Iterative Learning Control for Deterministic Systems

The material presented in this text addresses the analysis and design of learning control systems. Following an introduction to the concept of learning control, the book analyzes the problems encountered in linear time-invariant systems, using an approach which offers problem-solving techniques.

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The material presented in this book addresses the analysis and design of learning control systems. It begins with an introduction to the concept of learning control, including a comprehensive literature review. The text follows with a complete and unifying analysis of the learning control problem for linear LTI systems using a system-theoretic approach which offers insight into the nature of the solution of the learning control problem. Additionally, several design methods are given for LTI learning control, incorporating a technique based on parameter estimation and a one-step learning control algorithm for finite-horizon problems. Further chapters focus unpon learning control for deterministic nonlinear systems, and a time-varying learning controller is presented which can be applied to a class of nonlinear systems, including the models of typical robotic manipulators. The book concludes with the application of artificial neural networks to the learning control problem. Three specific ways to use neural nets for this purpose are discussed, including two methods which use backpropagation training and reinforcement learning.