Work place: Hunan Province Cooperative Innovation Center for Wind Power Equipment and Energy Conversion
E-mail: 185181173@qq.com
Website:
Research Interests: Engineering
Biography
ZhangCheng Dong was born in Shandong, on Nov. 18, 1988. He received the B.E. degree in electrical engineering from Shandong University of Technology, Zibo, Shandong, in 2013. He is currently working toward the M.S. degree at Xiangtan University, Xiangtan, Hunan. His major field of study including intelligent algorithm and intelligent control, energy storage technology of the new energy electric car.
By Lingzhi Yi Chengdong Zhang Genping Wang
DOI: https://doi.org/10.5815/ijisa.2017.03.08, Pub. Date: 8 Mar. 2017
The Permanent Magnet Synchronous Motor has been applying widely due to it’s high efficiency, high reliability, relatively low cost and low moment of inertia. However, the PMSM drives are easily affected by the uncertain factors such as the variation of motor parameters and load disturbance. In order to realize the control of the PMSM accurately, a novel adaptive chaotic kinetic molecular theory optimization algorithm was implemented for seeking the best parameters of PID controller. In the PMSM vector control system, the speed loop will be adjusted by a CKMTOA PID controller. In modified kinetic molecular theory optimization algorithm, the adaptive inertia weight factors are used to accelerate the convergence speed, and chaotic searching is conducted within the neighbor set of the solutions to avoid the local minima. The model of PMSM and its` space vector control system are set up in the software of MATLAB/Simulink. The effectiveness of the self-tuning CKMTOA PID controller is verified by comparing with the conventional PID and particle swarm optimization algorithm. The extensive simulations and analysis also show the effectiveness of the proposed approach.
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