Recurrent neural network control for LCC-resonant ultrasonic motor drive

A newly designed driving circuit for the traveling wave-type ultrasonic motor (USM), which consists of a push-pull DC-DC power converter and a two-phase voltage source inverter using one inductance and two capacitances (LCC) resonant technique, is presented in this study. Moreover, because the dynam...

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Bibliographic Details
Published in:IEEE transactions on ultrasonics, ferroelectrics, and frequency control ferroelectrics, and frequency control, 2000-05, Vol.47 (3), p.737-749
Main Authors: LIN, F.-J, WAI, R.-J, HONG, C.-M
Format: Article
Language:English
Subjects:
Algorithms
Applied sciences
Capacitance
Control systems
DC-DC power converters
Dynamical systems
Dynamics
Electrical engineering. Electrical power engineering
Electrical machines
Exact sciences and technology
Inductance
Induction motors
Inverters
Motors
Recurrent neural networks
Regulation and control
Resonance
RLC circuits
Tracking errors
Trains
Voltage
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Summary:A newly designed driving circuit for the traveling wave-type ultrasonic motor (USM), which consists of a push-pull DC-DC power converter and a two-phase voltage source inverter using one inductance and two capacitances (LCC) resonant technique, is presented in this study. Moreover, because the dynamic characteristics of the USM are difficult to obtain and the motor parameters are time varying, a recurrent neural network (RNN) controller is proposed to control the USM drive system. In the proposed controller, the dynamic backpropagation algorithm is adopted to train the RNN on-line using the proposed delta adaptation law. Furthermore, to guarantee the convergence of tracking error, analytical methods based on a discrete-type Lyapunov function are proposed to determine the varied learning rates for the training of the RNN. Finally, the effectiveness of the RNN-controlled USM drive system is demonstrated by some experimental results.
ISSN:0885-3010
1525-8955
DOI:10.1109/58.842063