基于神经网络逼近的异构多智能体系统二分拟一致性

Bipartite quasi-consensus of heterogeneous multi-agent systems based on neural network approximation

研究一类具有未知动力学的二阶异构非线性多智能体系统二分拟一致性问题.针对二阶多智能体系统中未知的非线性动态,基于神经网络逼近理论设计一类自适应控制协议,以保证所有智能体最终收敛到有界区域内.借助Lyapunov稳定性理论和不等式技巧得到异构多智能体系统实现领导-跟随二分拟一致性的充分性条件,并给出一致性误差的上界.最后通过数值仿真验证了理论结果的有效性.

This paper investigates the bipartite quasi-consensus for a class of second-order heterogeneous nonlinear multi-agent systems with unknown dynamics.Based on the neural network approximation theory,a new neuro-adaptive controller is designed to ensure all agents can eventually converge to a bounded region of the leader.Several sufficient conditions of quasi-consensus and the upper bounds of error for the multi-agent systems are obtained with the help of the Lyapunov stability theorem and inequality technique.Finally,some numerical simulations are provided to illustrate the feasibility and practicality of the theoretical results.