NDLI: Adaptive optimal controllers based on Generalized Policy Iteration in a continuous-time framework

Content Provider	IEEE Xplore Digital Library
Author	Vrabie, D. Vamvoudakis, K. Lewis, F.
Copyright Year	2009
Description	Author affiliation: Automation and Robotics Research Institute, University of Texas at Arlington, USA (Vrabie, D.; Vamvoudakis, K.; Lewis, F.)
Abstract	In this paper we present two adaptive algorithms which offer solution to the continuous-time optimal control problem for nonlinear, affine in the inputs, time-invariant systems. Both algorithms were developed based on the Generalized Policy Iteration technique and involve adaptation of two neural network structures namely Actor, providing the control signal, and Critic, performing evaluation of the control performance. Despite the similarities, the two adaptive algorithms differ in the manner in which the adaptation takes place, required knowledge on the system dynamics, and formulation of the persistence of excitation requirement. The main difference is that one algorithm uses sequential adaptation of the actor and critic structures, i.e. while one is trained the other one is kept constant, while for the second algorithm the two neural networks are trained synchronously in a continuous-time fashion. The two algorithms are described in detail and proof of convergence is provided. Simulation results of applying the two algorithms for finding the optimal state feedback controller of a nonlinear system are also presented.
Starting Page	1402
Ending Page	1409
File Size	360234
Page Count	8
File Format	PDF
ISBN	9781424446841
DOI	10.1109/MED.2009.5164743
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-06-24
Publisher Place	Greece
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Performance evaluation State feedback Adaptive algorithm adaptive critics Generalized Policy Iteration neural networks Nonlinear control systems Adaptive control Convergence adaptive optimal control Programmable control Neural networks Optimal control continuous-time Nonlinear systems
Content Type	Text
Resource Type	Article

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