Considering a sampling period t, a sampling instant. Worstcase formulations of model predictive control for systems with. Robust constrained model predictive control for discrete. In recent years it has also been used in power system balancing models and in power electronics. Model predictive controllers are implemented in discrete time since control decisions are made discretely instanteneously. I have a few confusions about model predictive control mpc. Our research lab focuses on the theoretical and real time implementation aspects of constrained predictive model based control. Pdf whither discrete time model predictive control. The proposed method is shown on two examples to be signi cantly more e cient than standard discrete time mpc that uses a sample time short enough to generate a cost close to the clqr solution. Discretetime mpc using laguerre functions springerlink. Model predictive control has a number of manipulated variable mv and controlled variable cv tuning constants. Pdf improved model predictive control of discretetime. The first is a discrete time model predictive methodbased trajectory tracking control law that is derived using an optimal quadratic algorithm.
Adaptive control processesa guided tour, princeton university press 1961. Eventtriggered model predictive control of discrete time linear systems subject to disturbances daniel lehmann, erik henriksson and karl h. Drivabilityrelated discrete time model predictive control of mode transition in pretransmission parallel hybrid powertrains article pdf available in energies 99. Abstract this paper presents the design of a new robust model predictive control algorithm for nonlinear systems represented by a linear model. As described in the next sections, in mpc a prediction model is used and the control law is computed in discrete time. Leaving the technical details aside until chapter 3, this chapter will explain the basic idea of mpc and summarize the content of the thesis. Chapter 4 discretetime model predictive control semantic scholar.
I have been reading the book model predictive control system design and implementation using matlab for studying the. Dubay 2007 provided real time comparison of a number of predictive controllers 6. Robust model predictive control for discretetime fractional. In the design of model predictive controller mpc, the traditional approach of expanding the projected control signal uses the forward operator to obtain the linearintheparameters relation for predicted output. In this thesis, we deal with aspects of linear model predictive control, or mpc for short. Discrete time model predictive control design using. Some related results are available in the literature, but proofs for the discrete time case are difficult to find. Model predictive control for discreteevent and hybrid systems. Citeseerx model predictive control of discretetime. A diabetic is simulated by a mathematical model, and based on this model the mpc will compute the optimal insulin input, taking constraints, disturbances and noise into account. In this paper, a dualmode model predictive linear control method is presented, which extends the concept of dualmode model predictive control mpc to trajectory tracking control of nonlinear dynamic systems described by discrete time statespace models. It has been in use in the process industries in chemical plants and oil refineries since the 1980s.
The famous takagisugeno ts fuzzy systems are utilized to represent nonlinear systems. Model predictive optimal control of a timedelay distributedparameter system nhan nguyen. In this paper, an overview of the most commonly used six methods of mpc with history. Two different predictive control formulations are developed based on minimization. Further it is assumed that the state, input and disturbance belong to the compact sets x x, u u, d d. Tube model predictive control for a class of nonlinear discrete time systems hashem imani marrani1, samane fazeli2, hamid malekizade3 and hasan hosseinzadeh4 abstract. Chapter 3 nonlinear model predictive control in this chapter, we introduce the nonlinear model predictive control algorithm in a rigorous way. Summary this paper investigates stability analysis for piecewise affine pwa systems and specifically contributes a new robust model. Optimized robust control invariance for linear discrete time systems. Dynamic control is also known as nonlinear model predictive control nmpc or simply as nonlinear control nlc. This thesis investigates design and implementation of continuous time model predictive control using laguerre polynomials and extends the design approaches proposed in 43 to include intermittent predictive control, as well as to include the case of the nonlinear predictive control. Basic workflow for designing traditional implicit model predictive controllers. Adaptive control of nonlinear plant by updating internal plant model at run time. Model predictive control of discretetime hybrid systems.
Model predictive optimal control of a timedelay distributed. Thus, by repeatedly solve an openloop optimization problem with every initial conditions updated at each time step, the model predictive control strategy. The process is repeated because objective targets may change or updated measurements may have adjusted parameter or state estimates. The issues of feasibility of the online optimization, stability and performance are largely understood for systems described by linear models. Furthermore, mpc methods for linear or nonlinear systems are developed by assuming that the plant under control is described by a discretetime one. This paper proposes and discusses a model predictive control approach to hybrid systems with discrete inputs only. Explicitmultiparametric model predictive control mpc. Instead of the lyapunovkrasovskii functional, the lyapunovrazumikhin function is adopted to deal with time delays. At each sampling time k, the timetriggered mpc solves minimize u k j x k,u k minimize u k. In mathematics and, in particular, mathematical dynamics, discrete time and continuous time are two alternative frameworks within which to model variables that evolve over time. Hybrid discrete time modelling and explicit model predictive control for brushed dc motor speed control1 zhaozhun zhong2, miao guan2, xinpei liu3 abstract. Can anyone explain discrete time model predictive control with constraints. The control calculations are based on both future predictions and current.
