Dynamic Event-Triggered Optimal Consensus Control of Nonlinear Multi-agent Systems with Input Saturation

This paper addresses the problem of distributed optimal coordination control for nonlinear multi-agent systems with input saturation. An adaptive dynamic programming method is utilized to derive an optimal control strategy with a non-quadratic cost function, enabling the handling of control input saturation while achieving consensus and minimizing the predefined performance function. To approximate optimal performance indices, single critic networks are employed. The proposed triggered condition, incorporating an internal dynamic variable, reduces the number of events, and thus alleviates computational and transmission loads. By applying the Lyapunov stability theory, it is demonstrated that all the closed-loop signals are uniformly ultimately bounded. A simulation example is provided to showcase the effectiveness of the proposed algorithm.