    Seykens, X.; Willems, F.P.T.; Kuijpers, B.; Rietjens, C.

    2014-01-01

    This paper presents an automated fit for a control-oriented physics-based diesel engine combustion model. This method is based on the combination of a dedicated measurement procedure and structured approach to fit the required combustion model parameters. Only a data set is required that is

  3. Modeling for Control of a Wobble–Yoke Stirling Engine

    NARCIS (Netherlands)

    García–Canseco, Eloísa; Scherpen, Jacquelien M.A.; Kuindersma, Marnix

    2009-01-01

    In this paper we derive the dynamic model of a four–cylinder double–acting wobble–yoke Stirling engine. In contrast with the classical thermodynamics methods that dominate the literature of Stirling mechanisms, we present a control system perspective to obtain a useful model for the analysis and

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

    African Journals Online (AJOL)

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

  5. Neutron field control cybernetics model of RBMK reactor operator

    International Nuclear Information System (INIS)

    Polyakov, V.V.; Postnikov, V.V.; Sviridenkov, A.N.

    1992-01-01

    Results on parameter optimization for cybernetics model of RBMK reactor operator by power release control function are presented. Convolutions of various criteria applied previously in algorithms of the program 'Adviser to reactor operator' formed the basis of the model. 7 refs.; 4 figs

  6. LPV model development and control of a solution copolymerization reactor

    NARCIS (Netherlands)

    Rahme, S.; Abbas, H.M.S.; Meskin, N.; Tóth, R.; Mohammadpour, J.

    2016-01-01

    In this paper, linear parameter-varying (LPV) control is considered for a solution copolymerization reactor, which takes into account the time-varying nature of the parameters of the process. The nonlinear model of the process is first converted to an exact LPV model representation in the

  7. Modeling Alaska boreal forests with a controlled trend surface approach

    Science.gov (United States)

    Mo Zhou; Jingjing Liang

    2012-01-01

    An approach of Controlled Trend Surface was proposed to simultaneously take into consideration large-scale spatial trends and nonspatial effects. A geospatial model of the Alaska boreal forest was developed from 446 permanent sample plots, which addressed large-scale spatial trends in recruitment, diameter growth, and mortality. The model was tested on two sets of...

  8. Modeling Supermarket Refrigeration Systems for Supervisory Control in Smart Grid

    DEFF Research Database (Denmark)

    Shafiei, Seyed Ehsan; Rasmussen, Henrik; Stoustrup, Jakob

    2013-01-01

    A modular modeling approach of supermarket refrigeration systems (SRS) which is appropriate for smart grid control purposes is presented in this paper. Modeling and identification are performed by just knowing the system configuration and measured data disregarding the physical details. So...

  9. Automated model fit method for diesel engine control development

    NARCIS (Netherlands)

    Seykens, X.L.J.; Willems, F.P.T.; Kuijpers, B.; Rietjens, C.J.H.

    2014-01-01

    This paper presents an automated fit for a control-oriented physics-based diesel engine combustion model. This method is based on the combination of a dedicated measurement procedure and structured approach to fit the required combustion model parameters. Only a data set is required that is

  10. Logical model for the control of a BWR turbine

    International Nuclear Information System (INIS)

    Vargas O, Y.; Amador G, R.; Ortiz V, J.; Castillo D, R.

    2009-01-01

    In this work a design of a logical model is presented for the turbine control of a nuclear power plant with a BWR like energy source. The model is sought to implement later on inside the thermal hydraulics code of better estimate RELAP/SCDAPSIM. The logical model is developed for the control and protection of the turbine, and the consequent protection to the BWR, considering that the turbine control will be been able to use for one or several turbines in series. The quality of the present design of the logical model of the turbine control is that it considers the most important parameters in the operation of a turbine, besides that they have incorporated to the logical model the secondary parameters that will be activated originally as true when the turbine model is substituted by a detailed model. The development of the logical model of a turbine will be of utility in the short and medium term to carry out analysis on the turbine operation with different operation conditions, of vapor extraction, specific steps of the turbine to feed other equipment s, in addition to analyze the separate and the integrated effect. (Author)

  11. Introducing Model Predictive Control for Improving Power Plant Portfolio Performance

    DEFF Research Database (Denmark)

    Edlund, Kristian Skjoldborg; Bendtsen, Jan Dimon; Børresen, Simon

    2008-01-01

    This paper introduces a model predictive control (MPC) approach for construction of a controller for balancing the power generation against consumption in a power system. The objective of the controller is to coordinate a portfolio consisting of multiple power plant units in the effort to perform...... reference tracking and disturbance rejection in an economically optimal way. The performance function is chosen as a mixture of the `1-norm and a linear weighting to model the economics of the system. Simulations show a significant improvement of the performance of the MPC compared to the current...

  12. Fuzzy Approximate Model for Distributed Thermal Solar Collectors Control

    KAUST Repository

    Elmetennani, Shahrazed

    2014-07-01

    This paper deals with the problem of controlling concentrated solar collectors where the objective consists of making the outlet temperature of the collector tracking a desired reference. The performance of the novel approximate model based on fuzzy theory, which has been introduced by the authors in [1], is evaluated comparing to other methods in the literature. The proposed approximation is a low order state representation derived from the physical distributed model. It reproduces the temperature transfer dynamics through the collectors accurately and allows the simplification of the control design. Simulation results show interesting performance of the proposed controller.

  13. Modeling of Methods to Control Heat-Consumption Efficiency

    Science.gov (United States)

    Tsynaeva, E. A.; Tsynaeva, A. A.

    2016-11-01

    In this work, consideration has been given to thermophysical processes in automated heat consumption control systems (AHCCSs) of buildings, flow diagrams of these systems, and mathematical models describing the thermophysical processes during the systems' operation; an analysis of adequacy of the mathematical models has been presented. A comparison has been made of the operating efficiency of the systems and the methods to control the efficiency. It has been determined that the operating efficiency of an AHCCS depends on its diagram and the temperature chart of central quality control (CQC) and also on the temperature of a low-grade heat source for the system with a heat pump.

  14. Thermal Storage Power Balancing with Model Predictive Control

    DEFF Research Database (Denmark)

    Halvgaard, Rasmus; Poulsen, Niels Kjølstad; Madsen, Henrik

    2013-01-01

    The method described in this paper balances power production and consumption with a large number of thermal loads. Linear controllers are used for the loads to track a temperature set point, while Model Predictive Control (MPC) and model estimation of the load behavior are used for coordination....... The total power consumption of all loads is controlled indirectly through a real-time price. The MPC incorporates forecasts of the power production and disturbances that influence the loads, e.g. time-varying weather forecasts, in order to react ahead of time. A simulation scenario demonstrates...

  15. PWM CONTROLLER'S MODELS FOR INVESTIGATION ACS IN SPICEFAMILY ECAD PROGRAMS

    Directory of Open Access Journals (Sweden)

    O. V. VASYLENKO

    2018-05-01

    Full Text Available Purpose. To improve simulation and design of Automatic Control Systems in the SPICE-compatible programs and to obtain separate economic and universal macromodels of PWM controller. Development of an PWM controller economical macromodel for the study of automatic control systems (ACS in computer-aided design (ECAD  programs, which does not generate algorithmic failures in comparison with the existing models of PWM. Findings. Analysis of SPICE-family applications’ mathematical basis allowed to classifying existing models of PWM-controllers, defining their suitability for ACS simulation. The criteria for the synthesis of new models have been defined. For the SPICE 3G algorithms, the Switch and Averaged models based on behavioral elements has been developed. Universal and economical PWM controller macromodel based on the simple algorithm for determining the output signal with minimum numbers of input parameters has been designed. For the Automated Measuring magnetic susceptibility System, the macromodel of quasi-PWM signal generator have been designed, which is used in the compensation subsystem. This model is different from the existing ones: it synthesizes the staircase output signal instead the pulse one, thus, there is direct control of the amplitude of the output signal, which is taken averaged. The adequacy of the models is confirmed as comparison of the simulation results during investigations of the model already existing in the SPICE program, as well as the results of experiments with real ACS. The modeling of the PWM controller was carried out on the basis of behavioral elements from the ECAD library, simulation (solution of algebra-differential equations systems with programming elements is based on SPICE algorithms. The object of the study was the simulation process of ACS with the pulse-width principle of adjusting the output value. The subject of the research are the models of PWM controllers. Originality. The new macromodel of PWM

  16. Patch models and their applications to multivehicle command and control.

    Science.gov (United States)

    Rao, Venkatesh G; D'Andrea, Raffaello

    2007-06-01

    We introduce patch models, a computational modeling formalism for multivehicle combat domains, based on spatiotemporal abstraction methods developed in the computer science community. The framework yields models that are expressive enough to accommodate nontrivial controlled vehicle dynamics while being within the representational capabilities of common artificial intelligence techniques used in the construction of autonomous systems. The framework allows several key design requirements of next-generation network-centric command and control systems, such as maintenance of shared situation awareness, to be achieved. Major features include support for multiple situation models at each decision node and rapid mission plan adaptation. We describe the formal specification of patch models and our prototype implementation, i.e., Patchworks. The capabilities of patch models are validated through a combat mission simulation in Patchworks, which involves two defending teams protecting a camp from an enemy attacking team.

  17. Discriminative training of self-structuring hidden control neural models

    DEFF Research Database (Denmark)

    Sørensen, Helge Bjarup Dissing; Hartmann, Uwe; Hunnerup, Preben

    1995-01-01

    This paper presents a new training algorithm for self-structuring hidden control neural (SHC) models. The SHC models were trained non-discriminatively for speech recognition applications. Better recognition performance can generally be achieved, if discriminative training is applied instead. Thus...... we developed a discriminative training algorithm for SHC models, where each SHC model for a specific speech pattern is trained with utterances of the pattern to be recognized and with other utterances. The discriminative training of SHC neural models has been tested on the TIDIGITS database...

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

    DEFF Research Database (Denmark)

    Solberg, Brian

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

  19. System control model of a turbine for a BWR

    International Nuclear Information System (INIS)

    Vargas O, Y.; Amador G, R.; Ortiz V, J.; Castillo D, R.; Delfin L, A.

    2009-10-01

    In this work is presented a design of a control system of a turbine for a nuclear power plant with a BWR like energy source. The model seeks to implement later on at thermal hydraulics code of better estimate RELAP/SCDAPSIM. The model is developed for control and protection of turbine, and the consequent protection to the BWR, considering that the turbine control could be employed for one or several turbines in series. The quality of present designs of control pattern of turbine it is that it considers the parameters more important in the operation of a turbine besides that is has incorporated at control the secondary parameters that will be activated originally as true when the turbine model is substituted by a model more detailed. The development of control model of a turbine will be good in short and medium term to realize analysis about the operation of turbine with different operation conditions, of vapor extraction specific steps of turbine to feed other equipment s, besides analyzing the separate effect and integrated effect. (Author)

  20. Humanoid Walking Robot: Modeling, Inverse Dynamics, and Gain Scheduling Control

    Directory of Open Access Journals (Sweden)

    Elvedin Kljuno

    2010-01-01

    Full Text Available This article presents reference-model-based control design for a 10 degree-of-freedom bipedal walking robot, using nonlinear gain scheduling. The main goal is to show concentrated mass models can be used for prediction of the required joint torques for a bipedal walking robot. Relatively complicated architecture, high DOF, and balancing requirements make the control task of these robots difficult. Although linear control techniques can be used to control bipedal robots, nonlinear control is necessary for better performance. The emphasis of this work is to show that the reference model can be a bipedal walking model with concentrated mass at the center of gravity, which removes the problems related to design of a pseudo-inverse system. Another significance of this approach is the reduced calculation requirements due to the simplified procedure of nominal joint torques calculation. Kinematic and dynamic analysis is discussed including results for joint torques and ground force necessary to implement a prescribed walking motion. This analysis is accompanied by a comparison with experimental data. An inverse plant and a tracking error linearization-based controller design approach is described. We propose a novel combination of a nonlinear gain scheduling with a concentrated mass model for the MIMO bipedal robot system.

