Caruntu 4, ricardo cajo 1,2,5, mihaela ghita 1,2, guillaume crevecoeur 2,6 and cosmin copot 7. Model predictive control for linear parametervarying inputoutput models. Output feedback model predictive control of linear. In this paper we demonstrate how one can reformulate the mpc problem for lpv systems to a series of mplps by a closedloop minimax mpc algorithm based on dynamic programming. In order to reduce the online computational burdens, a sequence of explicit control laws corresponding to a. Anticipative model predictive control for linear parameter varying systems hanema, j. A novel freeway traffic control design framework is proposed in the chapter.
Explicit model predictive control for systems with linear parametervarying state transition matrix thomas besselmann johan lo fberg manfred morari automatic control laboratory, eth zurich, zurich, switzer land, email. Offline robust constrained mpc for linear timevarying. Xwe introduce a nonempty control constraint set ux. In recent years it has also been used in power system balancing models and in power electronics. A parametervarying, modelpredictive envelope protection system is developed simplifying the controller structures required to keep the aircraft within a safe angleofattack and normal load factor envelope. A new datadriven predictive control method based on subspace identification for continuoustime linear parameter varying lpv systems is presented in this paper.
Stabilizing nonlinear mpc using linear parametervarying. This article discusses the existing linear model predictive control concepts in a unified theoretical framework based on a stabilizing, infinite horizon, linear quadratic regulator. The purpose is to give the readers some fundamental theoretical background on these topics and to give more insights on the possible applications of. An offline robust constrained model predictive control mpc algorithm for linear timevarying ltv systems is developed. Model predictive control stable equilibrium point linear parameter vary recede horizon control parameter trajectory these keywords were added by machine and not by the authors. Control of linear parameter varying systems with applications compiles stateoftheart contributions on novel analytical and computational methods to address system modeling and identification, complexity reduction, performance analysis and control design for timevarying and nonlinear systems in the lpv framework.
This process is experimental and the keywords may be updated as the learning algorithm improves. Model predictive control for linear parameter varying. An lpv approach andrea corti and marco lovera modeling and control of lpv systems. Since the prediction model parameters change at run time, the static kalman filter used in the mpc controller block is inappropriate.
Model predictive control for linear parameter varying systems using a new parameter dependent terminal weighting matrix. Robust linear parameter varying model predictive control. Control of linear parameter varying systems with applications compiles stateoftheart contributions on novel analytical and computational methods to address system modeling and identification, complexity reduction, performance analysis and control design for timevarying and nonlinear systems in. Output feedback and tracking of nonlinear systems, l. Stabilizing tubebased model predictive control for. Linear parametervarying control deals with the control of linear parametervarying systems, a class of nonlinear systems which can be modelled as parametrized linear systems whose parameters change with their state. Recurrent neural network model predictive control linear parameter varying. In control engineering, a state space representation is a mathematical model of a physical system as a set of input, output, and state variables, related by. Anticipative model predictive control for linear parameter varying. The residuals, the differences between the actual and predicted outputs, serve as the feedback signal to a.
Model predictive control for linear parameter varying systems using. Anticipative model predictive control for linear parametervarying systems. Modeling, dynamics and control of electrified vehicles. Such a linear timevarying ltv model is useful when controlling periodic systems or nonlinear systems that are linearized around a timevarying nominal trajectory. The main result of the chapter shows that this controller is nearly optimal provided that a certain finite horizon problem can be solved online. Toth, r modeling and identification of linear parametervarying systems. Robust linear parameter varying model predictive control and its. Model predictive control for linear parameter varying systems using pathdependent lyapunov functions marc jungers rodrigo p. Explicit model predictive control for systems with linear. Part of the lecture notes in computer science book series lncs, volume 8890.
By default, the block estimates its prediction model states. Model constraints stagewise cost terminal cost openloop optimal control problem openloop optimal solution is not robust must be coupled with online state model parameter update requires online solution for each updated problem analytical solution possible only in a few cases lq control. To this end, we introduce a nonempty state con straint set x. Anticipative model predictive control for linear parametervarying. The book has an interdisciplinary character by emphasizing techniques that can. Instead, the adaptive mpc controller block uses a lineartimevarying kalman filter ltvkf.
In this work, we propose the linear parameter varyingmodel predictive control lpvmpc approach as a novel option to solve the driving control problem. Robust model predictive control of linear timevarying. A process model is used to predict the current values of the output variables. This paper proposes a robust model predictive controller for linear parameter varying lpv systems subject to additive disturbances. At run time, use adaptive mpc controller block updating predictive model at each control interval together with linear parameter varying lpv system block supplying linear plant model with a scheduling strategy. Adaptive mpc control of nonlinear chemical reactor using. Linear parametervarying and timedelay systems ebook by. Abstractin this article, a synthesis approach for robust model predictive control using linear matrix inequalities is presented. Anticipative model predictive control for linear parametervarying systems citation for published version apa. Model predictive control of nonlinear parameter varying systems via receding horizon control lyapunov functions, m. Model predictive control mpc predicts and optimizes timevarying processes over a future time horizon. Control of linear parameter varying systems with applications. A predictive envelope protection system using linear.
Model predictive control mpc is an advanced method of process control that is used to control a process while satisfying a set of constraints. Model predictive control advanced textbooks in control. The book is of interest as an introduction to model predictive control, and a merit is the special presentation, connecting the subject intimately with. Linearparametervarying model predictive control for. The proposed controller relies on the constraint tightening method to guarantee that the mpcs optimization problem remains feasible in the presence of additive disturbances. We propose a model predictive control approach for nonlinear systems based on linear parametervarying representations.
