Second-Order Sliding Fuzzy Interval Type-2 Control for an Uncertain System With Real Application

2012 ◽  
Vol 20 (2) ◽  
pp. 262-275 ◽  
Author(s):  
Malik Manceur ◽  
Najib Essounbouli ◽  
Abdelaziz Hamzaoui
Keyword(s):  
Uncertain System ◽  
Second Order ◽  
Real Application ◽  
Interval Type ◽  
Fuzzy Interval

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

2021 ◽  
Vol 54 (3) ◽  
pp. 475-485
Author(s):  
Izzeddine Dilmi ◽  
Abderrahmen Bouguerra ◽  
Ali Djrioui ◽  
Larbi Chrifi-Alaoui
Keyword(s):  
Fuzzy Logic ◽  
Active Fault ◽  
Fault Tolerant ◽  
Sliding Mode ◽  
Short Circuit ◽  
Fault Tolerant Control ◽  
Second Order ◽  
Interval Type ◽  
Second Order Sliding Mode

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.

Influence of different fuzzy operators on analytical structure and variable gains of typical interval type-2 fuzzy PI controller

2020 ◽  
Vol 39 (3) ◽  
pp. 4319-4329
Author(s):  
Haibo Zhou ◽  
Chaolong Zhang ◽  
Shuaixia Tan ◽  
Yu Dai ◽  
Ji’an Duan ◽  
...  
Keyword(s):  
Pi Controller ◽  
Real Time Control ◽  
Fuzzy Operators ◽  
Fuzzy Operator ◽  
Analytical Structure ◽  
Product Operator ◽  
Pi Controllers ◽  
Fuzzy Pi Controller ◽  
Interval Type

The fuzzy operator is one of the most important elements affecting the control performance of interval type-2 (IT2) fuzzy proportional-integral (PI) controllers. At present, the most popular fuzzy operators are product fuzzy operator and min() operator. However, the influence of these two different types of fuzzy operators on the IT2 fuzzy PI controllers is not clear. In this research, by studying the derived analytical structure of an IT2 fuzzy PI controller using typical configurations, it is proved mathematically that the variable gains, i.e., proportional and integral gains of typical IT2 fuzzy PI controllers using the min() operator are smaller than those using the product operator. Moreover, the study highlights that unlike the controllers based on the product operator, the controllers based on the min() operator have a simple analytical structure but provide more control laws. Real-time control experiments on a linear motor validate the theoretical results.

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