Optimized neuro PI based speed control of sensorless induction motor

  • Authors:
  • R. Arulmozhiyal;C. Deepa;Kaliyaperumal Baskaran

  • Affiliations:
  • Department of EEE, Sona college of Technology, Salem, Tamil Nadu, India;Department of EEE, NPR College of Engineering and Technology, Dindigul, Tamil Nadu, India;Department of CSE, Government College of Technology, Coimbatore, Tamil Nadu, India

  • Venue:
  • SEMCCO'11 Proceedings of the Second international conference on Swarm, Evolutionary, and Memetic Computing - Volume Part II
  • Year:
  • 2011

Quantified Score

Hi-index 0.00

Visualization

Abstract

In this paper a sensorless vector control system of induction motor using Neural Networks is presented. Neural network is used to control the non linear dynamic systems to get desired degree of accuracy. A feed forward neural network with one input, two units in the hidden layer and one output is used for the speed controller. The tracking of the rotor speed is done by a neural PI controller and is realized by adjusting the new weights of the network depending on the difference between the actual speed and the command speed. The use of the controller tracks the rotor speed command smoothly and rapidly, without overshoot and with zero steady state error without the sensor. GA has been recognized as an effective and efficient technique to solve optimization problems. Finally this controller can be optimized using a Genetic Algorithm Technique. When compared to Neuro PI controller Genetic Algorithm produces better performance. Computer simulation results are carried out with various tool boxes in MATLAB to verify the effectiveness of the proposed controller. The result concludes that the efficiency and reliability of the proposed speed controller is good.