Synchronous distributed model predictive control for state-coupled systems. (June 2019)

• Record Type: Journal Article
• Authors: Yang, Yuanqing; Ding, Baocang
• Is Part Of: Transactions of the Institute of Measurement and Control. Volume 41:Number 10(2019)
• Page Start: 2922
• Page End: 2931
• Publication Date: 2019-06
• Subjects: Model predictive control -- dynamically coupled subsystems -- constraint tightening -- compatibility constraint; Automatic control -- Periodicals; Measuring instruments -- Periodicals; Commande automatique -- Périodiques; Mesure -- Instruments -- Périodiques; 681.2
• DOI: 10.1177/0142331218819129
• Languages: English
• ISSNs: 0142-3312

Abstract

In this paper, we study distributed model predictive control (MPC) for the constrained system composed of a set of dynamically coupled subsystems. The proposed approach is based on the synchronous framework, so in each sub-controller, assumed state trajectories of its neighbours are involved, which are constructed by the optimal solutions at the previous sampling time. The compatibility constraint is imposed to bound the uncertain deviation between the assumed predictive trajectory and the true one. In addition, we use the constraint tightening technique in the predicted future evolutions to counteract this uncertain deviation which appears in the dynamics of each subsystem, so that physical constraints of the state and input are satisfied at each sampling time. By applying the proposed distributed MPC approach, the recursive feasibility and asymptotic stability of the overall system are guaranteed. An example is provided to verify the effectiveness and advantage of the result.