A design of self‐tuning pole‐assignment control systems based on minimizing quadratic cost functions

Abstract

SUMMARYThere are numerous studies of the design of self-tuning control (STC) systems for linear nonminimum-phase systems. A wide variety of existing methods on designing STC systems are conceptually classified into two groups. One is based on minimization of an error criterion, and the other on pole assignment of the closed-loop system. On the other hand, in order to guarantee the tracking property for the reference signals, an internal model which corresponds to the reference signals must be inserted into the control system based on the internal model principle. However, the variance of the control error signal may become large on inserting the internal model, because stochastic noise may be amplified. In this paper, a design method for self-tuning pole-assignment control systems with internal models is proposed based on minimizing the linear quadratic cost function. The newly proposed control scheme has the feature that the variance of the stochastic noise in the control system is reduced owing to the minimum variance control scheme, and also the tracking property with respect to the reference signal is assured owing to the internal model. The proposed control scheme is numerically evaluated in some simulation examples.