System Reconfiguration and Fault-Tolerant for Distributed Model Predictive Control Using Parameterized Network Topology

A parameterized network topology based distributed model predictive control (DMPC) framework is proposed in this work, it is mainly applied in system reconfiguration and sensor fault-tolerant control. The Lyapunov stability condition for DMPC with a parameterized network topology is derived. Regarding to system reconfiguration, the parameterized network topology is served as the explicit reconfiguration model. Furthermore, for fault-tolerant control with sensor bias, the parameterized network topology is used to compensate the sensor fault, and a residual generator is designed by states of predictor and consider a time varying threshold for fault detection. The proposed approach is able to handle the system reconfiguration and fault-tolerant control without backup controllers or controllers redesign, and there is no need of the information of fault because of the using of predictor. (C) 2018, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.