Continuoustime model predictive control rmit research. Model predictive control of wind energy conversion systems wiley. Pdf critically damped stabilization of invertedpendulum. The most wellstudied mpc approaches with guaranteed stability use a control lyapunov function as terminal cost. The continuous time linear state space model will then be discretized to obtain the discrete time linear state space model. The robust mpc consists of a nonlinear feedback control and a continuous time model based dualmode mpc. Model predictive control of continuoustime nonlinear systems with. Introduction recent research interests and efforts have been directed towards reducing the computation orand communication load in control systems by using the eventtriggered scheme 1. Model predictive control for nonlinear continuoustime systems with.
In this paper, a robust model predictive control mpc is designed for a class of constrained continuous time nonlinear systems with bounded additive disturbances. The eventtriggered control is a promising solution to cyberphysical systems, such as networked control systems, multiagent systems, and largescale intelligent systems. Linearized mpc lmpc has the advantages over nonlinear approaches with its low computational cost 14 and avoidance of the occurrence of nonconvex programming which is common in nmpc 11. Robust continuoustime model predictive control of a grid. Continuous time model predictive control systems are designed for the drives and power supplies, and operational constraints are imposed in the design.
Integraltype eventtriggered model predictive control of. The plant under control, the state and control constraints, and the perf. View table of contents for model predictive control of wind energy. This paper presents a robust continuous time model predictive direct power control for doubly fed induction generator dfig. Critically damped stabilization of invertedpendulum systems using continuous time cascade linear model predictive control article pdf available in journal of the franklin institute 35416. The design and the experimental validation of a continuoustime model predictive control ctmpc for a permanent magnet synchronous motor pmsm drive with disturbance decoupling is discussed. A nonlinear model predictive control mpc is proposed for underactuated surface vessel usv with constrained inputs. Aimed at the special structure of usv, a statedependent coefficient sdc under the given usv is constructed in terms of diffeomorphism and statedependent riccati equation sdre theory. This technical note investigates the robust distributed model predictive control mpc problem for a group of nonlinear agents subsystems subject to control input constraints and external disturbances. The approach uses orthonormal functions to describe the trajectory of the control variable, and a multivariable state space model. Mpc model predictive control also known as dmc dynamical matrix control. The results are developed within the sampledata model predictive control mpc framework considering constrained nonlinear continuous time time varying dynamical systems.
The continuous time model predictive control scheme using orthonormal functions laguerre functions in our case developed in 7 is computationally effective and easy to tune to achieve desirable. The vformationmpc marriage can be understood in terms of the problem of synthesizing an optimal plan for a continuous space and continuous time markov decision process mdp, where the goal is to reach a target state that minimizes a given cost function. Continuoustime multimodel predictive control of variable. In this paper, a continuous time multi model predictive controller is proposed for variablespeed variablepitch wind turbine systems. Unconstrained model predictive control and suboptimality.
Other topics include the mapping of continuoustime models to. This paper presents a continuoustime version of recent results on unconstrained nonlinear model predictive control mpc schemes. Due to the ubiquitous existence of external disturbances, the design of distributed control algorithms with robustness is an urgent demand for multiagent system applications. Model predictive control 51 model predictive control with constraints. Offsetfree direct power control of dfig under continuous. Model predictive optimal control of a time delay distributedparameter system nhan nguyen. A numerical example is presented for illustrating the proposed control design methodology. This control technique is now being considered for power converters thanks to the drastic advances in power electronics and processors capabilities. Robust model predictive control for constrained continuous. The application is to control motor torque and specific mechanic energy.
