Title :
Neural network control of a piezo tool positioner
Author_Institution :
Syst. Res. Labs. Inc., Dayton, OH, USA
Abstract :
The major technical challenge to the application of piezo crystal as an actuator is concerned with its hysteresis behavior. This would result in a nonlinear and multi-valued mapping between the actuator input and output and hence influence the desired control precision. This problem was solved by using closed-loop robust neural network control technology
Keywords :
actuators; machine tools; neural nets; position control; actuator; closed-loop robust neural network control technology; control precision; hysteresis behavior; multi-valued mapping; neural network control; piezo crystal; piezo tool positioner; Actuators; Assembly; Cutting tools; Magnetic hysteresis; Neural networks; Position control; Recurrent neural networks; Robust control; Robust stability; Voltage;
Conference_Titel :
Electrical and Computer Engineering, 1993. Canadian Conference on
Conference_Location :
Vancouver, BC
Print_ISBN :
0-7803-2416-1
DOI :
10.1109/CCECE.1993.332324
