Pdf wind turbine control based on a modified model. The polytopic linear parameter varying model is established using tensorproduct modeling method, and tube model predictive control controller is designed to satisfy all vertices of the polytopic linear parameter varying model. Datadriven predictive control for continuoustime linear. International journal of advanced polytopic linear. Control engineering 1418 linear mpc nonlinearity is caused by the constraints if constraints are inactive, the qp problem solution is u q.
Model predictive control for linear parameter varying systems using. If the above equation of parameter dependent system is linear in time then it is called linear parameter dependent systems. Offline robust constrained mpc for linear timevarying. Pdf polytopic linear parameter varying modelbased tube. Firstly, the nominal model predictive control law is. 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 practical control systems, the plant states are not always measurable, so state estimation becomes essential before the state feedback control is applied. This study presents a successful application of a model predictive control mpc design approach based on linear parameter varying lpv models subject to inputoutput constraints to control a. International journal of advanced polytopic linear parameter. Index termslinear matrix inequality lmi, linear parameter varying lpv system, model predictive control mpc, parameter dependent lyapunov function. Anticipative model predictive control for linear parameter varying.
Pdf robust shrinking ellipsoid model predictive control. The use of linear parameter varying lpv prediction models has been proven to be an effective solution to develop model predictive control mpc algorithms for linear and nonlinear systems. Abstractwe propose a model predictive control approach for nonlinear systems based on linear parametervarying representations. The adaptive mpc controller then uses the lpv system to update the internal predictive model at each control interval and achieves nonlinear control successfully. Blending approach of linear parameter varying control synthesis for f. The proposed controller relies on the constraint tightening method to guarantee that the mpcs optimization problem remains feasible in the presence of additive disturbances. Johansen abstract nonlinear model predictive control and moving horizon estimation are related methods since both are based on the concept of solving an optimization problem that involves a. Linear parametervarying models what are linear parametervarying models. Pdf explicit model predictive control for linear parameter. Autonomous racing using linear parameter varyingmodel.
The polytopic linear parameter varying model is established using tensorproduct modeling method, and tubemodel predictive control controller is designed to satisfy all vertices of the polytopic. A new datadriven predictive control method based on subspace identification for continuoustime linear parameter varying lpv systems is presented in this paper. This paper presents a new approach to solving linear and nonlinear model predictive control mpc problems that requires minimal memory footprint and throughput and is particularly suitable when the model andor controller parameters change at runtime. Pdf robust shrinking ellipsoid model predictive control for. Computationally efficient model predictive control for a. Pdf wind turbine control based on a modified model predictive. This paper describes a new robust model predictive control mpc scheme to control the discretetime linear parameter varying inputoutput models subject to input and output constraints. Model predictive control for linear parameter varying systems. Model predictive control linear convex optimal control. A linear parameter varying lpv system consisting of three linear plant models is constructed offline to describe the local plant dynamics across the operating range.
Linear parameter varying lpv systems are a particular class of nonlinear systems which can be thought of as varyingsystems, for which the variation depends explicitly on a time varying parameter referred to as the scheduling or weight sequence 12. This paper describes a new robust model predictive control mpc scheme to control the discretetime linear parametervarying inputoutput models subject to input and output constraints. Model predictive control, linear parameter varying, nonlinear systems, wind turbines. The problem above is based on a single linear model of the plant around one operating point.
Summary this paper describes a new robust model predictive control mpc scheme to control the discrete. Pdf an efficient noncondensed approach for linear and. In this paper, we consider output feedback model predictive control mpc for linear parameter varying lpv systems with input constraints. 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. Robust linear parameter varying model predictive control. It is developed by reformulating the continuoustime lpv system which utilizes laguerre filters to obtain the subspace prediction of output. An improved robust model predictive control for linear parametervarying inputoutput models. Adaptive model predictive control of multivariable time. Linearparametervarying model predictive control for. To incorporate good longrange prediction capability with respect to manipulated. Variations on optimal control problem time varying costs, dynamics, constraints discounted cost. First, the equality constraints given by the model equations are not.
