Title
Adaptive Optimal Control of Linear Periodic Systems: An Off-Policy Value Iteration Approach
Abstract
This article studies the infinite-horizon adaptive optimal control of continuous-time linear periodic (CTLP) systems. A novel value iteration (VI) based off-policy adaptive dynamic programming (ADP) algorithm is proposed for a general class of CTLP systems, so that approximate optimal solutions can be obtained directly from the collected data, without the exact knowledge of system dynamics. Under mild conditions, the proofs on uniform convergence of the proposed algorithm to the optimal solutions are given for both the model-based and model-free cases. The VI-based ADP algorithm is able to find suboptimal controllers without assuming the knowledge of an initial stabilizing controller. Application to the optimal control of a triple inverted pendulum subjected to a periodically varying load demonstrates the feasibility and effectiveness of the proposed method.
Year
DOI
Venue
2021
10.1109/TAC.2020.2987313
IEEE Transactions on Automatic Control
Keywords
DocType
Volume
Adaptive dynamic programming,linear periodic systems,optimal control,value iteration
Journal
66
Issue
ISSN
Citations 
2
0018-9286
2
PageRank 
References 
Authors
0.40
2
2
Name
Order
Citations
PageRank
Bo Pang15795451.00
Z. Jiang210011.41