This thesis investigates design and implementation of continuous time model predictive control using laguerre polynomials and extends the design ap proaches proposed in to include intermittent predictive control, as well as to include the case of the nonlinear predictive control. The objective of this thesis is the development of novel model predictive control mpc schemes for nonlinear continuoustime systems with and without timedelays in the states which guarantee asymptotic stability of the closedloop. Index termsnonlinear model predictive control, integraltype eventtriggered mechanism, continuous time nonlinear system, robust control. Model predictive control advanced textbooks in control. This thesis addresses the design of optimizationbased control laws for the case where convergence to a desired setpoint, minimization of an arbitrary performance index, or a combination of the two, is the desired objective. A new model predictive control mpc algorithm for nonlinear systems is presented. Meanwhile, when designing the cooperative controller, the state and control constraints, ubiquitously existing in the physical system, have to be respected. For a discretetime prediction model, statefcn is the state update function. Model predictive control mpc was originally developed to control multivariable linear models subject to constraints.
Let us consider the transfer function model of a distillation column as, 87. This paper presents the design and implementation of a continuous time model predictive controller using laguerre functions. Model predictive control for nonlinear continuoustime systems. Model predictive control of wind energy conversion systems. Discrete time model predictive control systems are designed based on the discretization of the physical models, which will appeal to readers who are more familiar with sampleddata control system. Ive read all the books suggested above but in my opinion this is the best book. An introduction to model based predictive control mpc by stanislaw h. Robust distributed model predictive control of constrained continuoustime nonlinear systems. Robust distributed model predictive control of constrained. Discontinuous feedbacks, discontinuous optimal controls. Lmibased model predictive control for underactuated. Yet, most continuous time model predictive control mpc frameworks had to assume continuity of the resulting feedback law, being unable to address an important. Hello, im looking for some practical examples of mpc algorithm i.
Shirobust distributed model predictive control of constrained continuous time nonlinear systems. In this paper, we propose an eventtriggered model predictive control mpc scheme for constrained continuoustime nonlinear systems with bounded disturbances. It is relatively easier and straightforward to handle a transfer function model. Firstly, a continuoustime mathematical model is suited better to the extrusion plant that has a fast sampling rate and a wide range of time constants.
At each sampling time, mpc solves a constrained optimal control problem online. Continuoustime model predictive control of underactuated spacecraft with bounded control torques. This paper studies the model predictive stabilization problem of a class of underactuated rigid spacecrafts with two bounded control torques. If your state function is continuoustime, the controller automatically discretizes the model using the implicit trapezoidal rule.
Nasa ames research center, moffett field, ca 94035 this paper presents an optimal control method for a class of distributedparameter systems governed by. Robust model predictive control and distributed model. Continuoustime model predictive control of food extruder. Pid and predictive control of electrical drives and power. For a continuoustime prediction model, statefcn is the state derivative function. We begin this section with a straightforward example. On the contrary, mpc algorithms based on discretetime system. Most approaches, however, were derived on the basis of discrete time models, and their corresponding continuous counter part is still in a relatively immature state of development because of obstacles in obtaining predictions and imposing constraints on the control. Continuoustime model predictive control of underactuated. After reading this book, i wrote my own mpc controller in no time. A predictioncorrection algorithm for real time model predictive control santiago paternain, manfred morari and alejandro ribeiro abstractin this work we adapt a predictioncorrection algorithm for continuous time varying convex optimization problems to solve dynamic programs arising from model predictive control. Continuous time model predictive control this section provides a brief discussion of the continuous time model predictive control 7 used in this paper. Dynamic control is also known as nonlinear model predictive control nmpc or simply as nonlinear control nlc.
Ab in this paper we develop a continuous time model predictive control mpc design procedure for singleinput singleoutput linear systems with actuator amplitude and rate saturation. We consider robust predictive control of continuoustime, constrained, nonlinear systems by means of a discretetime control scheme. Liuping wang, model predictive control system design and. Year 2007 abstract model predictive control mpc refers to a class of algorithms that optimize the future behavior of the plant subject to operational constraints 46. Continuous time model predictive control design using. This chapter deals with the design methodology of a robust continuoustime model predictive control ctmpc for the dcdc and the dcac converters, used in a gridtied pv system. Based on linear matrix inequalities lmis, the states of the usv are steered into an. Robust economic model predictive control of continuous.
