Decentralized Fault Tolerant Control of a Class of Nonlinear Interconnected Systems


In this paper, a novel decentralized fault tolerant controller (DFTC) is proposed for interconnected nonlinear continuous-time systems by using local subsystem state vector alone in contrast with traditional distributed fault tolerant controllers or fault accommodation schemes where the measured or the estimated state vector of the overall system is needed. The proposed decentralized controller uses local state and input vectors and minimizes the fault effects on all the subsystems. The DFTC in each subsystem includes a traditional controller term and a neural network based online approximator term which is used to deal with the unknown parts of the system dynamics, such as fault and interconnection terms. The stability of the overall system with the proposed DFTC is investigated by using Lyapunov approach and the boundedness of all signals is guaranteed in the presence of a fault. Therefore, the proposed controller enables the system to continue its normal operation after the occurrence of a fault, as long as it does not cause failure or break down of a component. Although the decentralized fault tolerant controller is designed mainly for large-scale systems where continuous transmissions between subsystems is not possible, it can also be applied to small-scale systems where sensor measurements are available for use in all subsystems. Finally the proposed methods are verified and compared in simulation environment.


Electrical and Computer Engineering

Research Center/Lab(s)

Intelligent Systems Center

Keywords and Phrases

Continuous time systems; Controllers; Decentralized control; Fault tolerance; Large scale systems; Neural networks; Nonlinear systems; Adaptive Control; Decentralized controller; Fault tolerant control; Fault tolerant controllers; Nonlinear continuous-time systems; Nonlinear interconnected systems; On-line approximator; Simulation environment; Adaptive control systems

International Standard Serial Number (ISSN)

1598-6446; 2005-4092

Document Type

Article - Journal

Document Version


File Type





© 2017 Institute of Control, Robotics and Systems (ICROS), All rights reserved.

Publication Date

01 Apr 2017