Optimal Output Synchronization of Nonlinear Multi-Agent Systems using Approximate Dynamic Programming
Optimal output synchronization of multi-agent leader-follower systems is considered. The agents are assumed heterogeneous so that the dynamics may be non-identical. An optimal control protocol is designed for each agent based on the leader state and the agent local state. A distributed observer is designed to provide the leader state for each agent. A model-free approximate dynamic programming algorithm is then developed to solve the optimal output synchronization problem online in real time. No knowledge of the agents' dynamics is required. The proposed approach does not require explicitly solving of the output regulator equations, though it implicitly solves them by imposing optimality. A simulation example verifies the suitability of the proposed approach.
H. Modares et al., "Optimal Output Synchronization of Nonlinear Multi-Agent Systems using Approximate Dynamic Programming," Proceedings of the 2016 International Joint Conference on Neural Networks (2016, Vancouver, Canada), pp. 4227-4232, Institute of Electrical and Electronics Engineers (IEEE), Jul 2016.
The definitive version is available at https://doi.org/10.1109/IJCNN.2016.7727751
2016 International Joint Conference on Neural Networks (IJCNN) (2016: Jul. 24-29, Vancouver, Canada)
Electrical and Computer Engineering
Keywords and Phrases
Learning Algorithms; Optimal Control Systems; Reinforcement Learning; Synchronization; Adaptive Observer; Distributed Approaches; Heterogeneous Systems; Leader-Follower; Optimal Control Problem; Output Regulation; Output Synchronization; Regulator Equations; Multi Agent Systems; Leader-Follower Systems
International Standard Book Number (ISBN)
International Standard Serial Number (ISSN)
Article - Conference proceedings
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