A Model-Based Fault Detection and Prognostics Scheme for Takagi–Sugeno Fuzzy Systems

摘要: In this paper, a novel model-based fault detection (FD) and prediction scheme is developed for class of Takagi-Sugeno (T-S) fuzzy systems. Unlike other FD schemes, in the proposed design, an observer with online learning capability utilized to generate residual which obtained by comparing system output respect output. A declared active if generated exceeds priori chosen threshold. Subsequently, magnitude estimated using suitable parameter update law. Upon detection, estimate used mathematical equation determine time-to-failure (TTF) or remaining useful life. TTF determined projecting at current time instant against failure Note that previously reported schemes could neither growing real nor were they able predict life system. stability prognostics verified Lyapunov theory. Finally, two different simulation case studies are considered verify theoretical conjectures presented paper.