Diagnosis of speed sensor faults in an induction machine based on a robust adaptive super-twisting observer

The present paper aims to determine a robust sensor fault-tolerant controller based on fuzzy logic using a robust adaptive super-twisting observer for the control of an induction machine and an inverter set by a state estimation method. The speed sensor is considered in the present case. The modular structure of the fault-tolerant control (FTC) scheme allows integrating this sensor within the existing closed-loop system, and the observer can therefore be designed independently. This article presents a new method to develop a fuzzy decision system that provides fault-tolerant control. This paper also aims at detecting the mechanical speed sensor faults. The proposed approach allows the automatic reconfiguration of the system in the event of a speed sensor failure. The defective fuzzy detection system makes a transition between the speed sensor and the robust observer based on a super-twisting algorithm that ensures the continuity and stability of the system; the fuzzy detection and transition system is required to be robust to parametric variations, and must be fast enough in order to locate the defect and eventually make a transition in the event of a fault. The output of the fuzzy block is injected into the control block to ensure super-twisting speed regulation. The performance of the proposed strategy also the robustness against parameter variation are assessed by simulation thanks to Matlab/Simulink software.