Output regulation of nonlinear multi-agent systems based on dynamic neural networks

In this paper, the output regulation problem of the nonlinear multi-agent system with dynamic neural networks is addressed. First, we use a neural network to approximate the nonlinear model of the considered multi-agent system by the learning law. Then the output regulation technique is used to the neural network to design a controller, which make the following agents to asymptotically track (or reject) the reference (or disturbance) generated by an exosystem. The exosystem can be viewed as the active leaders or the environmental disturbance in the multi-agent systems. Finally, a numerical simulation example is presented to demonstrate the effectiveness of the main results.