Distributed Model Predictive Control of the Multi-agent Systems with Communication Distance Constraints

This paper addresses a distributed model predictive control (DMPC) scheme for multi-agent systems with communication distance constraints. Firstly, the communication distance constraints are dealt as non-coupling constraints by using the time varying compatibility constraints and the assumed state trajectory. Obviously, the control performance for all system is influenced by the time-varying compatibility constraints. Secondly, the deviation punishment is involved in the local cost function of each agent to penalize the deviation of the computed state trajectory from the assumed state. The value of the time-varying compatibility constraints is set according to the deviation of previous sample time. The closed-loop stability is guaranteed with a large weight for deviation punishment. A numerical example is given to illustrate the effectiveness of the proposed scheme.