Download Adaptive Dynamic Programming with Applications in Optimal by Derong Liu, Qinglai Wei, Ding Wang, Xiong Yang, Hongliang Li PDF

By Derong Liu, Qinglai Wei, Ding Wang, Xiong Yang, Hongliang Li

This booklet covers the newest advancements in adaptive dynamic programming (ADP). The textual content starts off with a radical history assessment of ADP to ensure that readers are sufficiently acquainted with the basics. within the middle of the ebook, the authors tackle first discrete- after which continuous-time platforms. insurance of discrete-time platforms starts off with a extra normal type of worth generation to illustrate its convergence, optimality, and balance with whole and thorough theoretical research. A extra lifelike type of price new release is studied the place worth functionality approximations are assumed to have finite mistakes. Adaptive Dynamic Programming additionally info one other street of the ADP procedure: coverage new release. either simple and generalized different types of policy-iteration-based ADP are studied with entire and thorough theoretical research by way of convergence, optimality, balance, and mistake bounds. between continuous-time structures, the keep watch over of affine and nonaffine nonlinear structures is studied utilizing the ADP procedure that's then prolonged to different branches of regulate thought together with decentralized regulate, powerful and warranted rate keep an eye on, and video game idea. within the final a part of the ebook the real-world importance of ADP concept is gifted, concentrating on 3 software examples built from the authors’ work:

• renewable power scheduling for clever energy grids;• coal gasification approaches; and• water–gas shift reactions.
Researchers learning clever regulate tools and practitioners trying to observe them within the chemical-process and power-supply industries will locate a lot to curiosity them during this thorough remedy of a sophisticated method of control.

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Extra info for Adaptive Dynamic Programming with Applications in Optimal Control

Example text

It is shown in this book that ADP is an accessible introduction to dynamic modeling and is also a valuable guide for the development of high-quality solutions to problems that exist in operations research and engineering. The book by Busoniu, et al. [14] provides an accessible in-depth treatment of dynamic programming (DP) and reinforcement learning (RL) methods using function approximators. Even though DP and RL are methods for solving problems where actions are applied to a dynamical plant to achieve a desired goal, the former requires a model of the systems behavior while the latter does not since it works using only data obtained from the system.

It shows that trial-and-error search and delayed reward are the two most important distinguishing features of reinforcement learning. With the growing levels of sophistication in modern operations, it is vital for practitioners to understand how to approach, model, and solve complex industrial problems. The book by Powell [76] on approximate dynamic programming shows the decades of experience working in large industrial settings to develop practical 24 1 Overview of Adaptive Dynamic Programming and high-quality solutions to problems that involve making decisions in the presence of uncertainty.

25) where δt = rt+1 + γ max Qt (st+1 , a ) − Qt (st , at ), a zt (s, a) = Is,st Ia,at + γ λzt−1 (s, a), if Qt−1 (st , at ) = maxa {Qt−1 (st , a)}, 0, otherwise Ix,y = 1, if x = y, 0, otherwise, and z0 (s, a) = 0, ∀s, a. TD, Q-learning, Sarsa, TD(λ), Sarsa(λ), and Q(λ) are developed to obtain the value functions V (s) and Q(s, a). 20) (cf. 8)). The process can be repeated until an optimal policy is obtained. 6) iteratively to provide approximate solutions. 3 Adaptive Dynamic Programming There are several schemes of dynamic programming [9, 11, 23, 41].

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