Predictive control is a very wide class of controllers that have found rather recent application in the control of power converters. Research on this topic has been increased in the last years due to the possibilities of today's microprocessors used for the control. This paper presents the application of different predictive control methods to power electronics and drives. A simple classification of the most important types of predictive control is introduced, and each one of them is explained including some application examples. Predictive control presents several advantages that make it suitable for the control of power converters and drives. The different control schemes and applications presented in this paper illustrate the effectiveness and flexibility of predictive control.

Predictive Control in Power Electronics and Drives

An attempt is made to coordinate the numerous results relating to separation of estimation and control in discrete time stochastic control theory. The results vary widely depending upon the assumptions about linearity, criteria, information pattern, constraints, and noise distributions. Some of the less well-known underlying concepts are discussed with the help of a fairly general model.

Separation of estimation and control for discrete time systems

The paper investigates the efficiency of a recently developed signal control methodology, which offers a computationally feasible technique for real-time network-wide signal control in large-scale urban traffic networks and is applicable also under congested traffic conditions. In this methodology, the traffic flow process is modeled by use of the store-and-forward modeling paradigm, and the problem of network-wide signal control (including all constraints) is formulated as a quadratic-programming problem that aims at minimizing and balancing the link queues so as to minimize the risk of queue spillback. For the application of the proposed methodology in real time, the corresponding optimization algorithm is embedded in a rolling-horizon (model-predictive) control scheme. The control strategy's efficiency and real-time feasibility is demonstrated and compared with the Linear-Quadratic approach taken by the signal control strategy TUC (Traffic-responsive Urban Control) as well as with optimized fixed-control settings via their simulation-based application to the road network of the city centre of Chania, Greece, under a number of different demand scenarios. The comparative evaluation is based on various criteria and tools including the recently proposed fundamental diagram for urban network traffic.

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A rolling-horizon quadratic-programming approach to the signal control problem in large-scale congested urban road networks

There is a vast literature about adaptive (self-organizing, self-optimizing) control systems. The aim of this paper is to point out some of the main ideas. Since there exists good survey papers about several of the classes of adaptive controllers the main part of this paper will concentrate on recent developments. The paper will cover stochastic adaptive controllers. The problem of dual control is given particular attention.

Stochastic adaptive control methods: a survey

Many concrete problems from engineering, economics, operations research, etc., can be formulated by an optimization problem of the type 

$$\displaystyle\begin{array}{rcl} \min f_{0}(a,x)& &{}\end{array}$$

(1.1a)



$$\displaystyle\begin{array}{rcl} \mbox{ s.t.}& & {}\\ & & {}\\ \end{array}$$



$$\displaystyle\begin{array}{rcl} f_{i}(a,x)& \leq & 0,i = 1,\ldots,m_{f}{}\end{array}$$

(1.1b)



$$\displaystyle\begin{array}{rcl} g_{i}(a,x)& =& 0,i = 1,\ldots,m_{g}{}\end{array}$$

(1.1c)



$$\displaystyle\begin{array}{rcl} x \in D_{0}.& &{}\end{array}$$

(1.1d)

Stochastic optimization methods

: The optimal control of stochastic systems is considered. Under various assumptions concerning the information available to the controller, different optimal control rules result. For certain specific problems, the different control schemes are analyzed and compared, and the vast superiority of feedback over open-loop control is demonstrated.

Stuart E. Dreyfus

Papers

Some Types of Optimal Control of Stochastic Systems