Distributed Fault-Tolerant Control of Large-Scale Systems: An Active Fault Diagnosis Approach

• Published in: IEEE transactions on control of network systems Vol. 7; no. 1; pp. 288 - 301
• Main Authors: Boem, Francesca, Gallo, Alexander J., Raimondo, Davide M., Parisini, Thomas
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 01.03.2020; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Active fault diagnosis; Algorithms; Computer architecture; Computer simulation; Control stability; Control systems; Controllers; decentralized control; Decision support systems; Fault detection; Fault diagnosis; Fault tolerance; Fault tolerant systems; fault-tolerant control (FTC); interconnected systems; Monitoring; optimal control; Predictive control; Reconfiguration; Stability analysis; Subsystems
• ISSN: 2325-5870; 2372-2533
• DOI: 10.1109/TCNS.2019.2913557

The paper proposes a methodology to effectively address the increasingly important problem of distributed fault-tolerant control for large-scale interconnected systems. The approach dealt with combines, in a holistic way, a distributed fault detection and isolation algorithm with a specific tube-based model predictive control scheme. A distributed fault-tolerant control strategy is illustrated to guarantee overall stability and constraint satisfaction even after the occurrence of a fault. In particular, each subsystem is controlled and monitored by a local unit. The fault diagnosis component consists of a passive set-based fault detection algorithm and an active fault isolation one, yielding fault-isolability subject to local input and state constraints. The distributed active fault isolation module-thanks to a modification of the local inputs-allows to isolate the fault that has occurred, avoiding the usual drawback of controllers that possibly hide the effect of the faults. The Active Fault Isolation method is used as a decision support tool for the fault-tolerant control strategy after fault detection. The distributed design of the tube-based model predictive control allows the possible disconnection of faulty subsystems or the reconfiguration of local controllers after fault isolation. Simulation results on a well-known power network benchmark show the effectiveness of the proposed methodology.