Robust sliding mode speed control with fuzzy approach for induction motors

Abstract

The main purpose of this paper is to apply the nonlinear sliding-mode control combined with fuzzy logic approach to the speed control of induction motor. O u r proposed method can achieve very robust and satisfactory performance and could be used to get the desired performance levels. The response time was also very fast despite the fact that the control strategy was based on bounded rationality. To evaluate the usefulness of the proposed method, we compare the response of this method with Fuzzy PD controller. The simulation results show that our method has the better control performance than Fuzzy PD controller.

Application of fuzzy neural network in the speed control system of induction motor

“…Sensorless control of induction motor drives is now receiving wide attention. However, due to the high order and nonlinearity of the dynamics of an induction motor, estimation of the angle speed and rotor flux without the measurement of mechanical variables becomes a challenging problem [3]. The advantages of speed sensorless induction motor derives are reduced hardware complexity and lower cost, reduce size of derive machine, eliminate of sensor cable, better noise immunity, increasing reliability and less maintenance requirements [4].…”

“…Various speed control algorithms for induction motor derives have been devised in the literature. Among them, PID controllers [5], optimal [6], nonlinear [7,8] and robust [9,10] control strategies, and neural and/or fuzzy [3,11] approaches are to be mentioned. The purpose of this paper is to suggest another control approach, based on adaptive FNN controller to achieve faster response with reduced overshoot and rise time.…”

Sensorless speed control of induction motor derives using a robust and adaptive neuro-fuzzy based intelligent controller

“…The mechanical parameters (J, B) can not always be obtained accurately and they may also vary during the induction motor operation. However, the uncertainties on the mechanical parameters can be well handled by the process of load torque estimation [3]. Thus in this section only the test under electrical parameter variations is done here.…”

“…Various speed control algorithms for induction motor derives have been devised in the literature. Among them, PID controllers [5], optimal [6], nonlinear [7,8] and robust [9,10] control strategies, and neural and/or fuzzy [3,11] approaches are to be mentioned. The purpose of this paper is to suggest another control approach, based on adaptive neurofuzzy controller to achieve faster response with reduced overshoot and rise time.…”

“…In a hostile environment, speed sensors can not even be mounted. However, due to the high order and nonlinearity of the dynamics of an induction motor, estimation of the angle speed and rotor flux without the measurement of mechanical variables becomes a challenging problem [3]. The advantages of speed sensorless induction motor derives are reduced hardware complexity and lower cost, reduce size of derive machine, eliminate of sensor cable, better noise immunity, increasing reliability and less maintenance requirements [4].…”