Title page for etd-0801115-141949


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URN etd-0801115-141949
Author Chien-Yu Chen
Author's Email Address cameron6107@hotmail.com
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Department Mechanical and Electro-Mechanical Engineering
Year 2014
Semester 2
Degree Master
Type of Document
Language zh-TW.Big5 Chinese
Title Online Self-Tuning PSO Algorithm for PMSM Controller Design
Date of Defense 2015-07-21
Page Count 97
Keyword
  • Proportional-integral controller
  • Digital signal processor
  • Permanent magnet synchronous motor
  • Self-tuning control
  • Particle swarm optimization algorithm
  • Abstract In order to make the motors have better transient response and steady state performance, the systems usually adopt closed loop control. The system have difference dynamic responses depending on various controller parameter setting. Traditionally, controller parameters are fixed. But in most cases, the motor works with external loads. When the motor is effected by external loads, the structure of internal system will be changed. The original controller parameters are not able to improve the motor dynamic system response effectively. According of this reason, this thesis proposes an online self-tuning particle swarm optimization (PSO) algorithm to deal with this problem. When the system operates under the external loads, it can dynamically adjust the controller parameters of permanent magnet synchronous motors (PMSM) to improve the system response. This method is based on a PSO algorithm for randomly searching controller parameters firstly and then inserting these parameters into the mathematical equations of PMSM to estimate the system dynamic response. The integral absolute error (IAE) is used as the fitness function to compare and determine the optimum fitness value due to adjust the controller parameters. The PMSM will have better transient and steady state responses. We use the simulation software MATLAB/Simulink to verify the design algorithm first. Then using a developed board of TI DSP28069 to carry out the system implementation. The experimental results show that the proposed algorithm can obviously improve the dynamic response of the control system.
    Advisory Committee
  • Chi-Cheng Cheng - chair
  • Tzuen-Lih Chen - co-chair
  • Perng, Jau-Woei - advisor
  • Files
  • etd-0801115-141949.pdf
  • Indicate in-campus at 5 year and off-campus access at 5 year.
    Date of Submission 2015-09-01

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