Motor control method based on self-learning of rotating speed-current two-dimensional fuzzy model

A fuzzy model and motor control technology, applied in the direction of single motor speed/torque control, etc., can solve problems such as inability to balance stability and rapidity, and no self-learning ability

Active Publication Date: 2015-01-07
南通创达机械有限公司
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Problems solved by technology

[0005] In order to overcome the shortcomings of the existing motor control methods that cannot balance stability and rapidity and have no self-learning ability, the present invention provides

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  • Motor control method based on self-learning of rotating speed-current two-dimensional fuzzy model
  • Motor control method based on self-learning of rotating speed-current two-dimensional fuzzy model
  • Motor control method based on self-learning of rotating speed-current two-dimensional fuzzy model

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Embodiment Construction

[0044] The present invention will be further described below in conjunction with the accompanying drawings.

[0045] refer to Figure 1 ~ Figure 4 , a motor control method based on speed-current two-dimensional fuzzy model self-learning, comprising the following steps:

[0046] Such as figure 1 Shown is a schematic structural diagram of the control system described in this patent. Overall, it includes double closed-loop feedback controller, fuzzy model feedforward controller and hardware system.

[0047]The double-closed-loop feedback controller is composed of an outer-loop angular velocity PI controller and an inner-loop current PI controller, and the input is the target angular velocity w t , measured angular velocity w s and the sampling current i s , the output is the feedback duty cycle d b ;Specific steps are as follows:

[0048] (1.1) According to the measured angular velocity w of the motor obtained by the Hall sensor at time t s (t) and the target speed value ...

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Abstract

The invention provides a motor control method based on self-learning of a rotating speed-current two-dimensional fuzzy model. The method comprises the following steps that (1) the dual closed-loop feedback control process is performed to obtain a feedback duty ratio db(t); (2) the feedforward control process of the fuzzy model is performed, wherein mapping of a current grid point p (including speed and current) on a fuzzy curve model S is performed, information of four top points is obtained, and the feedforward duty ratio corresponding to the point p is obtained according to membership and a gravity method; (3) the self-learning process is performed, wherein the feedforward duty ratio of the grid point p at the time (t-1) is amended according to the speed error at the time t, and the information of the four top points around the point p is amended according to the membership and a counter-gravity method. The method effectively gives consideration to stability and rapidness, and is good in self-learning capacity.

Description

technical field [0001] The invention relates to a motor control method. Background technique [0002] Compared with ordinary motors, brushless DC motors have obvious advantages such as high efficiency and small size, and at the same time have the advantages of stepless speed regulation. Today, when energy saving and environmental protection are greatly advocated, they are widely used in many fields. The algorithm proposed in this paper is obtained in the development process of the DC brushless servo drive for industrial sewing machines, and can be widely used in various occasions with wide speed, variable speed and variable load. [0003] In the application process of DC brushless motor, one of the core issues is the design of the driver, and the core technology of the driver mainly includes hardware circuit design and software control algorithm design. Among them, the software control algorithm currently widely used in the market is the speed outer loop based on the PID co...

Claims

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Application Information

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IPC IPC(8): H02P6/06
CPCH02P6/06
Inventor 吴乐彬
Owner 南通创达机械有限公司
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