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Research On The Motor Driver And Control System Of The Linear Ultrasonic Motor

Posted on:2019-03-11Degree:MasterType:Thesis
Country:ChinaCandidate:X D QiFull Text:PDF
GTID:2382330566998262Subject:Mechanical and electrical engineering
Abstract/Summary:PDF Full Text Request
Compared with the traditional Electro-Magnetic motor,the linear ultrasonic motor(Linear-USM)has many advantages,including small volume,high accuracy,high stalling torque and strong adaptive capacity.Also,it can create linear motion directly,avoiding the error created by motion transformation.Thus,the Linear-USM can be used widely and has studied by many scholars.The related driving and control system has a great influence on the performance of the Linear-USM,and the Linear-USM has a complex driving characteristics,which make the research on the driving and control system important.In this paper,a driving and control system of Linear-USM is designed and different control algorithms are introduced,which can improve the performance and accuracy of the Linear-USM.In this paper,the Linear-USM is analyzed and the experiment platform is built,based on which the requirements of the driving and control system is revealed.Next.The circuit of the design and control system is designed,which includes signal generation and control circuit,power amplifier circuit and signal sampling circuit.The signal generation and contro l circuit generate the low voltage control signals,whose main parts are DSP and FPGA systems.The power amplifier circuit amplify the voltage and the power of the control signals,whose main part are operational amplifier circuits.The signal sampling cir cuit sample and transmit the voltage data of the control signals,whose main part are micro-controller and analog-digital converter systems.Next,the software of the driving and control system is designed.The programs in DSP and FPGA are designed to imp lement control algorithms and generate control signals.The program in MCU is designed to control analog-digital converter.Also,the data transmission programs are designed in different chips to achieve communication of controllers and sensors.The circui t of the driving and control system can generate two sinusoidal control signals stably,which have the amplitude between 0V and 500 V,and can work under the frequency of 24 k Hz and under the phase difference of ±90 degree.The amplitude,frequency and phase of the signals can be controlled by the driving and control system,and the resolutions of these three parameters are 7.6m V,0.023 Hz and 0.7°,respectively,which can fulfill the control requirements.After the design and the manufacturing of the driving and control system,different control algorithms are designed and used in the experiments,where the Linear-USM is driven by the driving and control system.First,the PID controller is designed and used in speed control of the Linear-USM.The experiments show that the controller can reduced the speed error of the motor.Next,the fuzzy control system is designed and is used to control the Linear-USM.The experiments show that the fuzzy control system reduces the speed error of the Linear-USM,the speed error following a 100mm/s step single can be controlled within 3mm/s,and it reduces the driving dead-zone when the motor has a sinusoidal movement.Also,in the displacement control,the error can be controlled within 5?m when a 200 mm slope type displacement target is set,which show that the fuzzy control can improve the the Linear-USM's performance.Finally,the neural network control system is designed to control the Linear-USM.The experiments show that after the controller achieve a sufficient study process,the motor 's speed error is smaller than 4.9mm/s and the length of the dead-zone is shorter than 0.018 s,when the target speed is a sinusoidal signal with a frequency of 1Hz and an amplitude of 50mm/s.The experiments show that the neural network control system is highly adaptive and can improve the performance of the Linear-USM.
Keywords/Search Tags:linear ultrasonic motor, driving and control system, PID controller, fuzzy control system, neural network control system
PDF Full Text Request
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