This book presents a class of novel, self-learning, optimal control schemes based on adaptive dynamic programming techniques, which quantitatively obtain the optimal control schemes of the systems. It analyzes the properties identified by the programming methods, including the convergence of the iterative value functions and the stability of the system under iterative control laws, helping to guarantee the effectiveness of the methods developed. When the system model is known, self-learning optimal control is designed on the basis of the system model; when the system model is not known, adaptive dynamic programming is implemented according to the system data, effectively making the performance of the system converge to the optimum.
With various real-world examples to complement and substantiate the mathematical analysis, the book is a valuable guide for engineers, researchers, and students in control science and engineering.
- ISBN13 9789811350436
- Publish Date 12 January 2019 (first published 22 June 2017)
- Publish Status Active
- Publish Country SG
- Imprint Springer Verlag, Singapore
- Edition Softcover reprint of the original 1st ed. 2018
- Format Paperback
- Pages 230
- Language English