In this paper we propose a distributed MPC methods 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.
Stochastic Distributed Predictive Tracking Control for Networks of Autonomous Systems with Coupling Constraints
M. Farina;
2018-01-01
Abstract
In this paper we propose a distributed MPC methods 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.File in questo prodotto:
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