Chinese Journal of Intelligent Science and Technology ›› 2021, Vol. 3 ›› Issue (4): 444-448.doi: 10.11959/j.issn.2096-6652.202143

• Special Column: Data Based Learning and Optimization • Previous Articles     Next Articles

Synchronization control of unknown heterogeneous multi-agent system via model-free adaptive dynamic programming

Lina XIA1, Qing LI1, Ruizhuo SONG1, Zihan WANG1, Zhen XU2   

  1. 1 School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing 100083, China
    2 Research Institute of Urbanization and Urban Safety, University of Science and Technology Beijing, Beijing 100083, China
  • Revised:2021-11-09 Online:2021-12-15 Published:2021-12-01
  • Supported by:
    The National Natural Science Foundation of China(61873300);The National Natural Science Foundation of China(61722312);The Fundamental Research Funds for the Central Universities(FRF-MP-20-11);The Fundamental Research Funds for the Central Universities(FRF-IDRY-20-030)

Abstract:

Synchronization of multi-agent system has been gradually applied in the most fields, but there are still many unsolved problems.The synchronization control of unknown heterogeneous multi-agent system based on model-free adaptive dynamic programming (MFADP) algorithm was studied.Firstly, an observer was designed for each follower to estimate the information of the leader, including the state and the system dynamic matrix of the leader.Then, the optimal controller was obtained by exploiting the Bellman optimality principle.Under the condition that the dynamics of the follower was unknown, a MFADP algorithm was proposed.Finally, two-mass-spring systems were used to verify the effectiveness of the algorithm.

Key words: multi-agent system, algebraic Riccati equation, model-free adaptive dynamic programming

CLC Number: 

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