This paper presents a model predictive control approach to discretetime linear parameter varying systems based on a recurrent neural network. Instead, the adaptive mpc controller block uses a lineartimevarying kalman filter ltvkf. 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. The book has an interdisciplinary character by emphasizing techniques that can. Model predictive control for linear parametervarying inputoutput models.
Over the past few years significant progress has been achieved in the field of nonlinear model predictive control nmpc, also referred to as receding horizon control or moving horizon control. Multiobjective predictive control optimization with varying term objectives. Model predictive control for linear parameter varying systems using pathdependent lyapunov functions marc jungers rodrigo p. The residuals, the differences between the actual and predicted outputs, serve as the feedback signal to a.
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. We propose a model predictive control approach for nonlinear systems based on linear parametervarying representations. Tubebased model predictive control for linear parameter. Part of the lecture notes in computer science book series lncs, volume 8890. Model predictive control for linear parameter varying. Consider a mpc algorithm for a linear plan with constraints. Xwe introduce a nonempty control constraint set ux. A linearparametervarying lpv model with normbounded uncertainties is obtained.
The framework of linear parameter varying lpv systems concerns linear dynamical. 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. Abstractin this article, a synthesis approach for robust model predictive control using linear matrix inequalities is presented. 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. Anticipative model predictive control for linear parametervarying systems. This book provides an introduction to the analysis and control of linear parametervarying systems and timedelay systems and their interactions. 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. Constrained freeway traffic control via linear parameter varying paradigms. A linear parametervarying lpv system is a linear statespace model whose dynamics vary as a function of certain timevarying parameters called scheduling parameters. This control package accepts linear or nonlinear models. This process is experimental and the keywords may be updated as the learning algorithm improves. Stabilizing nonlinear mpc using linear parametervarying. Stabilizing tubebased model predictive control for.
Explicit model predictive control for linear parameter. Caruntu 4, ricardo cajo 1,2,5, mihaela ghita 1,2, guillaume crevecoeur 2,6 and cosmin copot 7. Unesco eolss sample chapters control systems, robotics and automation vol. The main result of the chapter shows that this controller is nearly optimal provided that a certain finite horizon problem can be solved online. Robust model predictive control of linear timevarying. These reasons have motivated the many efforts devoted to develop mpc algorithms robust with respect to unknown, but bounded.
Supervised gainscheduling multimodel versus linear. Anticipative model predictive control for linear parameter varying systems hanema, j. Model predictive control with linear models muske 1993. Model predictive control of nonlinear parameter varying systems via receding horizon control lyapunov functions, m. Model predictive control of linear parameter varying systems. The book is of interest as an introduction to model predictive control, and a merit is the special presentation, connecting the subject intimately with. 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. Anticipative model predictive control for linear parameter. Autonomous racing using linear parameter varyingmodel. In practical control systems, the plant states are not always measurable, so state estimation becomes essential before the state feedback control is applied. By default, the block estimates its prediction model states. Model predictive control for linear parameter varying systems using a new parameter dependent terminal weighting matrix. 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. In order to track the system reference, a generalized proportionalintegral pi control law is proposed.
More than 250 papers have been published in 2006 in isi journals. 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. In this paper, we propose a method for synthesizing a model predictive control mpc law for linear parameter varying lpv systems. 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.
Using largescale nonlinear programming solvers such as apopt and ipopt, it solves data reconciliation, moving horizon estimation, realtime optimization, dynamic simulation, and. Model predictive control for linear parameter varying systems using. Offline robust constrained mpc for linear timevarying. 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. Recurrent neural network model predictive control linear parameter varying. Risk adjusted receding horizon control of constrained. Modeling, dynamics and control of electrified vehicles. Identification of lowcomplexity lpv inputoutput models for control of a turbocharged combustion engines.
