Multi-mode ultrasonic motor driving control system

Abstract

The invention discloses a multi-mode ultrasonic motor driving control system, which comprises a DSP microprocessor, DDS chips, low-pass filters, programmable gain amplifiers, power amplification circuits and a transformer. The DSP microprocessor synchronously outputs two channels of frequency and phase control word sinusoidal signals which are input to the two DDS chips. Two sinusoidal voltages are produced after the signals pass through the low-pass filters. The two sinusoidal voltages are amplified to V-level AC voltage signals by the programmable gain amplifiers, and are then connected to the power amplification circuits. Finally, power matching is realized by push-pull of the transformer. The phase and frequency modulation accuracy of the driving system is improved by taking advantageof high precision of the dual DDSs. Tests show that the frequency adjustment range of the driver is from 20kHz to70kHz, the phase error is less than 0.1 degree, the resolution is lower than 0.1Hz andthe output power is 500W.

Description

technical field [0001] The invention relates to an ultrasonic motor drive control system. Background technique [0002] The development of instrument science, power electronics and control disciplines and technologies has improved the practical research and production of ultrasonic motor drive control technology and its control equipment. [0003] Fazel Bazrafshan et al. studied a typical rotating traveling wave ultrasonic motor, and proposed a fuzzy Hammerstein nonlinear model structure, which consists of a static fuzzy model connected in series with a linear dynamic model. The Hammerstein model can be integrated into standard linear generalized predictive controllers. H.Zhu et al. proposed a piezoelectric finite element dynamic model, which can be used to solve the dynamic characteristics of piezoelectric actuators with complex geometries. Frédéric Giraud et al proposed a position control driven by a traveling wave ultrasonic motor as an inertial load. The proposed cont...

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Problems solved by technology

In 2007, Fu Ping and Guo Jifeng proposed neuron PID control, which is a variable parameter control method, which uses a neuron to complete PID control, and uses the online learning algorithm of neural network to realize the dynamic adjustment of control parameters; in 2009, He Honglin , Zhu Hua, Zhao Chunsheng, etc. used the genetic algorithm to optimize the parameters of the PI controller online. The optimization process aims to minimize the position deviation, which can compensate the nonlinear and time-varying characteristics of the ultrasonic motor to a certain extent; however, the random characteristics of the genetic algorithm, and The trade-off between the amount of online calculation and the real-time control and time-varying tracking ability will affect the effect

The fuzzy neural network control strategy and the fuzzy control strategy also need a knowledge base established through a large amount of experimental data, which requires a long time

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