Optimal Consensus Control Design for Multiagent Systems With Multiple Time Delay Using Adaptive Dynamic Programming
提出一种基于数据的自适应动态规划方法，解决离散时间多智能体系统在多重时延下的最优一致性跟踪控制问题，无需系统动力学模型。
In this article, a novel data-based adaptive dynamic programming (ADP) method is presented to solve the optimal consensus tracking control problem for discrete-time (DT) multiagent systems (MASs) with multiple time delays. Necessary and sufficient conditions of the corresponding equivalent time-delay system are provided on the basis of the causal transformations. Benefitting from the construction of tracking error dynamics, the optimal tracking problem can be transformed into settling the Nash-equilibrium in the graphical game, which can be completed by solving the coupled Hamilton-Jacobi (HJ) equations. An error estimator is introduced to construct the tracking error of the MASs only using the input and output (I/O) data. Therefore, the designed data-based ADP algorithm can minimize the cost functions and ensure the consensus of MASs without the knowledge of system dynamics. Finally, a numerical example is given to demonstrate the effectiveness of the proposed method.