The Application of Decision Theory and Dynamic Programming to Adaptive Control Systems

Abstract

It is generally assumed that the implementation of adaptive control requires a precise identification of plant parameters. In the case of a system with varying parameters, the identification problem gets very involved, as speed of identification and accuracy are contradictory requirements. In this thesis it has been shown that using a feedback policy, the optimal controller is relatively· insensitive to changes in plant parameters as long as these lie within some specified ranges. It is, therefore, concluded that, with such an arrangement, adaptive control can be implemented if one has only the knowledge of the ranges within which the parameters of the plant lie. Thus identification can be carried on more rapidly, as stringent accuracy is no longer necessary.