Paper
20 August 1999 Intelligent control of piezoelectric actuators for precision manufacturing
Chi-Man Kwan, Roger Xu, Jun Lang, C. Lin, Mark W. Stevenson, Yan Lin, Zhubing Ren, Leonard S. Haynes
Author Affiliations +
Abstract
We had a contract from Navy in 1997 to work on the control of piezoelectric actuators. The controller consists of two loops: feedforward and feedback. The feedforward loop consists of a Fuzzy CMAC controller, which is used to compensate hysteresis nonlinearity. Fuzzy CMAC is a new type of neural net developed by Intelligent Automation Incorporated. It has a learning speed that is an order of magnitude faster than conventional multilayer perceptron neural nets. The advantage of feedforward control is that it can increase the system response speed without interfering with the system stability. We used a PID controller in the feedback loop because the feedforward compensation may have some residual errors and having a PID controller in the loop will help to reduce the error even further. In our experiment, we operate an actuator manufactured by Burleigh Instruments in the region of 100 Hz whereas the actuator resonance peak is about 1 kHz. Experimental results showed our approach can achieve excellent linearity.
© (1999) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Chi-Man Kwan, Roger Xu, Jun Lang, C. Lin, Mark W. Stevenson, Yan Lin, Zhubing Ren, and Leonard S. Haynes "Intelligent control of piezoelectric actuators for precision manufacturing", Proc. SPIE 3833, Intelligent Systems in Design and Manufacturing II, (20 August 1999); https://doi.org/10.1117/12.359513
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KEYWORDS
Actuators

Fuzzy logic

Digital signal processing

Neural networks

Data modeling

Digital filtering

Sensors

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