Model predictive control mpc is an advanced method of process control that is used to control a process while satisfying a set of constraints. We deal with linear, nonlinear and hybrid systems in both small scale and complex large scale applications. Model predictive control, generally based on state space models, needs the complete state for feedback. As a singlestage inverter topology, the qzsi regulates the dclink voltage and the ac output voltage through the shootthrough st duty cycle and the modulation index. Model predictive optimal control of a time delay distributedparameter system nhan nguyen.
Delft center for systems and control technical report 03012 model predictive control for discreteevent and hybrid systems. Robust model predictive control of constrained linear systems with bounded disturbances. The syntax for creating discretetime models is similar to that for continuoustime models, except that you must also provide a sample time sampling interval in seconds. Our motivation for obtaining these results was to determine conditions under which discrete time nonlinear model predictive control is stabilizing in the face of perturbations. The algorithm takes into account the real nonlinear system as a model of a hybrid system, which is based on building a tree of evolution. Can anyone explain discretetime model predictive control with. The problem of obtaining robustness against parametric uncertainty is renewed to the problem of grasping robustness against additional bounded disturbance. The development of an innovative empc explicit model predictive control scheme for brushed dc direct current motor speed control is traced to overcome the control. A dualmode model predictive control algorithm trajectory. Drivabilityrelated discretetime model predictive control.
Stabilising model predictive control for discretetime fractional. This paper recalls a few past achievements in model predictive control, gives an overview of some current developments and suggests a few avenues for future research. This paper suggests an improved method for predictive control of hybrid systems with mixed inputs. Within a course on optimal and robust control b3m35orr, be3m35orr given at faculty of electrical engineering, czech technical university in prague. This work presents a new algorithm for solving the explicitmultiparametric model predictive control or mpmpc problem for linear, time invariant d. Module 09 optimization, optimal control, and model. Learn the basics of model predictive control toolbox. Robustification of nonlinear model predictive control tel. In this chapter, we will introduce the basic ideas and terms about model predictive control.
Unlike time delay compensation methods, the predictions are made for more than one time delay ahead. Pdf drivabilityrelated discretetime model predictive. This paper presents an efficient direct model predictive control edmpc technique for surfacemounted permanentmagnet synchronous generators pmsgs in variablespeed wind energy conversion systems. Eventtriggered model predictive control of discretetime. Observerbased model predictive control bas rosety and henk nijmeijery model predictive control in combination with discrete time nonlinear observer theory is studied in this paper.
A discretetime average model based predictive control for. Model predictive control for discretetime linear systems. For confronting such problems, several robust model predictive control rmpc techniques have been developed in recent. This article presents a tracking control approach with obstacle avoidance for a mobile robot. Model predictive control model predictive control is a form of control scheme in which the current control action is obtained by solving, at each sampling instant, a finite horizon openloop optimal control problem, using the current state of the plant as the initial state.
Communications in computer and information science, vol 487. Mpc model predictive control also known as dmc dynamical matrix control. Module 09 optimization, optimal control, and model predictive control ahmad f. I have been reading the book model predictive control system design and implementation using matlab for studying the algorithm of mpc controller. Process control in the chemical industries 119 from the process. Can anyone explain discretetime model predictive control.
Pdf model predictive control status and challenges. Abstract in this paper, we investigate a robust constrained model predictive control synthesis approach for discrete. The partitioned discrete time model for control area of the continuous time fourarea interconnected power system,, and can be expressed as follows. Discretetime model predictive contouring control for biaxial feed drive systems and experimental verification article pdf available in mechatronics 216. Keywords model predictive control active constraint prediction horizon sampling instant control trajectory. Robust model predictive control for discretetime fractionalorder systems. Robust nonlinear model predictive control based on constrained. Discrete time model predictive control approach for inverted pendulum system with input constraints harshita joshi1, nimmy paulose2 1,2electrical engineering department, mnnit, allahabad,india. Model predictive control of discretetime hybrid systems with discrete inputs b.
Model predictive control mathematics stack exchange. Integration of extremum seeking and model predictive. The algorithm, which takes into account a model of a hybrid system, described as a mixed logical dynamical system, is based on a performancedriven reachability analysis. The recurrence for kis the discrete time varying riccati equation. This thesis deals with linear model predictive control, mpc, with the goal of making a controller for an arti cial pancreas. This paper proposes a distributed model predictive control dmpc approach for a family of discrete time linear systems with local uncoupled and global coupled constraints. A provoking analogy between mpc and classical control can be found in 15. In this paper, two efficient robust fuzzy model predictive control algorithms are investigated for discrete nonlinear systems with multiple time delays and bounded disturbances. Tube model predictive control for a class of nonlinear. Efficient directmodel predictive control with discrete. Then the optimization yields an optimal control sequence and the first control in this sequence is applied to the plant. Realtime implementation of model predictive control.
