General Second-Order Consensus of Discrete-Time Multiagent Systems via Q-Learning Method
研究了离散时间广义二阶多智能体系统的一致性问题，提出一种无需系统动力学模型信息的Q学习方法，在固定有向拓扑下推导耦合增益矩阵实现一致性，并推广到无向图。
A consensus control issue is studied for general second-order multiagent systems via Q-learning method in this article. A novel second-order type with discrete-time dynamics is investigated to solve the corresponding consensus issues. Under fixed directed topology, in order to achieve general second-order consensus for the systems, a model-free Q-learning method is proposed, which can derive the coupling gains matrix without any information from the system dynamics. Moreover, applying the obtained coupling gains matrix, this general second-order multiagent systems can achieve consensus. Then, for undirected graphs, a similar corollary is obtained for this system to achieve general second-order consensus by means of the Q-learning method. Finally, the correctness of the new method is confirmed by several simulation examples.