Self-Learning Fuzzy Sliding-Mode Control for a Water Bath Temperature Control System

2015 ◽  
Vol 17 (1) ◽  
pp. 31-38 ◽  
Author(s):  
Enkh-Amgalan Boldbaatar ◽  
Chih-Min Lin
Keyword(s):  
Control System ◽  
Sliding Mode Control ◽  
Temperature Control ◽  
Sliding Mode ◽  
Bath Temperature ◽  
Water Bath ◽  
Temperature Control System ◽  
Fuzzy Sliding Mode Control ◽  
Fuzzy Sliding Mode ◽  
Self Learning

Fuzzy sliding mode control of servo control system based on variable speeding approach rate

2019 ◽  
Vol 23 (24) ◽  
pp. 13477-13487 ◽  
Author(s):  
Hao Huang ◽  
Md Zakirul Alam Bhuiyan ◽  
Qunzhang Tu ◽  
Chengming Jiang ◽  
Jinhong Xue ◽  
...  
Keyword(s):  
Control System ◽  
Sliding Mode Control ◽  
Sliding Mode ◽  
Servo Control ◽  
Fuzzy Sliding Mode Control ◽  
Mode Control ◽  
Servo Control System ◽  
Fuzzy Sliding Mode

scholarly journals Adaptive Fuzzy Sliding Mode Control for a Micro Gyroscope with Backstepping Controller

Micromachines ◽  
2020 ◽  
Vol 11 (11) ◽  
pp. 968 ◽  
Author(s):  
Juntao Fei ◽  
Yunmei Fang ◽  
Zhuli Yuan
Keyword(s):  
Fuzzy Control ◽  
Sliding Mode Control ◽  
Sliding Mode ◽  
Learning Ability ◽  
Fuzzy Sliding Mode Control ◽  
Adaptive Fuzzy ◽  
Adaptive Fuzzy Sliding Mode ◽  
Fuzzy Sliding Mode ◽  
Self Learning ◽  
Fuzzy Parameters

This paper developed an adaptive backstepping fuzzy sliding control (ABFSC) approach for a micro gyroscope. Based on backstepping design, an adaptive fuzzy sliding mode control was proposed to adjust the fuzzy parameters with self-learning ability and reject the system nonlinearities. With the Lyapunov function analysis of error function and sliding surface function, a comprehensive controller is derived to ensure the stability of the proposed control system. The proposed fuzzy control scheme does not need to know the system model in advance and could approximate the system nonlinearities well. The adaptive fuzzy control method has self-learning ability to adjust the fuzzy parameters. Simulation studies were implemented to prove the validity of the proposed ABFSMC strategy, showing that it can adapt to the changes of external disturbance and model parameters and has a satisfactory performance in tracking and approximation.

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