  1. Development of model reference adaptive control theory for electric power plant control applications

    Energy Technology Data Exchange (ETDEWEB)

    Mabius, L.E.

    1982-09-15

    The scope of this effort includes the theoretical development of a multi-input, multi-output (MIMO) Model Reference Control (MRC) algorithm, (i.e., model following control law), Model Reference Adaptive Control (MRAC) algorithm and the formulation of a nonlinear model of a typical electric power plant. Previous single-input, single-output MRAC algorithm designs have been generalized to MIMO MRAC designs using the MIMO MRC algorithm. This MRC algorithm, which has been developed using Command Generator Tracker methodologies, represents the steady state behavior (in the adaptive sense) of the MRAC algorithm. The MRC algorithm is a fundamental component in the MRAC design and stability analysis. An enhanced MRC algorithm, which has been developed for systems with more controls than regulated outputs, alleviates the MRC stability constraint of stable plant transmission zeroes. The nonlinear power plant model is based on the Cromby model with the addition of a governor valve management algorithm, turbine dynamics and turbine interactions with extraction flows. An application of the MRC algorithm to a linearization of this model demonstrates its applicability to power plant systems. In particular, the generated power changes at 7% per minute while throttle pressure and temperature, reheat temperature and drum level are held constant with a reasonable level of control. The enhanced algorithm reduces significantly control fluctuations without modifying the output response.

  2. Adaptive PID and Model Reference Adaptive Control Switch Controller for Nonlinear Hydraulic Actuator

    Directory of Open Access Journals (Sweden)

    Xin Zuo

    2017-01-01

    Full Text Available Nonlinear systems are modeled as piecewise linear systems at multiple operating points, where the operating points are modeled as switches between constituent linearized systems. In this paper, adaptive piecewise linear switch controller is proposed for improving the response time and tracking performance of the hydraulic actuator control system, which is essentially piecewise linear. The controller composed of PID and Model Reference Adaptive Control (MRAC adaptively chooses the proportion of these two components and makes the designed system have faster response time at the transient phase and better tracking performance, simultaneously. Then, their stability and tracking performance are analyzed and evaluated by the hydraulic actuator control system, the hydraulic actuator is controlled by the electrohydraulic system, and its model is built, which has piecewise linear characteristic. Then the controller results are compared between PID and MRAC and the switch controller designed in this paper is applied to the hydraulic actuator; it is obvious that adaptive switch controller has better effects both on response time and on tracking performance.

  3. Modeling of active control of external magnetohydrodynamic instabilities

    International Nuclear Information System (INIS)

    Bialek, James; Boozer, Allen H.; Mauel, M.E.; Navratil, G.A.

    2001-01-01

    A general circuit formulation of resistive wall mode (RWM) feedback stabilization developed by Boozer [Phys. Plasmas 5, 3350 (1998)] has been used as the basis for the VALEN computer code that calculates the performance of an active control system in arbitrary geometry. The code uses a finite element representation of a thin shell structure in an integral formulation to model arbitrary conducting walls. This is combined with a circuit representation of stable and unstable plasma modes. Benchmark comparisons of VALEN results with large aspect ratio analytic model of the current driven kink mode are in very good agreement. VALEN also models arbitrary sensors, control coils, and the feedback logic connecting these sensors and control coils to provide a complete simulation capability for feedback control of plasma instabilities. VALEN modeling is in good agreement with experimental results on DIII-D [Garofalo et al., Nucl. Fusion 40, 1491 (2000)] and HBT-EP [Cates et al., Phys. Plasmas 7, 3133 (2000)]. VALEN feedback simulations have also been used to evaluate and optimize the sensor/coil configurations for present and planned RWM experiments on DIII-D. These studies have shown a clear advantage for the use of local poloidal field sensors driving a 'mode control' feedback logic control loop and configurations which minimize the control coil coupling to the stabilizing resistive wall

  4. Control of the exercise hyperpnoea in humans: a modeling perspective.

    Science.gov (United States)

    Ward, S A

    2000-09-01

    Models of the exercise hyperpnoea have classically incorporated elements of proportional feedback (carotid and medullary chemosensory) and feedforward (central and/or peripheral neurogenic) control. However, the precise details of the control process remain unresolved, reflecting in part both technical and interpretational limitations inherent in isolating putative control mechanisms in the intact human, and also the challenges to linear control theory presented by multiple-input integration, especially with regard to the ventilatory and gas-exchange complexities encountered at work rates which engender a metabolic acidosis. While some combination of neurogenic, chemoreflex and circulatory-coupled processes are likely to contribute to the control, the system appears to evidence considerable redundancy. This, coupled with the lack of appreciable error signals in the mean levels of arterial blood gas tensions and pH over a wide range of work rates, has motivated the formulation of innovative control models that reflect not only spatial interactions but also temporal interactions (i.e. memory). The challenge is to discriminate between robust competing control models that: (a) integrate such processes within plausible physiological equivalents; and (b) account for both the dynamic and steady-state system response over a range of exercise intensities. Such models are not yet available.

  5. A Mathematical Model of Marine Diesel Engine Speed Control System

    Science.gov (United States)

    Sinha, Rajendra Prasad; Balaji, Rajoo

    2018-02-01

    Diesel engine is inherently an unstable machine and requires a reliable control system to regulate its speed for safe and efficient operation. Also, the diesel engine may operate at fixed or variable speeds depending upon user's needs and accordingly the speed control system should have essential features to fulfil these requirements. This paper proposes a mathematical model of a marine diesel engine speed control system with droop governing function. The mathematical model includes static and dynamic characteristics of the control loop components. Model of static characteristic of the rotating fly weights speed sensing element provides an insight into the speed droop features of the speed controller. Because of big size and large time delay, the turbo charged diesel engine is represented as a first order system or sometimes even simplified to a pure integrator with constant gain which is considered acceptable in control literature. The proposed model is mathematically less complex and quick to use for preliminary analysis of the diesel engine speed controller performance.

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

    Directory of Open Access Journals (Sweden)

    Camilo Lozoya

    2016-01-01

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

  7. Model Oriented Application Generation for Industrial Control Systems

    CERN Document Server

    Copy, B; Blanco Vinuela, E; Fernandez Adiego, B; Nogueira Ferandes, R; Prieto Barreiro, I

    2011-01-01

    The CERN Unified Industrial Control Systems framework (UNICOS) is a software generation methodology and a collection of development tools that standardizes the design of industrial control applications [1]. A Software Factory, named the UNICOS Application Builder (UAB) [2], was introduced to ease extensibility and maintenance of the framework, introducing a stable metamodel, a set of platformindependent models and platformspecific configurations against which code generation plugins and configuration generation plugins can be written. Such plugins currently target PLC programming environments (Schneider and SIEMENS PLCs) as well as SIEMENS WinCC Open Architecture SCADA (previously known as ETM PVSS) but are being expanded to cover more and more aspects of process control systems. We present what constitutes the UNICOS metamodel and the models in use, how these models can be used to capture knowledge about industrial control systems and how this knowledge can be leveraged to generate both code and configuratio...

  8. Software toolkit for modeling, simulation and control of soft robots

    OpenAIRE

    Coevoet , Eulalie; Morales-Bieze , Thor; Largilliere , Frederick; Zhang , Zhongkai; Thieffry , Maxime; Sanz-Lopez , Mario; Carrez , Bruno; Marchal , Damien; Goury , Olivier; Dequidt , Jeremie; Duriez , Christian

    2017-01-01

    International audience; The technological differences between traditional robotics and soft robotics have an impact on all of the modeling tools generally in use, including direct kinematics and inverse models, Jacobians, and dynamics. Due to the lack of precise modeling and control methods for soft robots, the promising concepts of using such design for complex applications (medicine, assistance, domestic robotics...) cannot be practically implemented. This paper presents a first unified sof...

  9. The adaptive cruise control vehicles in the cellular automata model

    International Nuclear Information System (INIS)

    Jiang Rui; Wu Qingsong

    2006-01-01

    This Letter presented a cellular automata model where the adaptive cruise control vehicles are modelled. In this model, the constant time headway policy is adopted. The fundamental diagram is presented. The simulation results are in good agreement with the analytical ones. The mixture of ACC vehicles with manually driven vehicles is investigated. It is shown that with the introduction of ACC vehicles, the jam can be suppressed

  10. Automation of program model developing for complex structure control objects

    International Nuclear Information System (INIS)

    Ivanov, A.P.; Sizova, T.B.; Mikhejkina, N.D.; Sankovskij, G.A.; Tyufyagin, A.N.

    1991-01-01

    A brief description of software for automated developing the models of integrating modular programming system, program module generator and program module library providing thermal-hydraulic calcualtion of process dynamics in power unit equipment components and on-line control system operation simulation is given. Technical recommendations for model development are based on experience in creation of concrete models of NPP power units. 8 refs., 1 tab., 4 figs

  11. Model-Checking Real-Time Control Programs

    DEFF Research Database (Denmark)

    Iversen, T. K.; Kristoffersen, K. J.; Larsen, Kim Guldstrand

    2000-01-01

    In this paper, we present a method for automatic verification of real-time control programs running on LEGO(R) RCX(TM) bricks using the verification tool UPPALL. The control programs, consisting of a number of tasks running concurrently, are automatically translated into the mixed automata model...... of UPPAAL. The fixed scheduling algorithm used by the LEGO(R) RCX(TM) processor is modeled in UPPALL, and supply of similar (sufficient) timed automata models for the environment allows analysis of the overall real-time system using the tools of UPPALL. To illustrate our technique for sorting LEGO(R) bricks...

  12. RF system modeling and controller design for the European XFEL

    International Nuclear Information System (INIS)

    Schmidt, Christian

    2011-06-01

    The European XFEL is being constructed at the Deutsche Elektronen Synchrotron DESY to generate intense, ultrashort pulses of highly coherent and monochromatic X-Rays for material science research. X-ray flashes are generated by accelerating electron bunches within superconducting cavities with radio frequency (RF) fields to energies up to 17.5 GeV. The digital control of these fields requires extremely high quality in order to achieve the physical processes of photon generation. DESY offers with FLASH a pilot test facility, allowing to test and develop most necessary components, even before the XFEL is conducted. Current field control is based on a proportional feedback controller in addition to a constant feedforward drive, which do not meet the high requirements of the XFEL. This thesis shows that a model based controller design can achieve the necessary field regulation requirements. A linear, time invariant ''black box model'' is estimated, which characterizes the essential dynamic behavior. This model is not based on physical assumptions, but describes exclusively the transfer behavior of the plant. The acceleration modules are operated in a pulsed mode, in which the RF field must be kept constant for a finite period. The character of the disturbances and variations from pulse-to-pulse, together with the properties of the system, require a combination of controlled feedforward drive and feedback. Generally unpredictable, low frequency pulse-to-pulse variations are suppressed by the feedback controller. The structural design of the complex multivariable feedback controller is given, which constrains the model based design approach to assign the controller parameters only. Estimation of the parameters, which can not be tuned manually, is done by the method of H loop shaping which is often applied in modern control theory. However, disturbances within a pulse are in a high frequency range concerning the short pulse duration. They are not sufficiently suppressed

  13. RF system modeling and controller design for the European XFEL

    Energy Technology Data Exchange (ETDEWEB)

    Schmidt, Christian

    2011-06-15

    The European XFEL is being constructed at the Deutsche Elektronen Synchrotron DESY to generate intense, ultrashort pulses of highly coherent and monochromatic X-Rays for material science research. X-ray flashes are generated by accelerating electron bunches within superconducting cavities with radio frequency (RF) fields to energies up to 17.5 GeV. The digital control of these fields requires extremely high quality in order to achieve the physical processes of photon generation. DESY offers with FLASH a pilot test facility, allowing to test and develop most necessary components, even before the XFEL is conducted. Current field control is based on a proportional feedback controller in addition to a constant feedforward drive, which do not meet the high requirements of the XFEL. This thesis shows that a model based controller design can achieve the necessary field regulation requirements. A linear, time invariant ''black box model'' is estimated, which characterizes the essential dynamic behavior. This model is not based on physical assumptions, but describes exclusively the transfer behavior of the plant. The acceleration modules are operated in a pulsed mode, in which the RF field must be kept constant for a finite period. The character of the disturbances and variations from pulse-to-pulse, together with the properties of the system, require a combination of controlled feedforward drive and feedback. Generally unpredictable, low frequency pulse-to-pulse variations are suppressed by the feedback controller. The structural design of the complex multivariable feedback controller is given, which constrains the model based design approach to assign the controller parameters only. Estimation of the parameters, which can not be tuned manually, is done by the method of H{sub {infinity}} loop shaping which is often applied in modern control theory. However, disturbances within a pulse are in a high frequency range concerning the short pulse duration

  14. Nonlinear Economic Model Predictive Control Strategy for Active Smart Buildings

    DEFF Research Database (Denmark)

    Santos, Rui Mirra; Zong, Yi; Sousa, Joao M. C.

