GA-neural network based position control of Traveling Wave Ultrasonic Motor

Jahani, Mohammad; Mojallali, Hamed

doi:10.1109/iccet.2010.5486191

Cited by 3 publications

(1 citation statement)

References 7 publications

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“…These methods are based on the electromagnetic motor model, but the motor model used for performance estimation of the ultrasonic motor is very complicated due to the nonlinear characteristics of the ultrasonic motor, so the speed sensorless control method based on the motor model is not practical for the ultrasonic motor [ 16 ]. To achieve speed sensorless control of the ultrasonic motor, some algorithms based on neural networks, such as recurrent fuzzy neural network [ 17 ] and genetic neural network [ 18 ], have good performance. Because the neural network has good nonlinear identification ability, it can effectively predict the relationship between the input variables and speed of the ultrasonic motor.…”

Section: Introductionmentioning

confidence: 99%

Speed Sensorless Control of Linear Ultrasonic Motors Based on Stator Vibration Amplitude Compensation

Yan

Yang

et al. 2020

Sensors

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In some applications of linear ultrasonic motors (LUSMs), not installing speed/position sensors can reduce the size and cost of the system, changes in load will cause fluctuations in the speed of the LUSM. To eliminate the influence of load changes on speed, a speed sensorless control scheme based on stator vibration amplitude compensation (SSCBVC) is proposed. This scheme is implemented under the framework of the stator vibration amplitude-based speed control (VBSC) and frequency tracking. Based on the stator vibration amplitude-speed and the output force-speed curves of the LUSM, the relationship between the load changes and stator vibration amplitude (SVA) to be compensated is established, realizing a speed sensorless control of the LUSM under variable load conditions. The experimental results show that the maximum fluctuation of the speed is about 2.2% when the output force changes from 0 to 6 N with SSCBVC. This scheme can effectively reduce the influence of load changes on the speed of the LUSM without using speed/position sensors.

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Section: Introductionmentioning

confidence: 99%