Model predictive control is a group of algorithms developed as of the 1970s, specifically for discrete control in the process industry discrete because computers are digital and, hence, discrete. An introduction to modelbased predictive control mpc. A timevarying extremumseeking control approach for. The idea behind this approach can be explained using an example of driving a car. Model predictive control mpc is one of a few techniques. The main idea of mpc is to use a mathematical model of the process to predict its future behavior and minimize a given performance index, possibly subject to constraints capturing actuator limits and other operating constraints. Continuoustime model predictive control authors truong, q. A continuoustime predictive control system is designed based on the continuoustime model of the plant.
Model predictive control mpc is unusual in receiving ongoing interest in both industrial and academic circles. The key idea is to discretize the system first and to explicitly. Aperiodic robust model predictive control for constrained. Continuoustime model predictive control of a permanent magnet synchronous motor drive with disturbance decoupling abstract. Recurrent neural networkbased model predictive control for continuous. Is there good reference material on model predictive control. Based on a controllability assumption and a corresponding infinitedimensional optimization problem, performance estimates and stability conditions are derived in terms of the prediction horizon and the sampling time of the mpc controller. Model predictive control system design and implementation using. Model predictive control of continuoustime nonlinear. Predictive control for trajectory synthesis and path following of a carlike robot utilizes a nonlinear vehicle model with time varying constraints. Model predictive control of continuous time nonlinear systems with piecewise constant control lalo magni and riccardo scattolini abstracta new model predictive control mpc algorithm for nonlinear systems is presented. Apply the first value of the computed control sequence at the next time step, get the system state and recompute. A hybrid model predictive controller for path planning and.
Modeling of wind generators for model predictive control mapping of continuous. Therefore, a linear controller designed based on a model obtained at one operating point cannot guarantee stability and satisfactory performance across the whole operating regime of the turbine. Model predictive control advanced textbooks in control and signal processing. In matlab, the control toolbox offers a wide range of functions to handle the transfer function model, which is a linear model. Pdf discretetime robust model predictive control for.
Model predictive control linear convex optimal control. Since november 20, he has been with the school of marine science and technology, northwestern polytechnical university, xian, where he is currently an associate professor. Finally, model predictive control will be designed using the discrete time linear state space model. Continuous time model predictive control using orthonormal. The proposed approach uses taylor series expansion to predict the stator current in the synchronous reference frame over a finite time horizon. Model predictive control has received wide attention from researchers in both industry and universities over the last two decades. This article addresses the problem of controlling a constrained, continuoustime, nonlinear system through model predictive control mpc.
The plant under control, the state and control constraints, and the performance index to be minimized are described in. This class includes systems with interest in practice, such as nonholonomic systems, frequently appearing in robotics and other areas. Continuoustime model predictive control of a permanent. A time varying extremumseeking control approach for discrete time systems with application to model predictive control martin guay, ruud beerens, henk nijmeijer department of chemical engineering, queens university, kingston, on, canada department of mechanical engineering, eindhoven university of technology, eindhoven, the netherlands. In addition to its flexibility and time and costsaving features, continuous manufacturing is intrinsically steady and therefore easily amenable to model predictive design, optimization, and control.
Although continuoustime representation would be more natural, since the plant model. A predictioncorrection algorithm for realtime model. Continuous time model predictive control for a magnetic. Continuoustime model predictive control for economic. The merits of the class algorithms include its ability to handle imposed hard constraints on the system and. There are several advantages using the continuoustime approaches. Chapter 3 nonlinear model predictive control in this chapter, we introduce the nonlinear model predictive control algorithm in a rigorous way. A continuoustime model predictive controller was proposed using kautz function in order to improve the performance of load frequency control lfc. His research interests include networked control systems, multiagent systems, model predictive control and distributed and cooperative control of underwater vehicles. Model predictive control advanced textbooks in control and signal processing camacho, eduardo f.
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