    2016-01-01

    Nowadays, the development of advanced and innovative intelligent control techniques for energy management in buildings is a key issue within the smart grid topic. A nonlinear economic model predictive control (EMPC) scheme, based on the branch-and-bound tree search used as optimization algorithm ...... controller is shown very reliable keeping the comfort levels in the two considered seasons and shifting the load away from peak hours in order to achieve the desired flexible electricity consumption.......Nowadays, the development of advanced and innovative intelligent control techniques for energy management in buildings is a key issue within the smart grid topic. A nonlinear economic model predictive control (EMPC) scheme, based on the branch-and-bound tree search used as optimization algorithm...

  15. Enhanced pid vs model predictive control applied to bldc motor

    Science.gov (United States)

    Gaya, M. S.; Muhammad, Auwal; Aliyu Abdulkadir, Rabiu; Salim, S. N. S.; Madugu, I. S.; Tijjani, Aminu; Aminu Yusuf, Lukman; Dauda Umar, Ibrahim; Khairi, M. T. M.

    2018-01-01

    BrushLess Direct Current (BLDC) motor is a multivariable and highly complex nonlinear system. Variation of internal parameter values with environment or reference signal increases the difficulty in controlling the BLDC effectively. Advanced control strategies (like model predictive control) often have to be integrated to satisfy the control desires. Enhancing or proper tuning of a conventional algorithm results in achieving the desired performance. This paper presents a performance comparison of Enhanced PID and Model Predictive Control (MPC) applied to brushless direct current motor. The simulation results demonstrated that the PSO-PID is slightly better than the PID and MPC in tracking the trajectory of the reference signal. The proposed scheme could be useful algorithms for the system.

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

    Directory of Open Access Journals (Sweden)

    Agus Naba

    2016-12-01

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

  17. Health-aware Model Predictive Control of Pasteurization Plant

    Science.gov (United States)

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

    2017-01-01

    In order to optimize the trade-off between components life and energy consumption, the integration of a system health management and control modules is required. This paper proposes the integration of model predictive control (MPC) with a fatigue estimation approach that minimizes the damage of the components of a pasteurization plant. The fatigue estimation is assessed with the rainflow counting algorithm. Using data from this algorithm, a simplified model that characterizes the health of the system is developed and integrated with MPC. The MPC controller objective is modified by adding an extra criterion that takes into account the accumulated damage. But, a steady-state offset is created by adding this extra criterion. Finally, by including an integral action in the MPC controller, the steady-state error for regulation purpose is eliminated. The proposed control scheme is validated in simulation using a simulator of a utility-scale pasteurization plant.

  18. MODELING CONTROLLED ASYNCHRONOUS ELECTRIC DRIVES WITH MATCHING REDUCERS AND TRANSFORMERS

    Directory of Open Access Journals (Sweden)

    V. S. Petrushin

    2015-04-01

    Full Text Available Purpose. Working out of mathematical models of the speed-controlled induction electric drives ensuring joint consideration of transformers, motors and loadings, and also matching reducers and transformers, both in static, and in dynamic regimes for the analysis of their operating characteristics. Methodology. At mathematical modelling are considered functional, mass, dimensional and cost indexes of reducers and transformers that allows observing engineering and economic aspects of speed-controlled induction electric drives. The mathematical models used for examination of the transitive electromagnetic and electromechanical processes, are grounded on systems of nonlinear differential equations with nonlinear coefficients (parameters of equivalent circuits of motors, varying in each operating point, including owing to appearances of saturation of magnetic system and current displacement in a winding of a rotor of an induction motor. For the purpose of raise of level of adequacy of models a magnetic circuit iron, additional and mechanical losses are considered. Results. Modelling of the several speed-controlled induction electric drives, different by components, but working on a loading equal on character, magnitude and a demanded control range is executed. At use of characteristic families including mechanical, at various parameters of regulating on which performances of the load mechanism are superimposed, the adjusting characteristics representing dependences of a modification of electrical, energy and thermal magnitudes from an angular speed of motors are gained. Originality. The offered complex models of speed-controlled induction electric drives with matching reducers and transformers, give the chance to realize well-founded sampling of components of drives. They also can be used as the design models by working out of speed-controlled induction motors. Practical value. Operating characteristics of various speed-controlled induction electric

  19. Embedded model control GNC for the Next Generation Gravity Mission

    Science.gov (United States)

    Colangelo, Luigi; Massotti, Luca; Canuto, Enrico; Novara, Carlo

    2017-11-01

    A Next Generation Gravity Mission (NGGM) concept for measuring the Earth's variable gravity field has been recently proposed by ESA. The mission objective consists in measuring the temporal variations of the Earth gravity field over a long-time span, with very high spatial and temporal resolutions. This paper focuses on the guidance, navigation and control (GNC) design for the science phase of the NGGM mission. NGGM will consist of a two-satellite long-distance formation like GRACE, where each satellite will be controlled to be drag-free like GOCE. Satellite-to-satellite distance variations, encoding gravity anomalies, will be measured by laser interferometry. The formation satellites, distant up to 200 km, will fly in a quasi-polar orbit at an Earth altitude between 300 and 450 km. Orbit and formation control counteract bias and drift of the residual drag-free accelerations, in order to reach orbit/formation long-term stability. Drag-free control allows the formation to fly counteracting the atmospheric drag, ideally subject only to gravity. Orbit and formation control, designed through the innovative Integrated Formation Control (IFC), have been integrated into a unique control system, aiming at stabilizing the formation triangle consisting of satellites and Earth Center of Masses. In addition, both spacecraft must align their control axis to the satellite-to-satellite line (SSL) with micro-radian accuracy. This is made possible by specific optical sensors and the inter-satellite laser interferometer, capable of materializing the SSL. Such sensors allow each satellite to pursue an autonomous alignment after a suitable acquisition procedure. Pointing control is severely constrained by the angular drag-free control, which must ideally zero the angular acceleration vector, in the science frequency band. The control unit has been designed according to the Embedded Model Control methodology and is organized in a hierarchical way, where the drag-free control plays the

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

    Science.gov (United States)

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

    1997-01-01

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

  1. Impulsive control of a financial model [rapid communication

    Science.gov (United States)

    Sun, Jitao; Qiao, Fei; Wu, Qidi

    2005-02-01

    In this Letter, several new theorems on the stability of impulsive control systems are presented. These theorem are then used to find the conditions under which an advertising strategy can be asymptotically control to the equilibrium point by using impulsive control. Given the parameters of the financial model and the impulsive control law, an estimation of the upper bound of the impulse interval is given, i.e., number of advert can been decreased (i.e., can decrease cost) for to obtain the equivalent advertising effect.The result is illustrated to be efficient through a numerical example.

  2. Distributed model based control of multi unit evaporation systems

    International Nuclear Information System (INIS)

    Yudi Samyudia

    2006-01-01

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

  3. Intelligent control of HVAC systems. Part I: Modeling and synthesis

    Directory of Open Access Journals (Sweden)

    Adrian TOADER

    2013-03-01

    Full Text Available This is the first part of a work on intelligent type control of Heating, Ventilating and Air-Conditioning (HVAC systems. The study is performed from the perspective of giving a unitary control method to ensure high energy efficiency and air quality improving. To illustrate the proposed HVAC control technique, in this first part it is considered as benchmark problem a single thermal space HVAC system. The construction of the mathematical model is performed only with a view to obtain a framework of HVAC intelligent control validation by numerical simulations. The latter will be reported in a second part of the study.

  4. Exploring bird aerodynamics using radio-controlled models

    International Nuclear Information System (INIS)

    Hoey, Robert G

    2010-01-01

    A series of radio-controlled glider models was constructed by duplicating the aerodynamic shape of soaring birds (raven, turkey vulture, seagull and pelican). Controlled tests were conducted to determine the level of longitudinal and lateral-directional static stability, and to identify the characteristics that allowed flight without a vertical tail. The use of tail-tilt for controlling small bank-angle changes, as observed in soaring birds, was verified. Subsequent tests, using wing-tip ailerons, inferred that birds use a three-dimensional flow pattern around the wing tip (wing tip vortices) to control adverse yaw and to create a small amount of forward thrust in gliding flight.

  5. Modelling and performance assessment of an antenna-control system

    Science.gov (United States)

    Burrows, C. R.

    1982-03-01

    An assessment is made of a surveillance-radar control system designed to provide a sector-search capability and continuous control of antenna speed without unwanted torque-reaction on the supporting mast. These objectives are attained by utilizing regenerative braking, and control is exercised through Perbury CVTs. A detailed analysis of the system is given. The models derived for the Perbury CVTs supplement the qualitative data contained in earlier papers. Some results from a computer simulation are presented. Although the paper is concerned with a particular problem, the analysis of the CVTs, and the concept of using energy transfer to control large inertial loads, are of more general interest.

  6. Robust Control Mixer Method for Reconfigurable Control Design Using Model Matching Strategy

    DEFF Research Database (Denmark)

    Yang, Zhenyu; Blanke, Mogens; Verhagen, Michel

    2007-01-01

    A novel control mixer method for recon¯gurable control designs is developed. The proposed method extends the matrix-form of the conventional control mixer concept into a LTI dynamic system-form. The H_inf control technique is employed for these dynamic module designs after an augmented control...... system is constructed through a model-matching strategy. The stability, performance and robustness of the reconfigured system can be guaranteed when some conditions are satisfied. To illustrate the effectiveness of the proposed method, a robot system subjected to failures is used to demonstrate...

  7. Process control for sheet-metal stamping process modeling, controller design and shop-floor implementation

    CERN Document Server

    Lim, Yongseob; Ulsoy, A Galip

    2014-01-01

    Process Control for Sheet-Metal Stamping presents a comprehensive and structured approach to the design and implementation of controllers for the sheet metal stamping process. The use of process control for sheet-metal stamping greatly reduces defects in deep-drawn parts and can also yield large material savings from reduced scrap. Sheet-metal forming is a complex process and most often characterized by partial differential equations that are numerically solved using finite-element techniques. In this book, twenty years of academic research are reviewed and the resulting technology transitioned to the industrial environment. The sheet-metal stamping process is modeled in a manner suitable for multiple-input multiple-output control system design, with commercially available sensors and actuators. These models are then used to design adaptive controllers and real-time controller implementation is discussed. Finally, experimental results from actual shopfloor deployment are presented along with ideas for further...

