Overview
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.
The book, Self-Learning Optimal Control of Nonlinear Systems: Adaptive Dynamic Programming Approach (Studies in Systems, Decision and Control #103) [Bulk, Wholesale, Quantity] ISBN#9789811040795 in Hardcover by Qinglai Wei, Ruizhuo Song, Benkai Li, Xiaofeng Lin may be ordered in bulk quantities. Minimum starts at 25 copies. Availability based on publisher status and quantity being ordered.
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