Abstract
AbstractAiming at the problems of the poor adaptive ability in the current control methods for brushless DC motor, an adaptive fuzzy proportional integral derivative controller (AFPID) is proposed to realize the better control performance of speed for brushless DC motor. AFPID includes a conventional PID controller (C-PID) and PI + PD architectures with a configurable fuzzy logic controller (C-PID-FLC). The FLC in C-PID-FLC consists of two fuzzy inference engines, one is used to self-tune the parameters for PI control, the other is for the scaling factor self-tuning of PI control parameters. The PD structure in C-PID-FLC is mainly to reduce oscillation, overcome overshoot and speed up system response while effectively eliminating static errors. When the system reaches a certain stable state of rotation, AFPID adjusts the C-PID controller ground on the speed error, which saves control costs under the premise of ensuring control performance. AFPID adaptively realizes the respective advantages of C-PID and C-PID-FLC. Compared with other control methods, the merits of the proposed controller are highlighted. The results show that the AFPID controller has a better control performance regardless of changes in load disturbance and parameter variations. And through the change of mechanical parameters of brushless DC motor, the sensitivity of AFPID is analyzed.
Funder
Jilin Scientific and Technological Development Program
National Outstanding Youth Science Fund Project of National Natural Science Foundation of China
Publisher
Springer Science and Business Media LLC
Subject
General Earth and Planetary Sciences,General Physics and Astronomy,General Engineering,General Environmental Science,General Materials Science,General Chemical Engineering
Cited by
8 articles.
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