  8. Modeling validation and control analysis for controlled temperature and humidity of air conditioning system.

    Science.gov (United States)

    Lee, Jing-Nang; Lin, Tsung-Min; Chen, Chien-Chih

    2014-01-01

    This study constructs an energy based model of thermal system for controlled temperature and humidity air conditioning system, and introduces the influence of the mass flow rate, heater and humidifier for proposed control criteria to achieve the controlled temperature and humidity of air conditioning system. Then, the reliability of proposed thermal system model is established by both MATLAB dynamic simulation and the literature validation. Finally, the PID control strategy is applied for controlling the air mass flow rate, humidifying capacity, and heating, capacity. The simulation results show that the temperature and humidity are stable at 541 sec, the disturbance of temperature is only 0.14 °C, 0006 kg(w)/kg(da) in steady-state error of humidity ratio, and the error rate is only 7.5%. The results prove that the proposed system is an effective controlled temperature and humidity of an air conditioning system.

  9. Steering Angle Control of Car for Dubins Path-tracking Using Model Predictive Control

    Science.gov (United States)

    Kusuma Rahma Putri, Dian; Subchan; Asfihani, Tahiyatul

    2018-03-01

    Car as one of transportation is inseparable from technological developments. About ten years, there are a lot of research and development on lane keeping system(LKS) which is a system that automaticaly controls the steering to keep the vehicle especially car always on track. This system can be developed for unmanned cars. Unmanned system car requires navigation, guidance and control which is able to direct the vehicle to move toward the desired path. The guidance system is represented by using Dubins-Path that will be controlled by using Model Predictive Control. The control objective is to keep the car’s movement that represented by dinamic lateral motion model so car can move according to the path appropriately. The simulation control on the four types of trajectories that generate the value for steering angle and steering angle changes are at the specified interval.

  10. Modeling Validation and Control Analysis for Controlled Temperature and Humidity of Air Conditioning System

    Directory of Open Access Journals (Sweden)

    Jing-Nang Lee

    2014-01-01

    Full Text Available This study constructs an energy based model of thermal system for controlled temperature and humidity air conditioning system, and introduces the influence of the mass flow rate, heater and humidifier for proposed control criteria to achieve the controlled temperature and humidity of air conditioning system. Then, the reliability of proposed thermal system model is established by both MATLAB dynamic simulation and the literature validation. Finally, the PID control strategy is applied for controlling the air mass flow rate, humidifying capacity, and heating, capacity. The simulation results show that the temperature and humidity are stable at 541 sec, the disturbance of temperature is only 0.14°C, 0006 kgw/kgda in steady-state error of humidity ratio, and the error rate is only 7.5%. The results prove that the proposed system is an effective controlled temperature and humidity of an air conditioning system.

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

    Science.gov (United States)

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

    2018-04-03

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

  12. Fault Tolerance Automotive Air-Ratio Control Using Extreme Learning Machine Model Predictive Controller

    OpenAIRE

    Pak Kin Wong; Hang Cheong Wong; Chi Man Vong; Tong Meng Iong; Ka In Wong; Xianghui Gao

    2015-01-01

    Effective air-ratio control is desirable to maintain the best engine performance. However, traditional air-ratio control assumes the lambda sensor located at the tail pipe works properly and relies strongly on the air-ratio feedback signal measured by the lambda sensor. When the sensor is warming up during cold start or under failure, the traditional air-ratio control no longer works. To address this issue, this paper utilizes an advanced modelling technique, kernel extreme learning machine (...

  13. Individual-based modelling and control of bovine brucellosis

    Science.gov (United States)

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

    2018-05-01

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

  14. MATLAB/SIMULINK model of CANDU reactor for control studies

    International Nuclear Information System (INIS)

    Javidnia, H.; Jiang, J.

    2006-01-01

    In this paper a MATLAB/SIMULINK model is developed for a CANDU type reactor. The data for the reactor are taken from an Indian PHWR, which is very similar to CANDU in its design. Among the different feedback mechanisms in the core of the reactor, only xenon has been considered which plays an important role in spatial oscillations. The model is verified under closed loop scenarios with simple PI controller. The results of the simulation show that this model can be used for controller design and simulation of the reactor systems. Adding models of the other components of a CANDU reactor would ultimately result in a complete model of CANDU plant in MATLAB/SIMULINK. (author)

  15. Introduction to modeling and control of internal combustion engine systems

    Energy Technology Data Exchange (ETDEWEB)

    Guzzella, Lino; Onder, Christopher H. [ETH Zuerich (Switzerland). Institute for Dynamic Systems and Control

    2010-07-01

    Internal combustion engines (ICE) still have potential for substantial improvements, particularly with regard to fuel efficiency and environmental compatibility. In order to fully exploit the remaining margins, increasingly sophisticated control systems have to be applied. This book offers an introduction to cost-effective model-based control-system design for ICE. The primary emphasis is put on the ICE and its auxiliary devices. Mathematical models for these processes are developed and solutions for selected feedforward and feedback control-problems are presented. The discussions concerning pollutant emissions and fuel economy of ICE in automotive applications constantly intensified since the first edition of this book was published. Concerns about the air quality, the limited resources of fossil fuels and the detrimental effects of greenhouse gases exceedingly spurred the interest of both the industry and academia in further improvements. The most important changes and additions included in this second edition are: - restructured and slightly extended section on superchargers; - short subsection on rotational oscillations and their treatment on engine test-benches; - complete section on modeling, detection, and control of engine knock; - improved physical and chemical model for the three-way catalytic converter; - new methodology for the design of an air-to-fuel ratio controller; - short introduction to thermodynamic engine-cycle calculation and corresponding control-oriented aspects. (orig.)

  16. Propulsion Controls Modeling for a Small Turbofan Engine

    Science.gov (United States)

    Connolly, Joseph W.; Csank, Jeffrey T.; Chicatelli, Amy; Franco, Kevin

    2017-01-01

    A nonlinear dynamic model and propulsion controller are developed for a small-scale turbofan engine. The small-scale turbofan engine is based on the Price Induction company's DGEN 380, one of the few turbofan engines targeted for the personal light jet category. Comparisons of the nonlinear dynamic turbofan engine model to actual DGEN 380 engine test data and a Price Induction simulation are provided. During engine transients, the nonlinear model typically agrees within 10 percent error, even though the nonlinear model was developed from limited available engine data. A gain scheduled proportional integral low speed shaft controller with limiter safety logic is created to replicate the baseline DGEN 380 controller. The new controller provides desired gain and phase margins and is verified to meet Federal Aviation Administration transient propulsion system requirements. In understanding benefits, there is a need to move beyond simulation for the demonstration of advanced control architectures and technologies by using real-time systems and hardware. The small-scale DGEN 380 provides a cost effective means to accomplish advanced controls testing on a relevant turbofan engine platform.

  17. Model reduction in integrated controls-structures design

    Science.gov (United States)

    Maghami, Peiman G.

    1993-01-01

    It is the objective of this paper to present a model reduction technique developed for the integrated controls-structures design of flexible structures. Integrated controls-structures design problems are typically posed as nonlinear mathematical programming problems, where the design variables consist of both structural and control parameters. In the solution process, both structural and control design variables are constantly changing; therefore, the dynamic characteristics of the structure are also changing. This presents a problem in obtaining a reduced-order model for active control design and analysis which will be valid for all design points within the design space. In other words, the frequency and number of the significant modes of the structure (modes that should be included) may vary considerably throughout the design process. This is also true as the locations and/or masses of the sensors and actuators change. Moreover, since the number of design evaluations in the integrated design process could easily run into thousands, any feasible order-reduction method should not require model reduction analysis at every design iteration. In this paper a novel and efficient technique for model reduction in the integrated controls-structures design process, which addresses these issues, is presented.

  18. Optimal control in a model of malaria with differential susceptibility

    Science.gov (United States)

    Hincapié, Doracelly; Ospina, Juan

    2014-06-01

    A malaria model with differential susceptibility is analyzed using the optimal control technique. In the model the human population is classified as susceptible, infected and recovered. Susceptibility is assumed dependent on genetic, physiological, or social characteristics that vary between individuals. The model is described by a system of differential equations that relate the human and vector populations, so that the infection is transmitted to humans by vectors, and the infection is transmitted to vectors by humans. The model considered is analyzed using the optimal control method when the control consists in using of insecticide-treated nets and educational campaigns; and the optimality criterion is to minimize the number of infected humans, while keeping the cost as low as is possible. One first goal is to determine the effects of differential susceptibility in the proposed control mechanism; and the second goal is to determine the algebraic form of the basic reproductive number of the model. All computations are performed using computer algebra, specifically Maple. It is claimed that the analytical results obtained are important for the design and implementation of control measures for malaria. It is suggested some future investigations such as the application of the method to other vector-borne diseases such as dengue or yellow fever; and also it is suggested the possible application of free software of computer algebra like Maxima.

  19. Dynamic Modelling and Adaptive Traction Control for Mobile Robots

    Directory of Open Access Journals (Sweden)

    A. Albagul

    2004-09-01

    Full Text Available Mobile robots have received a great deal of research in recent years. A significant amount of research has been published in many aspects related to mobile robots. Most of the research is devoted to design and develop some control techniques for robot motion and path planning. A large number of researchers have used kinematic models to develop motion control strategy for mobile robots. Their argument and assumption that these models are valid if the robot has low speed, low acceleration and light load. However, dynamic modelling of mobile robots is very important as they are designed to travel at higher speed and perform heavy duty work. This paper presents and discusses a new approach to develop a dynamic model and control strategy for wheeled mobile robot which I modelled as a rigid body that roles on two wheels and a castor. The motion control strategy consists of two levels. The first level is dealing with the dynamic of the system and denoted as ‘Low’ level controller. The second level is developed to take care of path planning and trajectory generation.

  20. Embedded Control System Design A Model Based Approach

    CERN Document Server

    Forrai, Alexandru

    2013-01-01

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

  1. Adaptive model predictive process control using neural networks

    Science.gov (United States)

    Buescher, K.L.; Baum, C.C.; Jones, R.D.

    1997-08-19

    A control system for controlling the output of at least one plant process output parameter is implemented by adaptive model predictive control using a neural network. An improved method and apparatus provides for sampling plant output and control input at a first sampling rate to provide control inputs at the fast rate. The MPC system is, however, provided with a network state vector that is constructed at a second, slower rate so that the input control values used by the MPC system are averaged over a gapped time period. Another improvement is a provision for on-line training that may include difference training, curvature training, and basis center adjustment to maintain the weights and basis centers of the neural in an updated state that can follow changes in the plant operation apart from initial off-line training data. 46 figs.

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

    DEFF Research Database (Denmark)

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

    2010-01-01

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

  3. An improved robust model predictive control for linear parameter-varying input-output models

    NARCIS (Netherlands)

    Abbas, H.S.; Hanema, J.; Tóth, R.; Mohammadpour, J.; Meskin, N.

    2018-01-01

    This paper describes a new robust model predictive control (MPC) scheme to control the discrete-time linear parameter-varying input-output models subject to input and output constraints. Closed-loop asymptotic stability is guaranteed by including a quadratic terminal cost and an ellipsoidal terminal

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

    Science.gov (United States)

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

    2017-12-01

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

  5. Energy Auditor and Quality Control Inspector Competency Model

    Energy Technology Data Exchange (ETDEWEB)

    Head, Heather R [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Kurnik, Charles W [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Schroeder, Derek [U.S. Department of Energy; Cutchin, Kelly [Simonson Management Services

    2018-05-02

    The Energy Auditor (EA) and Quality Control Inspector (QCI) Competency model was developed to identify the soft skills, foundational competencies and define the levels of Knowledge, Skills, and Abilities (KSAs) required to successfully perform the tasks defined in the EA and QCI Job Task Analysis (JTAs), the U.S. Department of Energy (DOE) used the U.S. Department of Labor's (DOL) Competency Model Clearinghouse resources to develop a QCI and EA Competency Model. To keep the QCI and EA competency model consistent with other construction and energy management competency models, DOE and the National Renewable Energy Laboratory used the existing 'Residential Construction Competency Model' and the 'Advanced Commercial Building Competency Model' where appropriate.