This information is used to construct state tubes to which the future trajectories of the state are confined. A new datadriven predictive control method based on subspace identification for continuoustime linear parameter varying lpv systems is presented in this paper. Robust linear parameter varying model predictive control. Model predictive controllers rely on dynamic models of. Robust linear parameter varying model predictive control and its. Mpc model predictive control also known as dmc dynamical matrix control. Model predictive control of linear parameter varying. Explicit model predictive control for linear parameter varying systems abstract.
Output feedback and tracking of nonlinear systems, l. 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. This article discusses the existing linear model predictive control concepts in a unified theoretical framework based on a stabilizing, infinite horizon, linear quadratic regulator. In order to represent unstable as well as stable multivariable systems, the standard. In this paper, a model predictive control mpc algorithm for linear parameter varying lpv systems is proposed. Model predictive control mpc is nowadays a standard in many industrial contexts, see e. Anticipative model predictive control for linear parametervarying systems citation for published version apa. See adaptive mpc control of nonlinear chemical reactor using linear parametervarying system for more details. Analysis and control of linear parametervarying systems. Model predictive control of nonlinear parameter varying. In this work, we propose the linear parameter varyingmodel predictive control lpvmpc approach as a novel option to solve the driving control problem. 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.
An offline robust constrained model predictive control mpc algorithm for linear timevarying ltv systems is developed. Toth, r modeling and identification of linear parametervarying systems. A novel freeway traffic control design framework is proposed in the chapter. Linear parametervarying model of an electrohydraulic. A block diagram of a model predictive control system is shown in fig. 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.
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. Adaptive mpc control of nonlinear chemical reactor using. 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. The proposed controller relies on the constraint tightening method to guarantee that the mpcs optimization problem remains feasible in the presence of additive disturbances. By running closedloop simulations, you can evaluate controller performance. 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. This paper is concerned with the design of model predictive control mpc for linear parameter varying lpv discretetime systems. 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. 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. In this paper, we consider output feedback model predictive control mpc for linear parameter varying lpv systems with input constraints.
In recent years it has also been used in power system balancing models and in power electronics. Model predictive control mpc predicts and optimizes timevarying processes over a future time horizon. Model predictive control advanced textbooks in 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.
Since the prediction model parameters change at run time, the static kalman filter used in the mpc controller block is inappropriate. Receding horizon control for linear periodic timevarying systems subject to input constraints. Linear parametervarying models what are linear parametervarying models. In order to reduce the online computational burdens, a sequence of explicit control laws corresponding to a.
Multiobjective predictive control optimization with. Model predictive control mpc is an advanced method of process control that is used to control a process while satisfying a set of constraints. Linear parametervarying and timedelay systems ebook by. Control of linear parameter varying systems compiles stateoftheart contributions on novel analytical and computational methods for addressing system identification, model reduction, performance. The purpose is to give the readers some fundamental theoretical background on these topics and to give more insights on the possible applications of.
Such a linear timevarying ltv model is useful when controlling periodic systems or nonlinear systems that are linearized around a timevarying nominal trajectory. With the exception of other approaches based on model predictive control. Output feedback model predictive control of linear. A novel feature is the fact that both model uncertainty and bounded. Explicit model predictive control for systems with linear. It has been in use in the process industries in chemical plants and oil refineries since the 1980s. 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. A predictive envelope protection system using linear. 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. The first step is derived by using parameterdependent lyapunov function and the second step is derived by. Stochastic linear model predictive control with chance.
Anticipative model predictive control for linear parametervarying. 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. Anticipative model predictive control for linear parameter varying. 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. 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. 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. An lpv approach andrea corti and marco lovera modeling and control of lpv systems. Control of linear parameter varying systems with applications. Simulate adaptive and timevarying model predictive. Linearparametervarying model predictive control for multiregion traffic systems.
Linearparametervarying model predictive control for. 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. To this end, we introduce a nonempty state con straint set x. 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. The toolbox lets you specify plant and disturbance models, horizons, constraints, and weights.