Decentralized Model Predictive Control of interconnected nonlinear systems at the presence of faults over communication network

Abstract

Most processes in modern industries are physically distributed and generally composed of different subsystems, which characterized by significant interactions. In this paper, we investigate a decentralized Model Predictive Control (DMPC) approach for these systems over finite moving horizon at the presence of multiple faults occurring at unknown time-instants. Besides, the implementation of a control strategy can be achieved via a packet-based communication networks. The decentralized control strategy is combined with an online approximation method to deal with the unknown interconnection effects and multiple faults. This structure is implemented for each subsystem via the DMPC algorithm subject to some constraints. Meanwhile, the proposed structure is studied in the networked control system framework. It is proved that the proposed method guarantees input-to-state stability characterization for both local subsystems and the global system under some predetermined assumptions. The illustrative example is presented to explain the proposed strategy.