  6. Direct model reference adaptive control with application to flexible robots

    Science.gov (United States)

    Steinvorth, Rodrigo; Kaufman, Howard; Neat, Gregory W.

    1992-01-01

    A modification to a direct command generator tracker-based model reference adaptive control (MRAC) system is suggested in this paper. This modification incorporates a feedforward into the reference model's output as well as the plant's output. Its purpose is to eliminate the bounded model following error present in steady state when previous MRAC systems were used. The algorithm was evaluated using the dynamics for a single-link flexible-joint arm. The results of these simulations show a response with zero steady state model following error. These results encourage further use of MRAC for various types of nonlinear plants.

  7. Real time modeling, simulation and control of dynamical systems

    CERN Document Server

    Mughal, Asif Mahmood

    2016-01-01

    This book introduces modeling and simulation of linear time invariant systems and demonstrates how these translate to systems engineering, mechatronics engineering, and biomedical engineering. It is organized into nine chapters that follow the lectures used for a one-semester course on this topic, making it appropriate for students as well as researchers. The author discusses state space modeling derived from two modeling techniques and the analysis of the system and usage of modeling in control systems design. It also contains a unique chapter on multidisciplinary energy systems with a special focus on bioengineering systems and expands upon how the bond graph augments research in biomedical and bio-mechatronics systems.

  8. Domestic appliances energy optimization with model predictive control

    International Nuclear Information System (INIS)

    Rodrigues, E.M.G.; Godina, R.; Pouresmaeil, E.; Ferreira, J.R.; Catalão, J.P.S.

    2017-01-01

    Highlights: • An alternative power management control for home appliances that require thermal regulation is presented. • A Model Predictive Control scheme is assessed and its performance studied and compared to the thermostat. • Problem formulation is explored through tuning weights with the aim of reducing energetic consumption and cost. • A modulation scheme of a two-level Model Predictive Control signal as an interface block is presented. • The implementation costs in home appliances with thermal regulation requirements are reduced. - Abstract: A vital element in making a sustainable world is correctly managing the energy in the domestic sector. Thus, this sector evidently stands as a key one for to be addressed in terms of climate change goals. Increasingly, people are aware of electricity savings by turning off the equipment that is not been used, or connect electrical loads just outside the on-peak hours. However, these few efforts are not enough to reduce the global energy consumption, which is increasing. Much of the reduction was due to technological improvements, however with the advancing of the years new types of control arise. Domestic appliances with the purpose of heating and cooling rely on thermostatic regulation technique. The study in this paper is focused on the subject of an alternative power management control for home appliances that require thermal regulation. In this paper a Model Predictive Control scheme is assessed and its performance studied and compared to the thermostat with the aim of minimizing the cooling energy consumption through the minimization of the energy cost while satisfying the adequate temperature range for the human comfort. In addition, the Model Predictive Control problem formulation is explored through tuning weights with the aim of reducing energetic consumption and cost. For this purpose, the typical consumption of a 24 h period of a summer day was simulated a three-level tariff scheme was used. The new

  9. Control of chaotic dynamics in an OLG economic model

    International Nuclear Information System (INIS)

    Mendes, Diana A; Mendes, Vivaldo

    2005-01-01

    This paper deals with the control of chaotic economic motion. We show that very complicated dynamics arising, e.g., from an overlapping generations model (OLG) with production and an endogenous intertemporal decision between labour and leisure, which produces chaos, can in fact be controlled with relative simplicity. The aperiodic and very complicated motion that stems from this model can be subject to control by small perturbations in its parameters and turned into a stable steady state or into a regular cycle. Therefore, the system can be controlled without changing of its original properties. To perform the control of the totally unstable equilibrium (both eigenvalues with modulus greater than unity) in this economic model we apply the pole-placement technique, developed by Romeiras, Grebogi, Ott and Dayawansa (1992). The application of control methods to chaotic economic dynamics may raise serious reservations, at least on mathematical and logical grounds, to some recent views on economics which have argued that economic policy becomes useless in the presence of chaotic motion (and thus, that the performance of the economic system cannot be improved by public intervention, i.e., that the amplitude of cycles can not be controlled or reduced). In fact, the fine tuning of the system (that is, the control) can be performed without having to rely only on infinitesimal accuracy in the perturbation to the system, because the control can be performed with larger or smaller perturbations, but neither too large (because these would lead to a different fixed point of the system, therefore modifying its original nature), nor too small because the control becomes too inefficient

  10. Benchmarking Measures of Network Controllability on Canonical Graph Models

    Science.gov (United States)

    Wu-Yan, Elena; Betzel, Richard F.; Tang, Evelyn; Gu, Shi; Pasqualetti, Fabio; Bassett, Danielle S.

    2018-03-01

    The control of networked dynamical systems opens the possibility for new discoveries and therapies in systems biology and neuroscience. Recent theoretical advances provide candidate mechanisms by which a system can be driven from one pre-specified state to another, and computational approaches provide tools to test those mechanisms in real-world systems. Despite already having been applied to study network systems in biology and neuroscience, the practical performance of these tools and associated measures on simple networks with pre-specified structure has yet to be assessed. Here, we study the behavior of four control metrics (global, average, modal, and boundary controllability) on eight canonical graphs (including Erdős-Rényi, regular, small-world, random geometric, Barábasi-Albert preferential attachment, and several modular networks) with different edge weighting schemes (Gaussian, power-law, and two nonparametric distributions from brain networks, as examples of real-world systems). We observe that differences in global controllability across graph models are more salient when edge weight distributions are heavy-tailed as opposed to normal. In contrast, differences in average, modal, and boundary controllability across graph models (as well as across nodes in the graph) are more salient when edge weight distributions are less heavy-tailed. Across graph models and edge weighting schemes, average and modal controllability are negatively correlated with one another across nodes; yet, across graph instances, the relation between average and modal controllability can be positive, negative, or nonsignificant. Collectively, these findings demonstrate that controllability statistics (and their relations) differ across graphs with different topologies and that these differences can be muted or accentuated by differences in the edge weight distributions. More generally, our numerical studies motivate future analytical efforts to better understand the mathematical

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

    DEFF Research Database (Denmark)

    Guo, Yifei; Gao, Houlei; Wu, Qiuwei

    2018-01-01

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

  12. Modeling Human Error Mechanism for Soft Control in Advanced Control Rooms (ACRs)

    International Nuclear Information System (INIS)

    Aljneibi, Hanan Salah Ali; Ha, Jun Su; Kang, Seongkeun; Seong, Poong Hyun

    2015-01-01

    To achieve the switch from conventional analog-based design to digital design in ACRs, a large number of manual operating controls and switches have to be replaced by a few common multi-function devices which is called soft control system. The soft controls in APR-1400 ACRs are classified into safety-grade and non-safety-grade soft controls; each was designed using different and independent input devices in ACRs. The operations using soft controls require operators to perform new tasks which were not necessary in conventional controls such as navigating computerized displays to monitor plant information and control devices. These kinds of computerized displays and soft controls may make operations more convenient but they might cause new types of human error. In this study the human error mechanism during the soft controls is studied and modeled to be used for analysis and enhancement of human performance (or human errors) during NPP operation. The developed model would contribute to a lot of applications to improve human performance (or reduce human errors), HMI designs, and operators' training program in ACRs. The developed model of human error mechanism for the soft control is based on assumptions that a human operator has certain amount of capacity in cognitive resources and if resources required by operating tasks are greater than resources invested by the operator, human error (or poor human performance) is likely to occur (especially in 'slip'); good HMI (Human-machine Interface) design decreases the required resources; operator's skillfulness decreases the required resources; and high vigilance increases the invested resources. In this study the human error mechanism during the soft controls is studied and modeled to be used for analysis and enhancement of human performance (or reduction of human errors) during NPP operation

  13. Modeling Human Error Mechanism for Soft Control in Advanced Control Rooms (ACRs)

    Energy Technology Data Exchange (ETDEWEB)

    Aljneibi, Hanan Salah Ali [Khalifa Univ., Abu Dhabi (United Arab Emirates); Ha, Jun Su; Kang, Seongkeun; Seong, Poong Hyun [KAIST, Daejeon (Korea, Republic of)

    2015-10-15

    To achieve the switch from conventional analog-based design to digital design in ACRs, a large number of manual operating controls and switches have to be replaced by a few common multi-function devices which is called soft control system. The soft controls in APR-1400 ACRs are classified into safety-grade and non-safety-grade soft controls; each was designed using different and independent input devices in ACRs. The operations using soft controls require operators to perform new tasks which were not necessary in conventional controls such as navigating computerized displays to monitor plant information and control devices. These kinds of computerized displays and soft controls may make operations more convenient but they might cause new types of human error. In this study the human error mechanism during the soft controls is studied and modeled to be used for analysis and enhancement of human performance (or human errors) during NPP operation. The developed model would contribute to a lot of applications to improve human performance (or reduce human errors), HMI designs, and operators' training program in ACRs. The developed model of human error mechanism for the soft control is based on assumptions that a human operator has certain amount of capacity in cognitive resources and if resources required by operating tasks are greater than resources invested by the operator, human error (or poor human performance) is likely to occur (especially in 'slip'); good HMI (Human-machine Interface) design decreases the required resources; operator's skillfulness decreases the required resources; and high vigilance increases the invested resources. In this study the human error mechanism during the soft controls is studied and modeled to be used for analysis and enhancement of human performance (or reduction of human errors) during NPP operation.

  14. Modeling, control and optimization of water systems systems engineering methods for control and decision making tasks

    CERN Document Server

    2016-01-01

    This book provides essential background knowledge on the development of model-based real-world solutions in the field of control and decision making for water systems. It presents system engineering methods for modelling surface water and groundwater resources as well as water transportation systems (rivers, channels and pipelines). The models in turn provide information on both the water quantity (flow rates, water levels) of surface water and groundwater and on water quality. In addition, methods for modelling and predicting water demand are described. Sample applications of the models are presented, such as a water allocation decision support system for semi-arid regions, a multiple-criteria control model for run-of-river hydropower plants, and a supply network simulation for public services.

  15. 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.

  16. Modelling of a PMSG Wind Turbine with Autonomous Control

    Directory of Open Access Journals (Sweden)

    Chia-Nan Wang

    2014-01-01

    Full Text Available The aim of this research is to model an autonomous control wind turbine driven permanent magnetic synchronous generator (PMSG which feeds alternating current (AC power to the utility grid. Furthermore, this research also demonstrates the effects and the efficiency of PMSG wind turbine which is integrated by autonomous controllers. In order for well autonomous control, two voltage source inverters are used to control wind turbine connecting with the grid. The generator-side inverter is used to adjust the synchronous generator as well as separating the generator from the grid when necessary. The grid-side inverter controls the power flow between the direct current (DC bus and the AC side. Both of them are oriented control by space vector pulse width modulation (PWM with back-to-back frequency inverter. Moreover, the proportional-integral (PI controller is enhanced to control both of the inverters and the pitch angle of the wind turbine. Maximum power point tracking (MPPT is integrated in generator-side inverter to track the maximum power, when wind speed changes. The simulation results in Matlab Simulink 2012b showing the model have good dynamic and static performance. The maximum power can be tracked and the generator wind turbine can be operated with high efficiency.

