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    • Model-Free Distributed Optimal Consensus Control of Nonlinear Multi-Agent Systems: A Graphical Game Approach.

    Ningbo An,Xiaochuan Zhao,Qishao Wang,Qingyun Wang

    JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS（2023）

    Beihang Univ

    Cited 8|Views2
    Abstract
    In this paper, the optimal consensus control problem of nonlinear multi-agent systems(MASs) with completely unknown dynamics is considered. The problem is formulated in a differential graphical game approach which can be solved by Hamilton-Jacobi (HJ) equations. The main difficulty in solving the HJ equations lies in the nonlinear coupling between equations. Based on the Adaptive Dynamic Programming (ADP) technique, an VI-PI mixed HDP algorithm is proposed to solve the HJ equations distributedly. With the PI step, a suitable iterative initial value can be obtained according to the initial policies. Then, VI steps are run to get the optimal solution with exponential convergence rate. Neural networks (NNs) are applied to approximate the value functions, which makes the data-driven end-to-end learning possible. A numerical simulation is conducted to show the effectiveness of the proposed algorithm.& COPY; 2022 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.
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    Key words
    Multi-Agent Systems,Adaptive Dynamic Programming,Nonlinear Systems,Adaptive Control,Optimal Control
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