Design techniques for transient response control

Abstract

This dissertation analyzes and develops some design techniques for the control of transient response characteristics. First, a method for minimizing the output overshoot in SISO discrete-time systems with fixed-order controllers is given. The technique finds the optimal location of the assignable closed-loop system zeros for a given set of poles. Second, we investigate the use of multirate sampling techniques for assigning all the poles and zeros of the closed-loop system. Results are given for SISO plants, for square MIMO plants, and for the SISO servo problem. Intersample effects are also analyzed. Next, we consider a new approach called learning control. Learning control is an iterative approach to deriving the output of an optimal pre-filter, using actual input/output data. A complete analysis of the learning control problem is given for LTI systems, including a study of the nature of the solution, development of a learning controller based on parameter estimation, and a study of finite-horizon learning control schemes. We also present a learning control scheme that can be applied to a class of nonlinear systems which includes some models of robotic manipulators. Finally, we discuss the potential applications of artificial neural networks to the learning control problem.