  17. Computer Models for IRIS Control System Transient Analysis

    International Nuclear Information System (INIS)

    Gary D Storrick; Bojan Petrovic; Luca Oriani

    2007-01-01

    This report presents results of the Westinghouse work performed under Task 3 of this Financial Assistance Award and it satisfies a Level 2 Milestone for the project. Task 3 of the collaborative effort between ORNL, Brazil and Westinghouse for the International Nuclear Energy Research Initiative entitled 'Development of Advanced Instrumentation and Control for an Integrated Primary System Reactor' focuses on developing computer models for transient analysis. This report summarizes the work performed under Task 3 on developing control system models. The present state of the IRIS plant design--such as the lack of a detailed secondary system or I and C system designs--makes finalizing models impossible at this time. However, this did not prevent making considerable progress. Westinghouse has several working models in use to further the IRIS design. We expect to continue modifying the models to incorporate the latest design information until the final IRIS unit becomes operational. Section 1.2 outlines the scope of this report. Section 2 describes the approaches we are using for non-safety transient models. It describes the need for non-safety transient analysis and the model characteristics needed to support those analyses. Section 3 presents the RELAP5 model. This is the highest-fidelity model used for benchmark evaluations. However, it is prohibitively slow for routine evaluations and additional lower-fidelity models have been developed. Section 4 discusses the current Matlab/Simulink model. This is a low-fidelity, high-speed model used to quickly evaluate and compare competing control and protection concepts. Section 5 describes the Modelica models developed by POLIMI and Westinghouse. The object-oriented Modelica language provides convenient mechanisms for developing models at several levels of detail. We have used this to develop a high-fidelity model for detailed analyses and a faster-running simplified model to help speed the I and C development process. Section

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

    Science.gov (United States)

    Campbell, Stefan F.; Kaneshige, John T.

    2010-01-01

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

  19. A Nonlinear Ship Manoeuvering Model: Identification and adaptive control with experiments for a model ship

    Directory of Open Access Journals (Sweden)

    Roger Skjetne

    2004-01-01

    Full Text Available Complete nonlinear dynamic manoeuvering models of ships, with numerical values, are hard to find in the literature. This paper presents a modeling, identification, and control design where the objective is to manoeuver a ship along desired paths at different velocities. Material from a variety of references have been used to describe the ship model, its difficulties, limitations, and possible simplifications for the purpose of automatic control design. The numerical values of the parameters in the model is identified in towing tests and adaptive manoeuvering experiments for a small ship in a marine control laboratory.

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

    Science.gov (United States)

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

    2017-01-01

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

  1. Internal combustion engines - Modelling, estimation and control issues

    Energy Technology Data Exchange (ETDEWEB)

    Vigild, C.W.

    2001-12-01

    Alternative power-trains have become buzz words in the automotive industry in the recent past. New technologies like Lithium-Ion batteries or fuel cells combined with high efficient electrical motors show promising results. However both technologies are extremely expensive and important questions like 'How are we going to supply fuel-cells with hydrogen in an environmentally friendly way?', 'How are we going to improve the range - and recharging speed - of electrical vehicles?' and 'How will our existing infrastructure cope with such changes?' are still left unanswered. Hence, the internal combustion engine with all its shortcomings is to stay with us for the next many years. What the future will really bring in this area is uncertain, but one thing can be said for sure; the time of the pipe in - pipe out engine concept is over. Modem engines, Diesel or gasoline, have in the recent past been provided with many new technologies to improve both performance and handling and to cope with the tightening emission legislations. However, as new devices are included, the number of control inputs is also gradually increased. Hence, the control matrix dimension has grown to a considerably size, and the typical table and regression based engine calibration procedures currently in use today contain both challenging and time-consuming tasks. One way to improve understanding of engines and provide a more comprehensive picture of the control problem is by use of simplified physical modelling - one of the main thrusts of this dissertation. The application of simplified physical modelling as a foundation for engine estimation and control design is first motivated by two control applications. The control problem concerns Air/Fuel ratio control of Spark Ignition engines. Two different ways of control are presented; one based on. a model based Extended Kalman Filter updated predictor, and one based on robust H {infinity} techniques. Both controllers are

  2. 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....

  3. Model Predictive Control of Wind Turbines using Uncertain LIDAR Measurements

    DEFF Research Database (Denmark)

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

    2013-01-01

    , we simplify state prediction for the MPC. Consequently, the control problem of the nonlinear system is simplified into a quadratic programming. We consider uncertainty in the wind propagation time, which is the traveling time of wind from the LIDAR measurement point to the rotor. An algorithm based......The problem of Model predictive control (MPC) of wind turbines using uncertain LIDAR (LIght Detection And Ranging) measurements is considered. A nonlinear dynamical model of the wind turbine is obtained. We linearize the obtained nonlinear model for different operating points, which are determined...... on wind speed estimation and measurements from the LIDAR is devised to find an estimate of the delay and compensate for it before it is used in the controller. Comparisons between the MPC with error compensation, the MPC without error compensation and an MPC with re-linearization at each sample point...

  4. Explicit Nonlinear Model Predictive Control Theory and Applications

    CERN Document Server

    Grancharova, Alexandra

    2012-01-01

    Nonlinear Model Predictive Control (NMPC) has become the accepted methodology to solve complex control problems related to process industries. The main motivation behind explicit NMPC is that an explicit state feedback law avoids the need for executing a numerical optimization algorithm in real time. The benefits of an explicit solution, in addition to the efficient on-line computations, include also verifiability of the implementation and the possibility to design embedded control systems with low software and hardware complexity. This book considers the multi-parametric Nonlinear Programming (mp-NLP) approaches to explicit approximate NMPC of constrained nonlinear systems, developed by the authors, as well as their applications to various NMPC problem formulations and several case studies. The following types of nonlinear systems are considered, resulting in different NMPC problem formulations: Ø  Nonlinear systems described by first-principles models and nonlinear systems described by black-box models; �...

  5. Economic Model Predictive Control for Smart Energy Systems

    DEFF Research Database (Denmark)

    Halvgaard, Rasmus

    Model Predictive Control (MPC) can be used to control the energy distribution in a Smart Grid with a high share of stochastic energy production from renewable energy sources like wind. Heat pumps for heating residential buildings can exploit the slow heat dynamics of a building to store heat and ...... and hereby shift the heat pump power consumption to periods with both low electricity prices and a high fraction of green energy in the grid.......Model Predictive Control (MPC) can be used to control the energy distribution in a Smart Grid with a high share of stochastic energy production from renewable energy sources like wind. Heat pumps for heating residential buildings can exploit the slow heat dynamics of a building to store heat...

  6. Modelling and control of an upper extremity exoskeleton for rehabilitation

    Science.gov (United States)

    Taha, Zahari; Majeed, Anwar P. P. Abdul; Tze, Mohd Yashim Wong Paul; Abdo Hashem, Mohammed; Mohd Khairuddin, Ismail; Azraai Mohd Razman, Mohd

    2016-02-01

    This paper presents the modelling and control of a two degree of freedom upper extremity exoskeleton for rehabilitation. The Lagrangian formulation was employed to obtain the dynamic modelling of both the anthropometric based human upper limb as well as the exoskeleton that comprises of the upper arm and the forearm. A proportional-derivative (PD) architecture is employed to investigate its efficacy performing a joint task trajectory tracking in performing flexion/extension on the elbow joint as well as the forward adduction/abduction on the shoulder joint. An active force control (AFC) algorithm is also incorporated into the aforementioned controller to examine its effectiveness in compensating disturbances. It was found from the study that the AFC-PD performed well against the disturbances introduced into the system without compromising its tracking performances as compared to the conventional PD control architecture.

  7. Modelling and control of an upper extremity exoskeleton for rehabilitation

    International Nuclear Information System (INIS)

    Taha, Zahari; Majeed, Anwar P.P. Abdul; Tze, Mohd Yashim Wong Paul; Hashem, Mohammed Abdo; Khairuddin, Ismail Mohd; Razman, Mohd Azraai Mohd

    2016-01-01

    This paper presents the modelling and control of a two degree of freedom upper extremity exoskeleton for rehabilitation. The Lagrangian formulation was employed to obtain the dynamic modelling of both the anthropometric based human upper limb as well as the exoskeleton that comprises of the upper arm and the forearm. A proportional-derivative (PD) architecture is employed to investigate its efficacy performing a joint task trajectory tracking in performing flexion/extension on the elbow joint as well as the forward adduction/abduction on the shoulder joint. An active force control (AFC) algorithm is also incorporated into the aforementioned controller to examine its effectiveness in compensating disturbances. It was found from the study that the AFC-PD performed well against the disturbances introduced into the system without compromising its tracking performances as compared to the conventional PD control architecture. (paper)

  8. System Identification, Environmental Modelling, and Control System Design

    CERN Document Server

    Garnier, Hugues

    2012-01-01

    System Identification, Environmetric Modelling, and Control Systems Design is dedicated to Professor Peter Young on the occasion of his seventieth birthday. Professor Young has been a pioneer in systems and control, and over the past 45 years he has influenced many developments in this field. This volume is comprised of a collection of contributions by leading experts in system identification, time-series analysis, environmetric modelling and control system design – modern research in topics that reflect important areas of interest in Professor Young’s research career. Recent theoretical developments in and relevant applications of these areas are explored treating the various subjects broadly and in depth. The authoritative and up-to-date research presented here will be of interest to academic researcher in control and disciplines related to environmental research, particularly those to with water systems. The tutorial style in which many of the contributions are composed also makes the book suitable as ...

  9. Management Model for efficient quality control in new buildings

    Directory of Open Access Journals (Sweden)

    C. E. Rodríguez-Jiménez

    2017-09-01

    Full Text Available The management of the quality control of each building process is usually set up in Spain from different levels of demand. This work tries to obtain a model of reference, to compare the quality control of the building process of a specific product (building, and to be able to evaluate its warranty level. In the quest of this purpose, we take credit of specialized sources and 153 real cases of Quality Control were carefully revised using a multi-judgment method. Applying different techniques to get a specific valuation (impartial of the input parameters through Delphi’s method (17 experts query, whose matrix treatment with the Fuzzy-QFD tool condenses numerical references through a weighted distribution of the selected functions and their corresponding conditioning factors. The model thus obtained (M153 is useful in order to have a quality control reference to meet the expectations of the quality.

  10. Modelling and Identification for Control of Gas Bearings

    DEFF Research Database (Denmark)

    Theisen, Lukas Roy Svane; Niemann, Hans Henrik; Santos, Ilmar

    2015-01-01

    Gas bearings are popular for their high speed capabilities, low friction and clean operation, but suffer from poor damping, which poses challenges for safe operation in presence of disturbances. Enhanced damping can be achieved through active lubrication techniques using feedback control laws....... Such control design requires models with low complexity, able to describe the dominant dynamics from actuator input to sensor output over the relevant range of operation. The mathematical models based on first principles are not easy to obtain, and in many cases, they cannot be directly used for control design...... to industrial rotating machinery with gas bearings and to allow for subsequent control design. The paper shows how piezoelectric actuators in a gas bearing are efficiently used to perturb the gas film for identification over relevant ranges of rotational speed and gas injection pressure. Parameter...

  11. Dynamic Modelling of the DEP Controlled Boiling in a Microchannel

    Science.gov (United States)

    Lackowski, Marcin; Kwidzinski, Roman

    2018-04-01

    The paper presents theoretical analysis of flow dynamics in a heated microchannel in which flow rate may be controlled by dielectrophoretic (DEP) forces. Proposed model equations were derived in terms of lumped parameters characterising the system comprising of DEP controller and the microchannel. In result, an equation for liquid height of rise in the controller was obtained from momentum balances in the two elements of the considered system. In the model, the boiling process in the heated section of microchannel is taken into account through a pressure drop, which is a function of flow rate and uniform heat flux. Presented calculation results show that the DEP forces influence mainly the flow rate in the microchannel. In this way, by proper modulation of voltage applied to the DEP controller, it is possible to lower the frequency of Ledinegg instabilities.

