Stochastic Distributed Predictive Tracking Control for Networks of Autonomous Systems With Coupling Constraints

In this paper, we propose a distributed model predictive control method with chance constraints for tracking reference signals. More specifically, considering a network of systems with independent dynamics, the proposed control scheme allows each subsystem to reach feasible setpoints, while respecting local and joint probabilistic constraints. Both a simulation example consisting of an academic temperature control problem and experimental results concerning the motion and coordination of moving agents are illustrated.