Neural‐network‐based constrained optimal coordination for heterogeneous uncertain nonlinear multi‐agent systems

In this article, we investigate a constrained optimal coordination problem for class of heterogeneous nonlinear multi-agent systems described by high-order dynamics subject to both unknown nonlinearities and external disturbances. Each agent has private objective function steady-state constraint about its output. We develop composite distributed controller each combination internal model neural network techniques. All outputs are proven reach the minimal point aggregate with bounded residual errors irrespective Two examples finally given demonstrate effectiveness algorithm.