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lqr optimized brushless dc motor speed regulation neural network pid controller

A technology of brushed DC motors and DC motors, applied in electric controllers, controllers with specific characteristics, motors, etc., can solve problems such as robustness to be improved, and achieve improved dynamic characteristics and robustness, strong nonlinearity Mapping ability, suppressing the effect of non-linear cases

Active Publication Date: 2022-05-31
CHANGCHUN UNIV OF TECH
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Although the LQR optimized PID controller has good tracking performance and stable performance, its robustness needs to be improved

Method used

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  • lqr optimized brushless dc motor speed regulation neural network pid controller
  • lqr optimized brushless dc motor speed regulation neural network pid controller
  • lqr optimized brushless dc motor speed regulation neural network pid controller

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Embodiment Construction

[0027] O

[0030] O

[0034] W

[0035] W

[0037] S4: the final control output is input into the brushless DC motor system to realize speed control.

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Abstract

The invention designs an LQR optimized brushless DC motor speed regulating neural network PID controller, which is used to improve the control performance of the traditional neural network PID controller and the traditional LQR optimized PID controller. The designed LQR optimized neural network PID controller (LNPID) uses BP neural network to control the K of the controller P , K I , K D The gain is adjusted to improve the dynamic characteristics and robustness of the controller; the three-layer BP neural network adopted in the present invention has strong nonlinear mapping ability, and can effectively suppress the nonlinear situation of the controlled object; but the traditional BP Neural network is an optimization method of local search, therefore, the present invention quotes LQR control algorithm to optimize the optimal output of BP neural network, so that the output data is closer to the target PID gain; finally, the control output value of the controller is input to the brushless DC In the motor, the speed control of the motor is achieved. At the same time, LNPID is used to continuously monitor the changes of parameters and the real-time feedback of parameters, so that the control effect can be idealized.

Description

LQR-optimized brushless DC motor speed-regulating neural network PID controller technical field The invention belongs to the technical field of brushless direct current motor speed regulation, be specifically related to a kind of LQR optimization type brushless direct current motor Speed-regulated neural network PID controller. Background technique [0002] The brushless DC motor has the advantages of simple structure, high efficiency, low maintenance cost and high dynamic response. Aerospace, robotics, electric vehicles and other fields have been widely used. As we all know, speed control is a brushless DC motor drive an important aspect of the field of motion. With the development of modern power electronics technology, sensor technology, automatic control technology and manufacturing technology With continuous and rapid development, the speed control controller of brushless DC motor with fast response speed, strong adjustment ability and high control precision has...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G05B11/42
CPCG05B11/42Y02T10/64
Inventor 胡黄水王婷婷杨兴旺韩优佳韩博
Owner CHANGCHUN UNIV OF TECH
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