A decentralized fault detection and prediction scheme for nonlinear interconnected continuous-time systems

Abstract

Complex nonlinear systems such as an aircraft, trains, automobiles, power plants and chemical plants are represented as nonlinear interconnected subsystems. Therefore, in this paper a novel decentralized fault diagnosis and prognosis (FDP) methodology is proposed for such large-scale systems. Current FDP approaches require the knowledge of the entire state or its estimated vector. But the main goal in this work is to design a local fault detector (LFD) or observer for each subsystem based on the measured local states of the subsystem alone. A local residual signal is generated via the measured states of the local subsystem and the estimated states provided by the LFD. A fault is detected when this local residual exceeds a predefined threshold. The adaptive online approximator in each LFD is activated upon detection to compensate the fault dynamics due to local and non-local faults. A novel update law for tuning the parameters of the online approximator is derived. Upon detection, faults local to the subsystem and to other subsystems are isolated. In addition, the proposed scheme provides the time to failure (or remaining useful life) information by using local measurements and the parameter update law of the LFD. Simulation results verify the effectiveness of the proposed decentralized FDP scheme.

Fuzzy Adaptive Output Feedback Fault-Tolerant Tracking Control of a Class of Uncertain Nonlinear Systems With Nonaffine Nonlinear Faults

“…It is noted that the similar assumption is also given in [43]- [45]. In this paper, the controller can be designed in the following form: u = u n + u a , where u n is the nominal control law that stabilizes the system in the absence of unknown nonlinear function effects and faults, and u a is an adaptive control term for compensating the unknown nonlinear function and the change in dynamics due to faults.…”

“…In fact, the faults can be detected by some existing effective methods [35][36][37][38][39][40][41][42][43][44]. For example, in [35][36][37][38][39][40][41][42], by assuming the uncertainties are bounded, the faults can be detected.…”

“…For example, in [35][36][37][38][39][40][41][42], by assuming the uncertainties are bounded, the faults can be detected. In [43][44], based on the assumption that the uncertainties are bounded by a positive constant in healthy conditions. the detection threshold can be derived.…”

“…A similar approximator can be found in [43]- [45]. From (27), the stability of fuzzy state observer (14) cannot be achieved due to the second term, by introducing backstepping technique in the next section, this difficulty will be overcome and the objective will be derived.…”

“…To mention a few, in [42], an information based FTC scheme for a class of nonlinear dynamical systems is addressed in the presence of affine nonlinear faults, which are functions of x. By using local subsystem states alone, [43], [44] propose decentralized fault detection and accommodation scheme for interconnected nonlinear systems, where the unknown nonlinear function is assumed to be bounded by a positive constant in healthy conditions. On the basis of fault information from the fault-diagnosis procedure, the effects of faults can be compensated in [42]- [44].…”