The Fuzzy Neural Network Repeated Control Of High Frequency Response FTS Driven By Voice Coil Motor

Ultra-precision parts such as optical free-form surfaces and micro-structured functional surface parts are widely used in military,medical,and even civilian fields because of their superior optical performance and special physical characteristic.The diamond turning technology based on Fast Tool Servo(FTS)can efficiently turn high-precision and high-quality curved surfaces after a single processing operation,and it has attracted widely attention due to its high efficiency and low cost.The processing of ultra precision parts requires FTS to accurately track high-frequency periodic signal.On the base of these,the paper chooses Voice Coil Linear Actuator(VCLA)as the implementing agency of FTS and studies the corresponding control strategy.The specific contents of the research are as follows:Firstly,a large number of related documents are collected and consulted,and I have mastered the research trend of FTS in the main driving methods and related control strategies at domestic and abroad.On the base of these,the mathematical model of voice coil linear motor for driving FTS is established.Through the simulation and analysis,the designed IMC controller makes the servo tool hoider system have good dynamic and static performance,robust stability,enough bandwidth,phase margin and faster response speed.On the base of these,the processing of ultra precision parts requires FTS to accurately track high-frequency periodic signal and repetitive control can achieve accurate tracking or suppression of external reference input or disturbance signals for any period,an improved repetitive control strategy is proposed.On the basis of theoretical analysis,the corresponding control system is designed and simulated by Matlab,which verifies the effectiveness of the control strategy.Besides,when the input signal changes during the high-frequency cutting process of the FTS,that is,in the case of a high frequency variable period input signal,the fixed cut off frequency of the low pass filter in the repetitive controller will limit its control effect,and the accurate tracking control of track can not be realized.For this problem,a fuzzy neural network controller with self-learning ability is proposed to adaptively adjust the cut-off frequency of the filter,then the performance of repetitive controller will be improved.On the basis of theoretical analysis,the corresponding control system is designed and simulated by Matlab,which verifies the effectiveness of the control strategy.