Approximate Optimal Distributed Control of Nonlinear Interconnected Systems using Nonzero-Sum Games
In this paper, continuous and event-sampled approximate optimal distributed control schemes for an interconnected system, with nonlinear subsystem dynamics and strong interconnections, are presented. The control design problem for the interconnected system is reformulated as an N-player cooperative nonzero-sum differential game wherein the control policy of each subsystem is treated as a player in the game. The Nash solution of this game is used to design the control policy for each subsystem to optimize the performance of the interconnected system. Approximate dynamic programming (ADP), with critic neural networks, is utilized to approximate the solutions of the coupled Hamilton-Jacobi equations, for continuous and event-sampled control implementation. Event-sampling conditions are designed to asynchronously orchestrate the sampling and transmission at each subsystem. Finally, simulation results are included to substantiate the theoretical claims.
V. Narayanan et al., "Approximate Optimal Distributed Control of Nonlinear Interconnected Systems using Nonzero-Sum Games," Proceedings of the 2018 IEEE Conference on Decision and Control (2018, Miami Beach, FL), pp. 2872-2877, Institute of Electrical and Electronics Engineers (IEEE), Dec 2018.
The definitive version is available at https://doi.org/10.1109/CDC.2018.8618927
2018 IEEE Conference on Decision and Control, CDC 2018 (2018: Dec. 17-19, Miami Beach, FL)
Electrical and Computer Engineering
Intelligent Systems Center
Keywords and Phrases
Distributed parameter control systems; Large scale systems; Approximate dynamic programming; Control implementation; Distributed control; Distributed control schemes; Hamilton - Jacobi equations; Nonlinear interconnected systems; Nonlinear subsystems; Nonzero-sum differential game; Dynamic programming
International Standard Book Number (ISBN)
International Standard Serial Number (ISSN)
Article - Conference proceedings
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01 Dec 2018