With the exception of other approaches based on model predictive control. Linear parametervarying models what are linear parametervarying models. These reasons have motivated the many efforts devoted to develop mpc algorithms robust with respect to unknown, but bounded. This information is used to construct state tubes to which the future trajectories of the state are confined. Control of linear parameter varying systems compiles stateoftheart contributions on novel analytical and computational methods for addressing system identification, model reduction, performance analysis and feedback control design and addresses address theoretical developments, novel computational approaches and illustrative applications to various fields. The first step is derived by using parameter dependent lyapunov function and the second step is derived by using the perturbation on control input strategy. Since it is difficult to get the analytic solution for the pi gains, an augmented system is developed and the pi control is then converted into the state. Unesco eolss sample chapters control systems, robotics and automation vol. This book provides an introduction to the analysis and control of linear parametervarying systems and timedelay systems and their interactions. Model predictive controllers rely on dynamic models of. Multiobjective predictive control optimization with varying term objectives. In this chapter we propose a suboptimal regulator for nonlinear parameter varying, control affine systems based upon the combination of model predictive and control lyapunov function techniques.
This paper introduces a tubebased model predictive control mpc for linear parametervarying lpv systems which exploits knowledge about bounds on the parameters rate of change to extrapolate its admissible values over the prediction horizon. By running closedloop simulations, you can evaluate controller performance. Model predictive control mpc is nowadays a standard in many industrial contexts, see e. Uncertain timevarying parameters and bounded additive disturbances are explicitly taken into account in the controller design. A novel feature is the fact that both model uncertainty and bounded. A linearparametervarying lpv model with normbounded uncertainties is obtained. Consider a mpc algorithm for a linear plan with constraints. This article considers robust model predictive control mpc schemes for linear parameter varying lpv systems in which the time varying parameter is assumed to be measured online and exploited. Mpc model predictive control also known as dmc dynamical matrix control. In order to represent unstable as well as stable multivariable systems, the standard. Receding horizon control for linear periodic timevarying systems subject to input constraints. The first step is derived by using parameterdependent lyapunov function and the second step is derived by.
See adaptive mpc control of nonlinear chemical reactor using linear parametervarying system for more details. Model predictive control of linear parameter varying. The toolbox lets you specify plant and disturbance models, horizons, constraints, and weights. A linear parametervarying lpv system is a linear statespace model whose dynamics vary as a function of certain timevarying parameters called scheduling parameters. This text is an introduction to model predictive control, a control methodology which has encountered some success in industry, but which still presents many theoretical challenges. Anticipative model predictive control for linear parameter. Risk adjusted receding horizon control of constrained. Stochastic linear model predictive control with chance. If you can predict how the plant and nominal conditions vary in the future, you can use timevarying mpc to specify a model that changes over the prediction horizon.
Identification of lowcomplexity lpv inputoutput models for control of a turbocharged combustion engines. This paper is concerned with the design of model predictive control mpc for linear parameter varying lpv discretetime systems. It has been in use in the process industries in chemical plants and oil refineries since the 1980s. Autonomous racing using linear parameter varyingmodel. Linear parametervarying model of an electrohydraulic. Constrained freeway traffic control via linear parameter varying paradigms. Simulate adaptive and timevarying model predictive. Model predictive control of linear parameter varying systems. New methods for computing the terminal cost for minmax model predictive control. A novel feature is the fact that both model uncertainty and bounded additive disturbance are explicitly taken into account in the offline formulation of mpc. In this paper, two internal model control imc controllers using gainscheduling techniques are proposed and compared for openchannel systems that allow to deal with large operating conditions. In practical control systems, the plant states are not always measurable, so state estimation becomes essential before the state feedback control is applied. This article considers robust model predictive control mpc schemes for linear parameter varying lpv systems in which the timevarying parameter is assumed to be measured online and exploited.
In this paper, we consider output feedback model predictive control mpc for linear parameter varying lpv systems with input constraints. Multiobjective predictive control optimization with. Control of linear parameter varying systems compiles stateoftheart contributions on novel analytical and computational methods for addressing system identification, model reduction, performance. The authors perform a comparison against the corresponding nonlinear mpc version showing the promising results of the lpv technique. The model predictive control problem is formulated as a sequential convex optimization, and it is solved by using a recurrent neural network in real time. A block diagram of a model predictive control system is shown in fig. In this paper, we propose a method for synthesizing a model predictive control mpc law for linear parameter varying lpv systems. More than 250 papers have been published in 2006 in isi journals. In particular, in one side, a linear parameter varying lpv model for an openflow channel system based on a secondorder delay hayami model is proposed. The framework of linear parameter varying lpv systems concerns linear dynamical. Explicit model predictive control for linear parameter varying systems abstract.
This control package accepts linear or nonlinear models. Using largescale nonlinear programming solvers such as apopt and ipopt, it solves data reconciliation, moving horizon estimation, realtime optimization, dynamic simulation, and. Tubebased model predictive control for linear parameter. Model predictive control with linear models muske 1993. Recent applications of lpv methods in control of complex systems structured linear parameter varying control of wind turbines fabiano daher adegas, christoffer sloth and jakob stoustrup attitude regulation for spacecraft with magnetic actuators. In order to track the system reference, a generalized proportionalintegral pi control law is proposed. This paper presents a novel linear parametervarying lpv model of an electrohydraulic variable valve actuator ehvva for internal combustion engines that is capable of continuously varying valve timing with duallift. Supervised gainscheduling multimodel versus linear. Linearparametervarying model predictive control for multiregion traffic systems. Explicit model predictive control for linear parametervarying systems conference paper pdf available in proceedings of the ieee conference on decision and control january 2009 with 119 reads. In this paper, a model predictive control mpc algorithm for linear parameter varying lpv systems is proposed. Explicit model predictive control for linear parameter.
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