Using least mean square learning error to improve Takagi-Sugeno type fuzzy logic controller optimization

2002 ◽  
Author(s):  
Feijun Song ◽  
S.M. Smith
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Controller ◽  
Mean Square ◽  
Least Mean Square ◽  
Takagi Sugeno

scholarly journals Self-tuning Fuzzy Logic Controller Based on Takagi-Sugeno Applied to Induction Motor Drives

2018 ◽  
Vol 9 (4) ◽  
pp. 1967 ◽  
Author(s):  
Nabil Farah ◽  
M. H. N. Talib ◽  
Z. Ibrahim ◽  
J. M. Lazi ◽  
Maaspaliza Azri
Keyword(s):  
Fuzzy Logic ◽  
Induction Motor ◽  
Fuzzy Logic Controller ◽  
Experimental Testing ◽  
Motor Drives ◽  
Computational Burden ◽  
Response Characteristics ◽  
Speed Error ◽  
Self Tuning ◽  
Takagi Sugeno

<span>Fuzzy logic controller has been the main focus for many researchers and industries in motor drives. The popularity of Fuzzy Logic Controller (FLC) is due to its reliability and ability to handle parameters changes during load or disturbance. Fuzzy logic design can be visualized in two categories, mamdani design or Takagi-Sugeno (TS). Mamdani type can facilitate the design process, however it require high computational burden especially with big number of rules and experimental testing. This paper, develop Self-Tuning (ST) mechanism based on Takagi-Sugeno (TS) fuzzy type. The mechanism tunes the input scaling factor of speed fuzzy control of Induction Motor (IM) drives Based on the speed error and changes of error. A comparison study is done between the standard TS and the ST-TS based on simulations approaches considering different speed operations. Speed response characteristics such as rise time, overshoot, and settling time are compared for ST-TS and TS. It was shown that ST-TS has optimum results compared to the standard TS. The significance of the proposed method is that, optimum computational burden reduction is achieved.</span>

CMOS CIRCUIT DESIGN OF A TAKAGI-SUGENO FUZZY LOGIC CONTROLLER

2009 ◽  
Vol 18 (04) ◽  
pp. 841-856
Author(s):  
WEIWEI SHAN ◽  
YAN LIANG ◽  
DONGMING JIN
Keyword(s):  
Fuzzy Logic ◽  
Low Power ◽  
Integrated Circuit ◽  
High Speed ◽  
Fuzzy Logic Controller ◽  
Fuzzy Controller ◽  
High Accuracy ◽  
Real Time Control ◽  
Chip Area ◽  
Takagi Sugeno

This paper presents a low power CMOS analog integrated circuit of a Takagi–Sugeno fuzzy logic controller with voltage/voltage interface, small chip area, relatively high accuracy and medium speed, which is composed of several improved functional blocks. Z-shaped, Gaussian and S-shaped membership function circuits with compact structures are designed, performing well with low power, high speed and small areas. A current minimization circuit is provided with high accuracy and high speed. A follower-aggregation defuzzification block composed of several multipliers for center of gravity (COG) defuzzification is presented without using a division circuit. Based on these blocks, a two-input one-output singleton fuzzy controller with nine rules is designed under a CMOS 0.6 μm standard technology provided by CSMC. HSPICE simulation results show that this controller reaches an accuracy of ±3% with power consumption of only 3.5 mW (at ±2.5 V). The speed of this controller goes up to 0.625M Fuzzy Logic Inference per Second (FLIPS), which is fast enough for real-time control.

scholarly journals Design of Fuzzy TS-PDC Controller for Electrical Power System via Rules Reduction Approach

Symmetry ◽  
2020 ◽  
Vol 12 (12) ◽  
pp. 2068
Author(s):  
Badr Alshammari ◽  
Rim Ben Salah ◽  
Omar Kahouli ◽  
Lioua Kolsi
Keyword(s):  
Fuzzy Logic ◽  
Power Systems ◽  
Power System ◽  
Fuzzy Logic Controller ◽  
Electrical Power ◽  
Linearization Method ◽  
System Stability ◽  
Linear Matrix ◽  
Electrical Power System ◽  
Takagi Sugeno

In this paper, a new Takagi–Sugeno Fuzzy Logic controller (TS-FLC) is presented and applied for modeling and controlling the nonlinear power systems even in the presence of disturbances. Firstly, a nonlinear mathematical model for the electrical power system is presented with consideration of PSS and AVR controller. Then, a Takagi–Sugeno Fuzzy Logic controller is employed to control power system stability. Nevertheless, the study of the stability of Takagi–Sugeno fuzzy models will be difficult in the case where the number of nonlinearities is important. To cope with this problem, this study proposed a methodology to reduce the number of rules and to guarantee the global stability of the power system. The new model included only two rules. All the other nonlinearities were considered as uncertainties. In addition, a Parallel Distributed Compensation controller is designed using the Linear Matrix Inequalities constraints in order to guarantee system stability. Finally, this approach is applied on a Single Machine Infinite Bus affected by fault perturbation. To show the novelty of Takagi Sugeno’s method, we compared our approach to the Taylor linearization method. The numerical simulations prove the feasibility and performance of the proposed method.

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