DOI QR코드

DOI QR Code

Optimization of PI Controller Gain for Simplified Vector Control on PMSM Using Genetic Algorithm

  • Jeong, Seok-Kwon (Department of Refrigeration and Air-Conditioning Engineering, Pukyong National University) ;
  • Wibowo, Wahyu Kunto (Department of Interdisciplinary Program of Mechatronics Engineering, Pukyong National University)
  • 투고 : 2012.12.26
  • 심사 : 2013.09.17
  • 발행 : 2013.10.31

초록

This paper proposes the used of genetic algorithm for optimizing PI controller and describes the dynamic modeling simulation for the permanent magnet synchronous motor driven by simplified vector control with the aid of MATLAB-Simulink environment. Furthermore, three kinds of error criterion minimization, integral absolute error, integral square error, and integral time absolute error, are used as objective function in the genetic algorithm. The modeling procedures and simulation results are described and presented in this paper. Computer simulation results indicate that the genetic algorithm was able to optimize the PI controller and gives good control performance of the system. Moreover, simplified vector control on permanent magnet synchronous motor does not need to regulate the direct axis component current. This makes simplified vector control of the permanent magnet synchronous motor very useful for some special applications that need simple control structure and low cost performance.

키워드

참고문헌

  1. H. Chaoui and P. Sicard, 2010, "Adaptive Lyapunov-based Neural Network Sensorless Control of Permanent Magnet Synchronous Machines", Neural Computing and Applications, Vol. 20, No. 5, pp. 717-727.
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피인용 문헌

  1. Improvement on Sensorless Vector Control Performance of PMSM with Sliding Mode Observer vol.18, pp.5, 2014, https://doi.org/10.9726/kspse.2014.18.5.129