Ultrasonic motor adaptability recursive neural network control system

Abstract

The invention relates to an ultrasonic motor adaptability recursive neural network control system, comprising a base and an ultrasonic motor arranged thereon, wherein an output shaft on one side of the ultrasonic motor is connected with a photoelectric encoder, an output shaft on the other side of the ultrasonic motor is connected with a flywheel inertia load, an output shaft of the flywheel inertia load is connected with a torque sensor through a coupling, and the signal output ends of the photoelectric encoder and the torque sensor are respectively connected to a control system. The control system is composed of an adaptability recursive neural network controller and a motor, a recursive neural network is used for estimating an unknown dynamic function, and the adaptability learning law of recursive neural network parameters is obtained by the Lyapunov stability theorem. The ultrasonic motor adaptability recursive neural network control system is high in control accuracy, simple and compact in structure and good in using effect.

Description

technical field [0001] The invention relates to the field of motor controllers, in particular to an adaptive recursive neural network control system for ultrasonic motors. Background technique [0002] In the existing ultrasonic motor recursive neural network control system, when the rotor position of the motor starts to deviate from the reference command, the recursive neural network will automatically adjust the input frequency as the error increases to affect the control current. When the controlled system has parameter changes and external load interference, the error-driven recursive neural network controller will reduce the influence of the above two factors on the following performance of the controlled system. Therefore, the position and speed control of the motor can obtain better dynamic characteristics. Contents of the invention [0003] The object of the present invention is to provide an adaptive recursive neural network control system for an ultrasonic motor...

AI Technical Summary

Problems solved by technology

[0002] In the existing ultrasonic motor recursive neural network control system, when the motor rotor position starts to deviate from the reference command, the recursive neural network will automatically adjust the input frequency with the increase of the error to affect the control current

When the controlled system has parameter changes and external load disturbances, this error-driven recursive neural network controller will reduce the impact of the above two on the following performance of the controlled system

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