Flocking control for multi-agent systems with communication optimization

In this paper, we consider the flocking control and communication optimization problem for multi-agent systems in a realistic communication environment. In flocking control, it is common to specify the formation by setting the separation distance between neighboring agents and then design the control to maintain the desired formation. However, since communication quality will generally change during flocking in a physical environment, a predefined separation distance might not always be the desired communication distance. In this paper, a distributed scheme integrating potential function and extremum seeking algorithm is proposed to obtain the desired separation distance between neighboring agents in real time. A comprehensive performance index related to the environment is proposed, which captures a trade-off between formation tasks and communication quality. Since it is difficult to calculate the gradient of the performance in physical environments, an adaptive model-free extremum seeking algorithm is designed to solve for the optimal separation distances, which calls for no knowledge of the gradient of performance function. We illustrate the proposed method through simulations.