An error driven hybrid neuro-fuzzy torque/speed controller for electrical vehicle induction motor drive

2005 ◽  
Author(s):  
G. El-Saady ◽  
A.M. Sharaf ◽  
A.M. Makky ◽  
M.K. El-Sherbiny ◽  
G. Mohamed
Keyword(s):  
Induction Motor ◽  
Motor Drive ◽  
Induction Motor Drive ◽  
Speed Controller ◽  
Neuro Fuzzy ◽  
Electrical Vehicle

Performance analysis of the sensorless adaptive sliding-mode neuro-fuzzy control of the induction motor drive with MRAS-type speed estimator

2012 ◽  
Vol 60 (1) ◽  
pp. 61-70 ◽  
Author(s):  
T. Orlowska-Kowalska ◽  
M. Dybkowski
Keyword(s):  
Induction Motor ◽  
Sliding Mode ◽  
Motor Drive ◽  
Induction Motor Drive ◽  
Adaptive Sliding Mode ◽  
Speed Controller ◽  
Neuro Fuzzy ◽  
On Line ◽  
Speed Estimator ◽  
Model Reference Adaptive

Performance analysis of the sensorless adaptive sliding-mode neuro-fuzzy control of the induction motor drive with MRAS-type speed estimator This paper discusses a model reference adaptive sliding-mode control of the sensorless vector controlled induction motor drive in a wide speed range. The adaptive speed controller uses on-line trained fuzzy neural network, which enables very fast tracking of the changing speed reference signal. This adaptive sliding-mode neuro-fuzzy controller (ASNFC) is used as a speed controller in the direct rotor-field oriented control (DRFOC) of the induction motor (IM) drive structure. Connective weights of the controller are trained on-line according to the error between the actual speed of the drive and the reference model output signal. The rotor flux and speed of the vector controlled induction motor are estimated using the model reference adaptive system (MRAS) - type estimator. Presented simulation results are verified by experimental tests performed on the laboratory-rig with DSP controller.

scholarly journals Self-Tuning Speed Controller of the Induction Motor Drive

2014 ◽  
Vol 20 (6) ◽  
Author(s):  
J. Kriauciunas ◽  
R. Rinkeviciene ◽  
A. Baskys
Keyword(s):  
Induction Motor ◽  
Motor Drive ◽  
Induction Motor Drive ◽  
Speed Controller ◽  
Self Tuning

scholarly journals Sensorless Rotor-Field Oriented Controlled Induction Motor Drive with Particle Swarm Optimization Algorithm Speed Controller Design Strategy

2014 ◽  
Vol 2014 ◽  
pp. 1-13 ◽  
Author(s):  
Yung-Chang Luo ◽  
Zhi-Sheng Ke ◽  
Ying-Piao Kuo
Keyword(s):  
Particle Swarm Optimization ◽  
Induction Motor ◽  
Optimization Algorithm ◽  
Particle Swarm Optimization Algorithm ◽  
Controller Design ◽  
Particle Swarm ◽  
Motor Drive ◽  
Induction Motor Drive ◽  
Swarm Optimization ◽  
Speed Controller

A sensorless rotor-field oriented control induction motor drive with particle swarm optimization algorithm speed controller design strategy is presented. First, the rotor-field oriented control scheme of induction motor is established. Then, the current-and-voltage serial-model rotor-flux estimator is developed to identify synchronous speed for coordinate transformation. Third, the rotor-shaft speed on-line estimation is established applying the model reference adaptive system method based on estimated rotor-flux. Fourth, the speed controller of sensorless induction motor drive is designed using particle swarm optimization algorithm. Simulation and experimental results confirm the effectiveness of the proposed approach.

Takagi-Sugeno Fuzzy Perpose as Speed Controller in Indirect Field Oriented Control of Induction Motor Drive

2017 ◽  
Vol 8 (2) ◽  
pp. 513
Author(s):  
Roslina Mat Ariff ◽  
Dirman Hanafi ◽  
Wahyu Mulyo Utomo ◽  
Nooradzianie Muhammad Zin ◽  
Sy Yi Sim ◽  
...  
Keyword(s):  
Induction Motor ◽  
Fuzzy Logic Control ◽  
High Performance ◽  
Motor Drive ◽  
Field Oriented Control ◽  
Induction Motor Drive ◽  
Speed Controller ◽  
Logic Control ◽  
Indirect Field Oriented Control ◽  
Takagi Sugeno

This paper deal with the problem in speed controller for Indirect Field Oriented Control of Induction Motor.  The problem cause decrease performance of Induction Motor where it widely used in high-performance applications. In order decrease the fault of speed induction motor, Takagi-Sugeno type Fuzzy logic control is used as the speed controller. For this, a model of indirect field oriented control of induction motor is built and simulating using MATLAB simulink. Secondly, error of speed and derivative error as the input and change of torque command as the output for speed control is applied in simulation. Lastly, from the simulation result overshoot is zero persent, rise time is 0.4s and settling time is 0.4s. The important data is steady state error is 0.01 percent show that the speed can follow reference speed. From that simulation result illustrate the effectiveness of the proposed approach.

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