Adaptive NN Cooperative Optimal Control for Nonlinear Multiagent Systems Under Switching Topology

This article investigates the adaptive neural network (NN) cooperative optimal output-feedback control problem for nonlinear multi-agent (NMA) systems under switching topology. Since the optimization point of global cost function is unknown, an optimal signal generator and high-order filter are established to estimate optimization point and high-order derivatives of optimal virtual signals. Meanwhile, a NN state observer is designed to estimate unmeasurable states. Based on the NN state observer and high-order filter, an adaptive NN cooperative optimal output-feedback control scheme is proposed by backstepping control design technology. It is shown that the proposed adaptive NN cooperative optimal output-feedback control method ensures that all signals of systems are bounded and the global cost function is minimized. In addition, we apply the proposed cooperative optimal control approach to unmanned surface vehicle systems, the simulation results verify its effectiveness.