Interval Type-2 Fuzzy Logic-Second Order Sliding Mode Based Fault Detection and Active Fault-Tolerant Control of Brushless DC Motor

Abstract

This paper addresses the detection of the short-circuit faults and the active fault tolerant control (AFTC) of the brushless direct current motor (BLDCM) based on the interval type-2 fuzzy-second order sliding mode. In this article, the main idea consists of using an algorithm to detect the fault in an electric current. This algorithm corrects the detected fault. In this study, a hybrid technique of fault tolerant control is proposed. This technique based on interval type 2 fuzzy logic and second order sliding mode. Also, it facilitates the procedures for setting and controlling the velocity of BLDCM. For that, a dynamic model for direct current has been established. Furthermore, short circuit faults have also been introduced between turns to test the robustness of the control laws. Finally, a theoretical analysis is presented and the simulations are presented in order to validate the proposed control strategy. The proposed AFTC can then achieve favorable tracking performance.

A Methodology for Fault Tolerant Control of Brushless DC Motors with Damaged Hall-Effect Sensors Using Electronic Logic Gates

“…The literature review conducted by Dilmi et al [9] explores the challenges and limitations of fault-tolerant control for BLDC motors, such as the need for accurate fault detection and the trade-off between system performance and safety. The review calls for further research in this area to address these challenges.…”

“…Compared to existing fault detection and control methods [1][2][3][4][5][6][7][8][9][10], the proposed FTC technique offers a more comprehensive and integrated approach. It offers quicker reaction times, more precise problem localisation, and more effective fault mitigation by directly integrating the fault detection system with the control strategy.…”

Real-Time Metaheuristic Algorithm for Dynamic Fuzzification, De-Fuzzification and Fuzzy Reasoning Processes

“…Furthermore, in the last three years of studies on higher-order types of FLS in particular, the designed and developed applications of interval type-2 fuzzy logic have increased significantly [48][49][50][51][52][53][54]. These type-2-based FLS applications have been identified in artificial intelligence (AI) [55][56][57][58][59], adaptive control [60][61][62][63][64][65][66], electric motor control [67][68][69][70][71][72], Internet of Things (IoT) [73][74][75][76][77], digital image processing [78][79][80][81][82][83][84] and other areas [85][86][87]. Of course, the application of interval type-2 fuzzy logic in the domain of control has recently attracted a lot of attention due to its better performance under uncertain conditions.…”