Fuzzy neural network-based rotational speed control of ultrasonic motor

A technology of fuzzy neural network and ultrasonic motor, applied in the direction of piezoelectric effect/electrostrictive or magnetostrictive motor, generator/motor, electrical components, etc., can solve the unstable operation of ultrasonic motor speed fluctuation and cannot guarantee Ultrasonic motor speed tracking dynamic control performance and other issues, to achieve the effect of strong global search optimization performance, good local fast search ability, and high adjustment accuracy

Inactive Publication Date: 2018-04-17
WUXI OPEN UNIV
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Problems solved by technology

However, when the above methods are adopted, the problem of large fluctuations in the speed of the ultrasonic motor and unstable operation cannot

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  • Fuzzy neural network-based rotational speed control of ultrasonic motor
  • Fuzzy neural network-based rotational speed control of ultrasonic motor
  • Fuzzy neural network-based rotational speed control of ultrasonic motor

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Embodiment Construction

[0026] Below in conjunction with accompanying drawing and embodiment, the present invention is further explained in detail, mainly from five aspects such as ultrasonic motor speed control system, fuzzy neural network controller, optimization of fuzzy neural network controller structural parameters, simulation analysis and experimental verification etc. introduce.

[0027] 1. Ultrasonic motor speed control system

[0028] figure 1 It is a schematic diagram of the principle of the ultrasonic motor speed control system. The speed tracking target of the motor is set by the speed reference model, which can be constant speed, step speed, etc. The motor stator vibration signal detection unit is introduced in the inner loop of the system speed control to enhance the speed tracking accuracy of the USM and improve the speed response of the USM. The function of the fuzzy neural network (that is, FNN) controller in the control principle structure is to control the speed of the ultrason...

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Abstract

The invention discloses an ant colony-particle swarm hybrid algorithm optimized fuzzy neural network-based speed control model of an ultrasonic motor. An ant colony algorithm and a particle swam algorithm form a master-slave hierarchical structure optimized fuzzy neural network, a structural parameter of a fuzzy neural network controller is optimized by employing a global searching function of theant colony algorithm and a local searching function of the particle swam algorithm, the controller is introduced to a rotational speed control system of the ultrasonic motor, and adaptability and theintelligence of speed control of the ultrasonic motor are achieved. Simulation analysis and experiment result show that by employing an ant colony-particle swarm hybrid algorithm optimized fuzzy neural network-based speed control strategy, the adaptive tracking of the system on speed of the ultrasonic motor can be achieved, and the speed control model is small in speed pulse, high in adjustment accuracy, good in dynamic performance and high in interference-resistant capability and robustness.

Description

technical field [0001] The invention relates to a speed control of an ultrasonic motor, in particular to a speed control method of an ultrasonic motor based on an ant colony-particle swarm hybrid algorithm to optimize a fuzzy neural network, and belongs to the field of computer application and automatic control. Background technique [0002] Ultrasonic motor (USM) is a kind of miniature driving motor developed at the end of the 20th century. Compared with the traditional electromagnetic motor, the ultrasonic motor has the characteristics of compact structure, small size, light weight, micro displacement, low speed, high torque, noiseless operation, no electromagnetic interference, low temperature resistance, etc., which can be described as an ideal Servo-driven actuators have been widely used in aerospace, medical equipment, precision micro-motion mechanisms, office automation, robot industry, high-end automobiles, military and industrial control and other fields. Due to th...

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Application Information

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IPC IPC(8): H02N2/14
CPCH02N2/142
Inventor 乔维德
Owner WUXI OPEN UNIV
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