The system array size is equal to the grid size in scheduling space. Must be coupled with online state model parameter update. This paper presents a model predictive control approach to discretetime linear parameter varying systems based on a recurrent neural network. Chapter 3 nonlinear model predictive control in this chapter, we introduce the nonlinear model predictive control algorithm in a rigorous way. Control of linear parameter varying systems with applications. For more information on model arrays, see model arrays. The subspace predictors are derived by qr decomposition of inputoutput and. An improved robust model predictive control for linear parameter. Model predictive control based on lpv models with parametervarying delays fatemeh karimi pour, vicenc. In this paper we propose a closedloop minmax mpc algorithm based on dynamic programming, to compute explicit control laws for systems with a linear parametervarying state transition matrix. Closedloop asymptotic stability is guaranteed by including a quadratic terminal cost and an ellipsoidal terminal set. This study presents a successful application of a model predictive control mpc design approach based on linear parametervarying lpv models subject to inputoutput constraints to control a.
Pdf an ellipsoidal offline model predictive control. To adapt to changing operating conditions, adaptive mpc supports updating the prediction model and its associated nominal conditions at each control interval. Use model arrays to create linear parameter varying models. Pdf development of linearparametervarying models for. The array of stateconsistent linear models that define an lpv model are represented by an array of statespace model objects. However, the updated model and conditions remain constant over the prediction horizon. New methods for computing the terminal cost for minmax model predictive control. An offline robust constrained model predictive control mpc algorithm for linear time varying ltv systems is developed. The use of linear parameter varying lpv prediction models has been proven to be an effective solution to develop model predictive control mpc algorithms for linear and non linear systems. Model predictive control of linear parameter varying.
The proposed method is derived by using the parameter dependent. Model predictive controller design based on the linear. Explicit model predictive control for systems with linear parameter varying state transition matrix thomas besselmann johan lo fberg manfred morari automatic control laboratory, eth zurich, zurich, switzer land, email. Publishers pdf, also known as version of record includes final. Lee school of chemical and biomolecular engineering. In this brief, we propose a method of synthesizing a model predictive control mpc law for linear parameter varying systems. First, by putting the advantages of the mpc approach into practice, the optimal output power regulation of the wind turbine is obtained using a control oriented linear parameter varying lpv model of the wind turbine. The main objective of the controller is to allow the wind turbine to extract from the wind a prespecified desired amount of power according to the wind speed and to guara ntee the stability. An improved robust model predictive control for linear parametervarying inputoutput models h. Anticipative model predictive control for linear parametervarying systems. Linear parameter varying lpv systems are a particular class of nonlinear systems which can be thought of as varyingsystems, for which the variation depends explicitly on a timevarying parameter referred to as the scheduling or weight sequence 12. 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. Linearparametervarying model predictive control for multiregion traffic systems.
Robust linear parameter varying model predictive control and its. Model predictive control of a nonlinear system with known. Sufficient linear matrix inequality lmi conditions are provided for the existence of a pathdependent lyapunov function which generalizes previous results based on affine parameterdependent lyapunov functions. Model predictive control based on lpv models with parameter.
Pdf this study presents a successful application of a model predictive control mpc design approach based on linear parametervarying. Model predictive control of linear parameter varying systems. A novel feature is the fact that both model uncertainty and bounded. The parameter is not known but its evolution is measured in real time and used for control. The model predictive control problem is formulated as a. Gligorovski 1 introduction this manuscript contains technical details of recent results developed by the authors on adaptive model predictive control for constrained linear, time varying systems. Model predictive controller design based on the linear parameter varying model method for a class of turboshaft engines. Adaptive model predictive control for constrained, linear time varying systems m. Robust linear parameter varying model predictive control and. Wind turbines power regulation using a lowcomplexity linear. Model predictive control for linear parameter varying systems using pathdependent lyapunov functions marc jungers rodrigo p. In this work, we propose the linear parameter varying model predictive control lpvmpc approach as a novel option to solve the driving control problem. An offline robust constrained model predictive control mpc algorithm for linear timevarying ltv systems is developed.
Balanced truncation,12 lmis, bounded parameter variaton rates,14 coprime factorizations17,18 and singular perturbation15,16 are presented as an extension of the model reduction techniques for linear time invariant lti systems. However, the computational effort is a crucial issue for lpvmpc, which has severely limited its application especially in embedded control. This paper describes a new robust model predictive control mpc scheme to control the discrete. Chapter1 introductiontononlinearmodel predictivecontroland. In order to reduce the online computational burdens, a sequence of explicit control laws corresponding to a. The toolbox lets you specify plant and disturbance models, horizons, constraints, and weights. An improved robust model predictive control for linear. This paper proposes a robust model predictive controller for linear parameter varying lpv systems subject to additive disturbances. Several model reduction techniques for linear, parameter varying lpv systems have been reported in the literature. Tubebased model predictive control for linear parameter. Anticipative model predictive control for linear parameter. Linear, parameter varying model reduction for aeroservoelastic systems. Linearparametervarying model predictive control for multi.
