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A Theoretical Difficulty in Approximate Dynamic Programming with Input Constraints by Bao, Xuefeng; Mao, Zhi-Hong; Sharma, Nitin is a scholarly article available to read on EtoBox.

What is A Theoretical Difficulty in Approximate Dynamic Programming with Input Constraints about?

Equipping approximate dynamic programming (ADP) with inputconstraints has a tremendous significance. This enables ADP to be applied tothe systems with actuator limitations, which is quite common for dynamicalsystems. In a conventional constrained ADP framework, the optimal control issearched via a policy iteration algorithm, where the value under a constrainedcontrol is solved from a Hamilton-Jacobi-Bellman (HJB) equation while theconstrained control policy is improved based on the current estimated value.This concise and applicable method has been widely-used. However, the con-vergence of the existing policy iteration algorithm may possesses a theoreticaldifficulty, which might be caused by forcibly evaluating the same trajectoryeven though the control policy has already changed. This problem will beexplored in this paper.

Author

Bao, Xuefeng; Mao, Zhi-Hong; Sharma, Nitin

Published

2018

Language

EN