Intelligent condition monitoring of variable speed wind energy conversion systems based on decentralized sliding mode observer

Abstract

The main objective of this work is to describe the application of Decentralized sliding mode observer (DSMO) based fault detection and isolation (FDI) scheme for nonlinear variable speed wind energy conversion system (VSWECS) designed by a polytopic Quasi LPV representation, which is able to describe it as a convex combination of submodels defined by the vertices of a convex polytope. Stability conditions are performed by using Linear Matrix Inequalities (LMIs). In this work, we focus on the estimation and the reconstruction of the possible actuator and sensor faults to guarantee the efficiency and the continuous operation of this system. Simulation results are given to demonstrate the validity and the effectiveness of the proposed approach.

Contribution of Intelligent Instruments in Improving the Dependability of a Mechatronic Systems

“…In this model, the places P1 and P2 respectively represent the operating state and the malfunction of the sensor. Seats P3 to P5 represent the sensor fault [21] qualification part in a hazardous state or P6 (Tc) represents the test state of the sensor by the logic solver.…”

“…In this model of the sensor, a number of failures are specified. It is safe failure [21] (Safe Place) and dangerous failures (Danger place). A coverage rate of diagnosis DC is represented by the transition.…”

“…The model of the intelligent actuator is equivalent to the model intelligent sensor of Figure 7, but each with its own settings. The failure rates [21] of each element (sensor and actuator) are: lambda-sensor (λS) is equal to 6e -6 h -1 and lambda-actuator (λa) is equal to 9e -6 h -1 [4][5][6][17][18][19].…”

Robust Fuzzy Sliding Mode Observer for Faults Detection in Solar Power Plant Application

“…Recently, several researches have exploited the fuzzy modeling approach for the detection and the isolation of faults [17], Gao et al [18], have proposed an alternative approach to the reconstruction of sensor faults using fuzzy observer TS based on an increased blurred descriptor system [x], these observers are not robust. To achieve robustness, TS observers blurred were combined with the sliding mode [19] called TS-SMO can treat several faults and limited uncertainties in a well-defined theoretical framework, including the estimation of faults and the possible reconstruction of unknown inputs [17].…”