A discrete time average model based predictive control dtampc is proposed for a quasizsource inverter qzsi. The proposed approach is based on the dual problem of a mpc optimization problem involving all systems. Delay removal if the discrete time model includes any input, output, or internal delays, the absorbdelay command replaces them with the appropriate number of poles at z 0, increasing the total number of discrete states. Ee392m winter 2003 control engineering 1220 emerging mpc applications nonlinear plants just need a computable model simulation hybrid plants combination of dynamics and discrete mode change engine control large scale operation control problems operations management campaign control. Optimal control, and model predictive control 18 32. Citeseerx document details isaac councill, lee giles, pradeep teregowda. Several matlab tutorials are presented in this chapter for the design of discrete time predictive control systems, with or without constraints.
Delft center for systems and control technical report 03012 model predictive control for discrete event and hybrid systems. Robust economic model predictive control of continuous. The inputdelay, outputdelay, and internaldelay properties of the resulting statespace model are all zero. B technique is applied for discrete controls in which an embedded nonlinear programming approach pattern search is. Pdf discretetime model predictive contouring control for. The basic ideaof the method isto considerand optimizetherelevant variables, not. The first control action is taken and then the entire process is repeated at the next time instance. Thus, a discrete time representation of this model becomes necessary. Johansson abstract this paper presents an approach to eventtriggered model predictive control for discrete time linear systems subject to input and state constraints as well as exogenous disturbances.
Model predictive control has had an exceptional history with early intimations in the academic literature coupled with an explosive growth due to its independent adoption by the process industries where it proved to be highly successful in comparison with alternative methods of multivariable control. Efficient robust fuzzy model predictive control of. Nmpc is interpreted as an approximation of infinitehorizon optimal control so that important properties like closedloop stability, inverse optimality and suboptimality can be derived in a uniform manner. The key parameters of the discrete time model predictive controller are determined by comparison with a discrete time linear quadratic regulator dlqr minimizing the almost identical cost function but without constraints. The algorithm, which takes into account a model of a hybrid system, described as an mld mixed logical dynamical system, is based on a performancedriven reachability analysis. This paper signifies a tube model predictive control for discrete time uncertain nonlinear systems in the presence of bounded disturbances.
This paper proposes a distributed model predictive control dmpc approach for a family of discretetime linear systems with local uncoupled and global coupled constraints. By and large, the main disadvantage of the mpc is that it cannot be able of explicitly dealing with plant model uncertainties. Specify plant model, input and output signal types, scale factors. Stabilising model predictive control for discretetime fractionalorder. Since they are all minor questions related to the same category, i ask them under one topic. However, the updated model and conditions remain constant over the prediction horizon. Model predictive control for load frequency control with wind.
Apply the first value of the computed control sequence at the next time step, get the system state and recompute. Discrete time model definition of discrete time model by. Model predictive controllers rely on dynamic models of. Model predictive control of discretetime hybrid systems with. Model predictive control of discrete time hybrid systems with discrete inputs b. College station, tx in robust model predictive control, the aim is to control a system in. Control system toolbox lets you create both continuoustime and discretetime models.
Model predictive control of nonlinear discrete time systems with. Future values of output variables are predicted using a dynamic model of the process and current measurements. Abstract in this paper, the model predictive control problem is investigated for a class of discrete. This cited by count includes citations to the following articles in scholar.
Improved model predictive control of discretetime hybrid. Datadriven model predictive control with stability and. Let us consider the following discretetime nonlinear system. Our contributions include the discovery of fundamental theoretical results, the development of novel control. A model in which the system under analysis jumps from one state to the next at fixed intervals at a finite rate of change at each interval. Mpc model predictive control also known as dmc dynamical matrix control gpc generalized predictive control rhc receding horizon control control algorithms based on numerically solving an optimization problem at each step constrained optimization typically qp or lp receding horizon control. Hence, we concentrate our attention from now onwards on results related to discrete time systems. Continuous time systems are sampled to obtain a discrete time. First, we prove exponential stability of a nominal datadriven mpc scheme with. In this paper, a novel controller design which consists of discrete time model predictive control dmpc based on laguerre functions and space vector pulse width modulation svpwm is proposed to. Nasa ames research center, moffett field, ca 94035 this paper presents an optimal control method for a class of distributedparameter systems governed by. To adapt to changing operating conditions, adaptive mpc supports updating the prediction model and its associated nominal conditions at each control interval. Abstract model predictive control mpc includes a recedinghorizon control techniques based on the process model for predictions of the plant output. Model predictive control, constrained control, large scale systems, nonlinear systems.
In this paper we propose a model predictive control scheme for constrained fractionalorder discretetime systems. Distributed model predictive control of linear discrete. Efficient direct model predictive control with discrete time integral action for pmsgs abstract. Discretetime predictive trajectory tracking control for. Review of mpc methods there are various control design methods based on model predictive control concepts.