Distributed Model Predictive Control and Coalitional Control Strategies—Comparative Performance Analysis Using an Eight-Tank Process Case Study

Abstract

Complex systems composed of multiple interconnected sub-systems need to be controlled with specialized control algorithms. In this paper, two classes of control algorithms suitable for such processes are presented. Firstly, two distributed model predictive control (DMPC) strategies with different formulations are described. Afterward, a coalitional control (CC) strategy is proposed, with two different communication topologies, i.e., a default decentralized topology and a distributed topology. All algorithms were tested on the same simulation setup consisting of eight water tanks. The simulation results show that the coalitional control methodology has a similar performance to the distributed algorithms. Moreover, due to its simplified formulation, the former can be easily tested on embedded systems with limited computation storage.