Output feedback model predictive control of linear. First, by putting the advantages of the mpc approach into practice, the optimal output power regulation of the wind turbine is obtained using a control oriented linear parameter varying lpv model of. Linear parameter varying lpv theory is used to model the dynamics of the vehicle and implement an lpvmodel predictive controller lpvmpc that can be computed online with reduced computational cost. In this paper, a new offline model predictive control strategy is presented for a kind of linear parameter varying system with polytopic uncertainty. In this work, we develop a novel adaptive model predictive control ampc formulation for multivariable timevarying systems. Pdf explicit model predictive control for systems with.
Adaptive model predictive control for constrained, linear. Linear parameter varying lpv theory is used to model the dynamics of the vehicle and implement an lpv model predictive controller lpvmpc that can be computed online with reduced computational cost. This information is used to construct state tubes to which the future trajectories of the state are confined. Adaptive mpc control of nonlinear chemical reactor using. This paper is concerned with the design of model predictive control mpc for linear parameter varying lpv discretetime systems. Development of linear parameter varying models are a key step in applying lpv control synthesis. Fast linear parameter varying model predictive control of. The controller is designed based on two different approaches and results have been compared.
Abstract this paper introduces a novel fast model predictive control mpc methodology based on linear parameter varying lpv systems. However below we formulate our problem using linear parameter varying systems lpv in which the scheduling variable is known for the entire prediction horizon. 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. Model predictive control of a wind turbine based on linear.
The models are obtained for the upandaway flight envelope of the boeing 747100200. An ellipsoidal offline model predictive control strategy for linear parameter varying systems with applications in chemical processes. Linearparametervarying approximation of nonlinear dynamics for model predictive flow control of urban multiregion systems. Hence, the model will be a time varying, nonlinear system, with the future time variation unknown, but measured by the sensors in realtime.
Jun 02, 2017 in this paper, a new offline model predictive control strategy is presented for a kind of linear parameter varying system with polytopic uncertainty. Model predictive control for linear parameter varying systems using a new parameter dependent terminal weighting matrix. Explicit model predictive control for systems with linear. Wind turbines power regulation using a lowcomplexity. Anticipative model predictive control for linear parametervarying systems hanema, j. Output feedback model predictive control of linear parameter. The authors perform a comparison against the corresponding non linear mpc version showing the. By running closedloop simulations, you can evaluate controller performance. Puig and carlos ocampomartinez abstractthis paper presents a model predictive control mpc strategy based on linear parameter varying lpv models with varying delays affecting states and inputs. Stabilizing nonlinear mpc using linear parametervarying. Linearparametervarying approximation of nonlinear dynamics. The proposed approach can deal with largescale problems better than conventional fast mpc methods. Model predictive control of a nonlinear system with.
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. A twotier modeling scheme is proposed in which the deterministic and stochastic components of the model are updated online by two separate recursive pseudolinear regression schemes. A linear parametervarying lpv system is a linear statespace model whose dynamics vary as a function of certain timevarying parameters called scheduling parameters. A polyhedral offline model predictive control algorithm for linear parameter varying systems. The three approaches used to obtain the quasilpv models are jacobian linearization, state transformation, and function substitution. Chapter1 introductiontononlinearmodel predictivecontroland movinghorizon estimation tor a. Model predictive control for linear parameter varying. 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 polytopic linear parameter varying model is established using tensorproduct modeling method, and tube model predictive control controller is designed to satisfy all vertices of the polytopic. Indeed, for dynamical systems of dimension commonly found in.
This article presents an innovative control approach for autonomous racing vehicles. Anticipative model predictive control for linear parameter varying systems hanema, j. The subspace predictors are derived by qr decomposition of inputoutput and laguerre. They are written similar to linear time invariant form albeit the inclusion in time variant parameter. The polytopic linear parameter varying model is established using tensorproduct modeling method, and tubemodel predictive control controller is designed to satisfy all vertices of the polytopic linear parameter varying model. Abstract this paper introduces a novel fast model predictive control mpc methodology based on linear parametervarying lpv systems.
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