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10 July 2009 Induction machine Direct Torque Control system based on fuzzy adaptive control
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Proceedings Volume 7490, PIAGENG 2009: Intelligent Information, Control, and Communication Technology for Agricultural Engineering; 74900E (2009) https://doi.org/10.1117/12.836640
Event: International Conference on Photonics and Image in Agriculture Engineering (PIAGENG 2009), 2009, Zhangjiajie, China
Abstract
Direct Torque Control technology is a high-performance communication control method, it uses the space voltage vector method, and then to the inverter switch state control, to obtain high torque dynamic performance. But none of the switching states is able to generate the exact voltage vector to produce the desired changes in torque and flux in most of the switching instances. This causes a high ripple in torque. To solve this problem, a fuzzy implementation of Direct Torque Control of Induction machine is presented here. Error of stator flux, error of motor electromagnetic torque and position of angle of flux are taken as fuzzy variables. In order to further solve nonlinear problem of variation parameters in direct torque control system, the paper proposes a fuzzy parameter PID adaptive control method which is suitable for the direct torque control of an asynchronous motor. The generation of its fuzzy control is obtained by analyzing and optimizing PID control step response and combining expert's experience. For this reason, it carries out fuzzy work to PID regulator of motor speed to achieve to regulate PID parameters. Therefore the control system gets swifter response velocity, stronger robustness and higher precision of velocity control. The computer simulated results verify the validity of this novel method.
© (2009) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Shi-ping Li, Yan Yu, Zhen-gang Jiao, and Shu-sheng Gu "Induction machine Direct Torque Control system based on fuzzy adaptive control", Proc. SPIE 7490, PIAGENG 2009: Intelligent Information, Control, and Communication Technology for Agricultural Engineering, 74900E (10 July 2009); https://doi.org/10.1117/12.836640
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