  12. Advanced Issues of Wind Turbine Modelling and Control

    International Nuclear Information System (INIS)

    Simani, Silvio

    2015-01-01

    The motivation for this paper comes from a real need to have an overview about the challenges of modelling and control for very demanding systems, such as wind turbine systems, which require reliability, availability, maintainability, and safety over power conversion efficiency. These issues have begun to stimulate research and development in the wide control community particularly for these installations that need a high degree of “sustainability”. Note that this topic represents a key point mainly for offshore wind turbines with very large rotors, since they are characterised by challenging modelling and control problems, as well as expensive and safety critical maintenance works. In this case, a clear conflict exists between ensuring a high degree of availability and reducing maintenance times, which affect the final energy cost. On the other hand, wind turbines have highly nonlinear dynamics, with a stochastic and uncontrollable driving force as input in the form of wind speed, thus representing an interesting challenge also from the modelling point of view. Suitable control methods can provide a sustainable optimisation of the energy conversion efficiency over wider than normally expected working conditions. Moreover, a proper mathematical description of the wind turbine system should be able to capture the complete behaviour of the process under monitoring, thus providing an important impact on the control design itself. In this way, the control scheme could guarantee prescribed performance, whilst also giving a degree of “tolerance” to possible deviation of characteristic properties or system parameters from standard conditions, if properly included in the wind turbine model itself. The most important developments in advanced controllers for wind turbines are addressed, and open problems in the areas of modelling of wind turbines are also outlined. (paper)

  13. Optimal control of information epidemics modeled as Maki Thompson rumors

    Science.gov (United States)

    Kandhway, Kundan; Kuri, Joy

    2014-12-01

    We model the spread of information in a homogeneously mixed population using the Maki Thompson rumor model. We formulate an optimal control problem, from the perspective of single campaigner, to maximize the spread of information when the campaign budget is fixed. Control signals, such as advertising in the mass media, attempt to convert ignorants and stiflers into spreaders. We show the existence of a solution to the optimal control problem when the campaigning incurs non-linear costs under the isoperimetric budget constraint. The solution employs Pontryagin's Minimum Principle and a modified version of forward backward sweep technique for numerical computation to accommodate the isoperimetric budget constraint. The techniques developed in this paper are general and can be applied to similar optimal control problems in other areas. We have allowed the spreading rate of the information epidemic to vary over the campaign duration to model practical situations when the interest level of the population in the subject of the campaign changes with time. The shape of the optimal control signal is studied for different model parameters and spreading rate profiles. We have also studied the variation of the optimal campaigning costs with respect to various model parameters. Results indicate that, for some model parameters, significant improvements can be achieved by the optimal strategy compared to the static control strategy. The static strategy respects the same budget constraint as the optimal strategy and has a constant value throughout the campaign horizon. This work finds application in election and social awareness campaigns, product advertising, movie promotion and crowdfunding campaigns.

  14. Centralised gaming models: providing optimal gambling behaviour controls

    OpenAIRE

    Griffiths, MD; Wood, RTA

    2009-01-01

    The expansion in the gaming industry and its widening attraction points to the need for ever more verifiable means of controlling problem gambling. Various strategies have been built into casino venue operations to address this, but recently, following a new focus on social responsibility, a group of experts considered the possibilities of a centralised gaming model as a more effective control mechanism for dealing with gambling behaviours.

  15. Multivariable robust adaptive controller using reduced-order model

    Directory of Open Access Journals (Sweden)

    Wei Wang

    1990-04-01

    Full Text Available In this paper a multivariable robust adaptive controller is presented for a plant with bounded disturbances and unmodeled dynamics due to plant-model order mismatches. The robust stability of the closed-loop system is achieved by using the normalization technique and the least squares parameter estimation scheme with dead zones. The weighting polynomial matrices are incorporated into the control law, so that the open-loop unstable or/and nonminimum phase plants can be handled.

  16. A General Model for Repeated Audit Controls Using Monotone Subsampling

    OpenAIRE

    Raats, V.M.; van der Genugten, B.B.; Moors, J.J.A.

    2002-01-01

    In categorical repeated audit controls, fallible auditors classify sample elements in order to estimate the population fraction of elements in certain categories.To take possible misclassifications into account, subsequent checks are performed with a decreasing number of observations.In this paper a model is presented for a general repeated audit control system, where k subsequent auditors classify elements into r categories.Two different sub-sampling procedures will be discussed, named 'stra...

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

    International Nuclear Information System (INIS)

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

    2012-01-01

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

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

    CERN Document Server

    Baranyi, Péter

    2016-01-01

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

  19. Application of model based control to robotic manipulators

    Science.gov (United States)

    Petrosky, Lyman J.; Oppenheim, Irving J.

    1988-01-01

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

  20. Modelling and control system of multi motor conveyor

    Science.gov (United States)

    Kovalchuk, M. S.; Baburin, S. V.

    2018-03-01

    The paper deals with the actual problem of developing the mathematical model of electromechanical system: conveyor – multimotor electric drive with a frequency converter, with the implementation in Simulink/MatLab, which allows one to perform studies of conveyor operation modes, taking into account the specifics of the mechanism with different electric drives control algorithms. The authors designed the mathematical models of the conveyor and its control system that provides increased uniformity of load distribution between drive motors and restriction of dynamic loads on the belt (over-regulation until 15%).

  1. Augmented models for improving vision control of a mobile robot

    DEFF Research Database (Denmark)

    Andersen, Gert Lysgaard; Christensen, Anders C.; Ravn, Ole

    1994-01-01

    obtain good performance even when using standard low cost equipment and a comparatively low sampling rate. The plant model is a compound of kinematic, dynamic and sensor submodels, all integrated into a discrete state space representation. An intelligent strategy is applied for the vision sensor......This paper describes the modelling phases for the design of a path tracking vision controller for a three wheeled mobile robot. It is shown that, by including the dynamic characteristics of vision and encoder sensors and implementing the total system in one multivariable control loop, one can...

  2. Information Modeling for Direct Control of Distributed Energy Resources

    DEFF Research Database (Denmark)

    Biegel, Benjamin; Andersen, Palle; Stoustrup, Jakob

    2013-01-01

    We present an architecture for an unbundled liberalized electricity market system where a virtual power plant (VPP) is able to control a number of distributed energy resources (DERs) directly through a two-way communication link. The aggregator who operates the VPP utilizes the accumulated...... a desired accumulated response. In this paper, we design such an information model based on the markets that the aggregator participates in and based on the flexibility characteristics of the remote controlled DERs. The information model is constructed in a modular manner making the interface suitable...

  3. Mathematical models and lymphatic filariasis control: monitoring and evaluating interventions.

    Science.gov (United States)

    Michael, Edwin; Malecela-Lazaro, Mwele N; Maegga, Bertha T A; Fischer, Peter; Kazura, James W

    2006-11-01

    Monitoring and evaluation are crucially important to the scientific management of any mass parasite control programme. Monitoring enables the effectiveness of implemented actions to be assessed and necessary adaptations to be identified; it also determines when management objectives are achieved. Parasite transmission models can provide a scientific template for informing the optimal design of such monitoring programmes. Here, we illustrate the usefulness of using a model-based approach for monitoring and evaluating anti-parasite interventions and discuss issues that need addressing. We focus on the use of such an approach for the control and/or elimination of the vector-borne parasitic disease, lymphatic filariasis.

  4. Modelling of Rotor-gas bearings for Feedback Controller Design

    DEFF Research Database (Denmark)

    Theisen, Lukas Roy Svane; Niemann, Hans Henrik

    2014-01-01

    Controllable rotor-gas bearings are popular oering adaptability, high speed operation, low friction and clean operation. Rotor-gas bearings are however highly sensitive to disturbances due to the low friction of the injected gas. These undesirable damping properties call for controllers, which ca...... and are shown to accurately describe the dynamical behaviour of the rotor-gas bearing. Design of a controller using the identied models is treated and experiments verify the improvement of the damping properties of the rotor-gas bearing.......Controllable rotor-gas bearings are popular oering adaptability, high speed operation, low friction and clean operation. Rotor-gas bearings are however highly sensitive to disturbances due to the low friction of the injected gas. These undesirable damping properties call for controllers, which can...... be designed from suitable models describing the relation from actuator input to measured shaft position. Current state of the art models of controllable gas bearings however do not provide such relation, which calls for alternative strategies. The present contribution discusses the challenges for feedback...

  5. Model Predictive Control of Integrated Gasification Combined Cycle Power Plants

    Energy Technology Data Exchange (ETDEWEB)

    B. Wayne Bequette; Priyadarshi Mahapatra

    2010-08-31

    The primary project objectives were to understand how the process design of an integrated gasification combined cycle (IGCC) power plant affects the dynamic operability and controllability of the process. Steady-state and dynamic simulation models were developed to predict the process behavior during typical transients that occur in plant operation. Advanced control strategies were developed to improve the ability of the process to follow changes in the power load demand, and to improve performance during transitions between power levels. Another objective of the proposed work was to educate graduate and undergraduate students in the application of process systems and control to coal technology. Educational materials were developed for use in engineering courses to further broaden this exposure to many students. ASPENTECH software was used to perform steady-state and dynamic simulations of an IGCC power plant. Linear systems analysis techniques were used to assess the steady-state and dynamic operability of the power plant under various plant operating conditions. Model predictive control (MPC) strategies were developed to improve the dynamic operation of the power plants. MATLAB and SIMULINK software were used for systems analysis and control system design, and the SIMULINK functionality in ASPEN DYNAMICS was used to test the control strategies on the simulated process. Project funds were used to support a Ph.D. student to receive education and training in coal technology and the application of modeling and simulation techniques.

  6. Model-reference robust tuning of PID controllers

    CERN Document Server

    Alfaro, Victor M

    2016-01-01

    This book presents a unified methodology for the design of PID controllers that encompasses the wide range of different dynamics to be found in industrial processes. This is extended to provide a coherent way of dealing with the tuning of PID controllers. The particular method at the core of the book is the so-called model-reference robust tuning (MoReRT), developed by the authors. MoReRT constitutes a novel and powerful way of thinking of a robust design and taking into account the usual design trade-offs encountered in any control design problem. The book starts by presenting the different two-degree-of-freedom PID control algorithm variations and their conversion relations as well as the indexes used for performance, robustness and fragility evaluation:the bases of the proposed model. Secondly, the MoReRT design methodology and normalized controlled process models and controllers used in the design are described in order to facilitate the formulation of the different design problems and subsequent derivati...

  7. Distributed Model Predictive Control for Active Power Control of Wind Farm

    DEFF Research Database (Denmark)

    Zhao, Haoran; Wu, Qiuwei; Rasmussen, Claus Nygaard

    2014-01-01

    This paper presents the active power control of a wind farm using the Distributed Model Predictive Controller (D- MPC) via dual decomposition. Different from the conventional centralized wind farm control, multiple objectives such as power reference tracking performance and wind turbine load can...... be considered to achieve a trade-off between them. Additionally, D- MPC is based on communication among the subsystems. Through the interaction among the neighboring subsystems, the global optimization could be achieved, which significantly reduces the computation burden. It is suitable for the modern large......-scale wind farm control....

  8. Control system architecture: The standard and non-standard models

    International Nuclear Information System (INIS)

    Thuot, M.E.; Dalesio, L.R.

    1993-01-01

    Control system architecture development has followed the advances in computer technology through mainframes to minicomputers to micros and workstations. This technology advance and increasingly challenging accelerator data acquisition and automation requirements have driven control system architecture development. In summarizing the progress of control system architecture at the last International Conference on Accelerator and Large Experimental Physics Control Systems (ICALEPCS) B. Kuiper asserted that the system architecture issue was resolved and presented a ''standard model''. The ''standard model'' consists of a local area network (Ethernet or FDDI) providing communication between front end microcomputers, connected to the accelerator, and workstations, providing the operator interface and computational support. Although this model represents many present designs, there are exceptions including reflected memory and hierarchical architectures driven by requirements for widely dispersed, large channel count or tightly coupled systems. This paper describes the performance characteristics and features of the ''standard model'' to determine if the requirements of ''non-standard'' architectures can be met. Several possible extensions to the ''standard model'' are suggested including software as well as the hardware architectural feature

  9. Model oriented application generation for industrial control systems

    International Nuclear Information System (INIS)

    Copy, B.; Barillere, R.; Blanco, E.; Fernandez Adiego, B.; Nogueira Fernandes, R.; Prieto Barreiro, I.

