Adaptive Neuro Fuzzy Based Maximum Torque Control of Three Phase Induction Motor

Author Name(s): G.Srikanth, Dr.G.Madhusudhan Rao
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Abstract

This paper manages the Maximum Torque Control of IM drives utilizing ANFIS. In modern control hypothesis, the IM is depicted by various arithmetical models, as per the engaged control technique. The proposed approaches straightforwardly direct the machine stator flux as indicated by the desirable torque, utilizing an optimal stator flux reference. In this manner, the proposed technique is appropriate for motor control conspires that depend on coordinate motion control, for example, coordinate torque control or direct torque vector control. Utilizing ANFIS, especially the neural systems, execution and operation of acceptance IM is progressed. This paper presents ANFIS based MTC of Three-phase IM. The execution of the intellectual controller has been examined through MATlab/Simulink condition, for various operational conditions. At last, the outcomes are watched that ANFIS based controllers give preferable reactions over alternate controllers

Introduction

For any machine we expect less error, most extreme output for that we have to control the torque. In three phases IM the maximum torque control can be accomplished in various techniques. The controlling of most extreme torque should be possible in customary controllers, for example, corresponding controller, relative in addition to essential controller however these are particularly helpful in steady state and for linear systems. In any case, the P, PI controller has primary disfavor is tuning of parameters Kp,Ki,Kd,Td,Ti (and also other problems like the high starting overshoot, sensitivity to controller gains and sluggish response due to sudden disturbance) In about the same period, there were also advances in control methods and Artificial Intelligence (AI) techniques.. Artificial Intelligent strategies mean utilization of master framework, fluffy rationale, neural systems and hereditary calculation. Experts soon understood that the control of IM drives can be improved by receiving automated interpretation based techniques like The Artificial Intelligence (AI) methods, for example, Expert System (ES), Fuzzy Logic (FL), Artificial Neural Network (ANN), and Genetic Algorithm (GA) have been connected broadly responsible for Control of IM drives. Among all the branches of AI, the ANFIS appears to have more significant effect on Power electronics and IM Drives.

Conclusion

The maximum torque of the three -phase induction motor is attaining by means of the ANFIS and the responses are evaluated with the PI controller it has been observed that the ripple substance and the robust response to the sudden changes are reduced. the simulation speed increases even with respect to the customary controller. From the results of the simulation we can see that the performance of the drive is improved for a shorter acceleration time and maximum torque is reached. The performance of ANFIS has been studied through the MATLAB / Simulink environment. From the results we can see that when using ANFIS (back propagation algorithm) the response of the induction motor in terms of time domain specifications is better than using the PI controller.

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