Title :
Output characteristics modeling of fast tool servo based on neural network method
Author :
Mengnan Xu ; Chungang Zhuang ; Zhenhua Xiong
Author_Institution :
Shanghai Jiao Tong Univ., Shanghai, China
Abstract :
Flexure hinge mechanism driven by piezoelectric actuator is widely used in Fast Tool Servo (FTS) system. Most of the research focuses on constructing the model between the control voltage and output displacement. In this paper, the FTS is designed for compensating the machining error caused by flutter during turning. Therefore, the turning force should be considered as an additional load for the real time control system. This paper presents an output characteristics model of FTS based on the Neural Network model by analyzing the relationship among the output displacement, control voltage and external load. Finally, through the fitting plot and residual plot compared with the regression model, the accuracy and validity of the proposed method for the output characteristics model is demonstrated.
Keywords :
control engineering computing; hinges; neural nets; piezoelectric actuators; regression analysis; servomechanisms; turning (machining); FTS; control voltage; external load; fast tool servo system; flexure hinge mechanism; machining error compensation; neural network method; output displacement; piezoelectric actuator; real time control system; regression model; turning force; Biological neural networks; Data models; Fitting; Force; Load modeling; Mathematical model; Piezoelectric actuators;
Conference_Titel :
Advanced Intelligent Mechatronics (AIM), 2014 IEEE/ASME International Conference on
Conference_Location :
Besacon
DOI :
10.1109/AIM.2014.6878308