An Overview of Fault-Diagnosis and Fault-Tolerance Techniques for Switched Reluctance Machine Systems <s> 2) FUZZY LOGIC CONTROL <s> An adaptive fuzzy controller has been designed to develop a high-performance fault-tolerant SRM drive. The fuzzy controller continuously adapts its properties to regulate the machine torque as desired by the drive system even under fault conditions. The adaptation of the fuzzy membership functions results in extended conduction period and increased peak current of the healthy phases to deliver the commanded torque, as much as possible. The adaptive fuzzy controller provides smooth torque output with minimum ripple, even under fault conditions, yielding a high-performance SRM drive with fault-tolerant capability. <s> BIB001 </s> An Overview of Fault-Diagnosis and Fault-Tolerance Techniques for Switched Reluctance Machine Systems <s> 2) FUZZY LOGIC CONTROL <s> In the present scenario, Switched reluctance motors (SRM) are growing prominence by industry due to their simple and craggy motor construction, the proficiency of running at wide speed range, their simple unipolar current drive system, high torque to inertia ratio, high consistency, and low cost. This study gives the information about different types of faults occurring in Switched reluctance motor (SRM) drives. SRM has unique property that it can run the motor during the fault condition by its inherent fault resilient capability. This paper emphasizes on switch open fault and switch short fault in the inverter circuitry so that fault-tolerant topology can be implemented to minimize toque and speed ripples. This paper also gives the comparison in fault behavior of switched reluctance motor drive having fuzzy controller and PID controller. <s> BIB002 </s> An Overview of Fault-Diagnosis and Fault-Tolerance Techniques for Switched Reluctance Machine Systems <s> 2) FUZZY LOGIC CONTROL <s> In this paper, a novel fuzzy adaptive tracking control scheme is concerned for switched reluctance motor with sensor fault. The considered switched nonlinear system contains unknown nonlinearities and sensor fault. In the design process, firstly, fuzzy logic systems (FLSs) are used to approximate the unknown nonlinear dynamics. Secondly, in order to solve the challenge of partial failure of the sensor, a novel fuzzy adaptive fault-tolerant controller is designed. Finally, the Lyapunov functions are constructed to prove the stability of switched reluctance motor and all of signals for closed-loop system is bounded. <s> BIB003
Fuzzy logic control is suitable for dealing with the system with high nonlinearity by fuzzification and defuzzification processes. Compared with the PID control method for SRM drives, fuzzy logic control schemes exhibit better speed dynamic response and lower torque ripple in the faulty case BIB002 . Fuzzy logic systems (FLSs) with adaptive tracking ability is derived for sensor faults and Lyapunov functions are adopted to analyze the system stability BIB003 . An adaptive fuzzy logic control strategy is also investigated in BIB001 . The fuzzy controller uses rotor position information to calculate the command phase currents. The system parameters are calculated on-line which avoids time-consuming finite element analysis and mathematical model. The membership functions consist of five triangular functions and one rectangular function. To minimize the torque ripple and maintain stable operation, the turn-off angle of the outgoing phase is delayed and the turn-on angle of the incoming phase is advanced. The control diagram of the adaptive fuzzy logic control is depicted in Fig. 22 . This method offers the minimum torque ripple and maximum output torque during opencircuit fault. 