Iterative learning control for deterministic systems
The contents of this book on Learning Control are as follows: After the introductory Section 1, an overview of Iterative Learning Control is given. Then linear time invariant systems are discussed. If the system dynamics are known, then, according to the conclusions, iterative learning control does not give interesting results. In the next chapter a scheme is provided, when some parameters are unknown. Then extensions are discussed, including finite horizon problems, time-varying plants and nonlinear systems. Finally, the application of artificial neural networks is discussed. There are two appendices on multirate sampling and artificial neural networks, respectively. The book is well structured and an effort is made to introduce readers to the field and to state clearly the present stage of research.
scientific article; zbMATH DE number 408380