    2012-01-01

    The CERN Unified Industrial Control Systems framework (UNICOS) is a software generation methodology and a collection of development tools that standardizes the design of industrial control applications. A Software Factory, named the UNICOS Application Builder (UAB), was introduced to ease extensibility and maintenance of the framework, introducing a stable meta-model, a set of platform-independent models and platform-specific configurations against which code generation plug-ins and configuration generation plug-ins can be written. Such plug-ins currently target PLC programming environments (Schneider and SIEMENS PLCs) as well as SIEMENS WinCC Open Architecture SCADA (previously known as ETM PVSS) but are being expanded to cover more and more aspects of process control systems. We present what constitutes the UNICOS meta-model and the models in use, how these models can be used to capture knowledge about industrial control systems and how this knowledge can be used to generate both code and configuration for a variety of target usages. (authors)

  10. Models for integrated pest control and their biological implications.

    Science.gov (United States)

    Tang, Sanyi; Cheke, Robert A

    2008-09-01

    Successful integrated pest management (IPM) control programmes depend on many factors which include host-parasitoid ratios, starting densities, timings of parasitoid releases, dosages and timings of insecticide applications and levels of host-feeding and parasitism. Mathematical models can help us to clarify and predict the effects of such factors on the stability of host-parasitoid systems, which we illustrate here by extending the classical continuous and discrete host-parasitoid models to include an IPM control programme. The results indicate that one of three control methods can maintain the host level below the economic threshold (ET) in relation to different ET levels, initial densities of host and parasitoid populations and host-parasitoid ratios. The effects of host intrinsic growth rate and parasitoid searching efficiency on host mean outbreak period can be calculated numerically from the models presented. The instantaneous pest killing rate of an insecticide application is also estimated from the models. The results imply that the modelling methods described can help in the design of appropriate control strategies and assist management decision-making. The results also indicate that a high initial density of parasitoids (such as in inundative releases) and high parasitoid inter-generational survival rates will lead to more frequent host outbreaks and, therefore, greater economic damage. The biological implications of this counter intuitive result are discussed.

  11. Model calibration and beam control systems for storage rings

    International Nuclear Information System (INIS)

    Corbett, W.J.; Lee, M.J.; Ziemann, V.

    1993-04-01

    Electron beam storage rings and linear accelerators are rapidly gaining worldwide popularity as scientific devices for the production of high-brightness synchrotron radiation. Today, everybody agrees that there is a premium on calibrating the storage ring model and determining errors in the machine as soon as possible after the beam is injected. In addition, the accurate optics model enables machine operators to predictably adjust key performance parameters, and allows reliable identification of new errors that occur during operation of the machine. Since the need for model calibration and beam control systems is common to all storage rings, software packages should be made that are portable between different machines. In this paper, we report on work directed toward achieving in-situ calibration of the optics model, detection of alignment errors, and orbit control techniques, with an emphasis on developing a portable system incorporating these tools

  12. An optimal control model of crop thinning in viticulture

    Directory of Open Access Journals (Sweden)

    Schamel Guenter H.

    2016-01-01

    Full Text Available We develop an economic model of cluster thinning in viticulture to control for grape quantity harvested and grape quality, applying a simple optimal control model with the aim to raise grape quality and related economic profits. The model maximizes vineyard owner profits and allows to discuss two relevant scenarios using a phase diagram analysis: (1 when the initial grape quantity is sufficiently small, thinning grapes will not be optimal and (2 when the initial grape quantity is high enough, it is optimal to thin grapes from the beginning of the relevant planning horizon and to reduce the quantity over time until the stock of grapes arrives at its optimum. Depending on the model's parameters, the “stopping time” for thinning grapes is reached sooner or later. After the stopping time, grape quantity evolves solely according to natural decay. The results relate to observed dynamics in viticulture and for other horticultural crops.

  13. Modelling and control design for SHARON/Anammox reactor sequence

    DEFF Research Database (Denmark)

    Valverde Perez, Borja; Mauricio Iglesias, Miguel; Sin, Gürkan

    2012-01-01

    metabolism against fast chemical reaction and mass transfer. Likewise, the analysis of the dynamics contributed to establish qualitatively the requirements for control of the reactors, both for regulation and for optimal operation. Work in progress on quantitatively analysing different control structure......With the perspective of investigating a suitable control design for autotrophic nitrogen removal, this work presents a complete model of the SHARON/Anammox reactor sequence. The dynamics of the reactor were explored pointing out the different scales of the rates in the system: slow microbial...

  14. Time dependent optimal switching controls in online selling models

    Energy Technology Data Exchange (ETDEWEB)

    Bradonjic, Milan [Los Alamos National Laboratory; Cohen, Albert [MICHIGAN STATE UNIV

    2010-01-01

    We present a method to incorporate dishonesty in online selling via a stochastic optimal control problem. In our framework, the seller wishes to maximize her average wealth level W at a fixed time T of her choosing. The corresponding Hamilton-Jacobi-Bellmann (HJB) equation is analyzed for a basic case. For more general models, the admissible control set is restricted to a jump process that switches between extreme values. We propose a new approach, where the optimal control problem is reduced to a multivariable optimization problem.

  15. Theoretical model for ultracold molecule formation via adaptive feedback control

    OpenAIRE

    Poschinger, Ulrich; Salzmann, Wenzel; Wester, Roland; Weidemueller, Matthias; Koch, Christiane P.; Kosloff, Ronnie

    2006-01-01

    We investigate pump-dump photoassociation of ultracold molecules with amplitude- and phase-modulated femtosecond laser pulses. For this purpose a perturbative model for the light-matter interaction is developed and combined with a genetic algorithm for adaptive feedback control of the laser pulse shapes. The model is applied to the formation of 85Rb2 molecules in a magneto-optical trap. We find for optimized pulse shapes an improvement for the formation of ground state molecules by more than ...

  16. A mathematical model for incorporating biofeedback into human postural control

    Directory of Open Access Journals (Sweden)

    Ersal Tulga

    2013-02-01

    Full Text Available Abstract Background Biofeedback of body motion can serve as a balance aid and rehabilitation tool. To date, mathematical models considering the integration of biofeedback into postural control have represented this integration as a sensory addition and limited their application to a single degree-of-freedom representation of the body. This study has two objectives: 1 to develop a scalable method for incorporating biofeedback into postural control that is independent of the model’s degrees of freedom, how it handles sensory integration, and the modeling of its postural controller; and 2 to validate this new model using multidirectional perturbation experimental results. Methods Biofeedback was modeled as an additional torque to the postural controller torque. For validation, this biofeedback modeling approach was applied to a vibrotactile biofeedback device and incorporated into a two-link multibody model with full-state-feedback control that represents the dynamics of bipedal stance. Average response trajectories of body sway and center of pressure (COP to multidirectional surface perturbations of subjects with vestibular deficits were used for model parameterization and validation in multiple perturbation directions and for multiple display resolutions. The quality of fit was quantified using average error and cross-correlation values. Results The mean of the average errors across all tactor configurations and perturbations was 0.24° for body sway and 0.39 cm for COP. The mean of the cross-correlation value was 0.97 for both body sway and COP. Conclusions The biofeedback model developed in this study is capable of capturing experimental response trajectory shapes with low average errors and high cross-correlation values in both the anterior-posterior and medial-lateral directions for all perturbation directions and spatial resolution display configurations considered. The results validate that biofeedback can be modeled as an additional

  17. A mathematical model for incorporating biofeedback into human postural control

    Science.gov (United States)

    2013-01-01

    Background Biofeedback of body motion can serve as a balance aid and rehabilitation tool. To date, mathematical models considering the integration of biofeedback into postural control have represented this integration as a sensory addition and limited their application to a single degree-of-freedom representation of the body. This study has two objectives: 1) to develop a scalable method for incorporating biofeedback into postural control that is independent of the model’s degrees of freedom, how it handles sensory integration, and the modeling of its postural controller; and 2) to validate this new model using multidirectional perturbation experimental results. Methods Biofeedback was modeled as an additional torque to the postural controller torque. For validation, this biofeedback modeling approach was applied to a vibrotactile biofeedback device and incorporated into a two-link multibody model with full-state-feedback control that represents the dynamics of bipedal stance. Average response trajectories of body sway and center of pressure (COP) to multidirectional surface perturbations of subjects with vestibular deficits were used for model parameterization and validation in multiple perturbation directions and for multiple display resolutions. The quality of fit was quantified using average error and cross-correlation values. Results The mean of the average errors across all tactor configurations and perturbations was 0.24° for body sway and 0.39 cm for COP. The mean of the cross-correlation value was 0.97 for both body sway and COP. Conclusions The biofeedback model developed in this study is capable of capturing experimental response trajectory shapes with low average errors and high cross-correlation values in both the anterior-posterior and medial-lateral directions for all perturbation directions and spatial resolution display configurations considered. The results validate that biofeedback can be modeled as an additional torque to the postural

  18. Modeling and control of a gravity gradient stabilised satellite

    Directory of Open Access Journals (Sweden)

    Aage Skullestad

    1999-01-01

    Full Text Available This paper describes attitude control, i.e., 3-axes stabilisation and pointing, of a proposed Norwegian small gravity gradient stabilized satellite to be launched into low earth orbit. Generally, a gravity gradient stabilised system has limited stability and pointing capabilities, and wheels and/or magnetic coils are added in order to improve the attitude control. The best attitude accuracy is achieved using wheels, which can give accuracies down to less than one degree, but wheels increase the complexity and cost of the satellite. Magnetic coils allow cheaper satellites, and are an attractive solution to small, inexpensive satellites in low earth orbits and may provide an attitude control accuracy of a few degrees. Scientific measurements often require accurate attitude control in one or two axes only. Combining wheel and coil control may, in these cases, provide the best solutions. The simulation results are based on a linearised mathematical model of the satellite.

  19. Model predictive control of room temperature with disturbance compensation

    Science.gov (United States)

    Kurilla, Jozef; Hubinský, Peter

    2017-08-01

    This paper deals with temperature control of multivariable system of office building. The system is simplified to several single input-single output systems by decoupling their mutual linkages, which are separately controlled by regulator based on generalized model predictive control. Main part of this paper focuses on the accuracy of the office temperature with respect to occupancy profile and effect of disturbance. Shifting of desired temperature and changing of weighting coefficients are used to achieve the desired accuracy of regulation. The final structure of regulation joins advantages of distributed computing power and possibility to use network communication between individual controllers to consider the constraints. The advantage of using decoupled MPC controllers compared to conventional PID regulators is demonstrated in a simulation study.

  20. Engineering models and methods for industrial cell control

    DEFF Research Database (Denmark)

    Lynggaard, Hans Jørgen Birk; Alting, Leo

    1997-01-01

    This paper is concerned with the engineering, i.e. the designing and making, of industrial cell control systems. The focus is on automated robot welding cells in the shipbuilding industry. The industrial research project defines models and methods for design and implemen-tation of computer based...... SHIPYARD.It is concluded that cell control technology provides for increased performance in production systems, and that the Cell Control Engineering concept reduces the effort for providing and operating high quality and high functionality cell control solutions for the industry....... control and monitor-ing systems for production cells. The project participants are The Danish Academy of Technical Sciences, the Institute of Manufacturing Engineering at the Technical University of Denmark and ODENSE STEEL SHIPYARD Ltd.The manufacturing environment and the current practice...