H Fuzzy Fault Detection for Uncertain 2-D Systems Under Round-Robin Scheduling Protocol

• Published in: IEEE transactions on systems, man, and cybernetics. Systems Vol. 47; no. 8; pp. 2172 - 2184
• Main Authors: Yuqiang Luo, Zidong Wang, Guoliang Wei, Alsaadi, Fuad E.
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.08.2017; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: 2-D systems; Asymptotic properties; Bandwidths; Communications systems; Design of experiments; Detectors; Discrete time systems; Dynamic stability; evaluation function; Fault detection; Fuzzy systems; Generators; limited communication; Nonlinear dynamics; nonlinear Roesser model; Probability theory; Protocols; Randomness; residual generator; Round-Robin protocol; Scheduling; Sensors; Stability analysis; Stability augmentation; State estimation; Stochastic processes; Takagi–Sugeno (T–S) fuzzy system; Uncertainty; update matrix
• DOI: 10.1109/TSMC.2016.2632043
• ISSN: 2168-2216

This paper is concerned with the robust H ∞ fault detection problem for a class of uncertain discrete-time nonlinear 2-D systems subject to Round-Robin scheduling protocol. The Takagi-Sugeno fuzzy model is used to approximate the nonlinearities, where the linear fractional uncertainties enter the system in a random way. A kind of widely used communication mechanism, namely, Round-Robin communication protocol, is adopted to periodically schedule the sensors and the fault detectors to realize the information exchange in order to reduce the bandwidth usage in a networked environment with limit resource. An improved 2-D fuzzy residual generator is constructed to detect the possible fault, where the stability analysis of the resulting augmented 2-D system is discussed. It is accomplished by using a combination of the basis-dependent Lyapunov-like function and the stochastic analysis techniques. Sufficient conditions are first established to guarantee the globally asymptotic stability of the error dynamics of the state estimation with prescribed H ∞ performance constraints. Then, a residual generator is proposed to detect the possible faults. The effectiveness of the developed algorithm is demonstrated via application to the fault detection problem for a thermal process.