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An Intelligent Nano-positioning Control System Driven by an Ultrasonic Motor
Kuang-Chao Fan,Zi-Fa Lai 한국정밀공학회 2008 International Journal of Precision Engineering and Vol.9 No.3
This paper presents a linear positioning system and its control algorithm design with nano accuracy/resolution. The basic linear stage structure is driven by an ultrasonic motor and its displacement feedback is detected by a LDGI(Laser Diffraction Grating Interferometer), which can achieve nanometer resolution. Due to the friction driving property of the ultrasonic motor, the driving situation differs in various ranges along the travel. Experiments have been carried out in order to observe and realize the phenomena of the three main driving modes: AC mode (for ㎜ motion), Gate mode (for ㎛ motion), and DC mode (for ㎚ motion). A proposed FCMAC(Fuzzy Cerebella Model Articulation Controller) control algorithm is implemented for manipulating and predicting the velocity variation during the motion of each mode respectively. The PCbased integral positioning system is built up with a NI DAQ Device by a BCB (Borland C?? Builder) program to accomplish the purpose of an intelligent nano-positioning control.
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An Intelligent Nano-positioning Control System Driven by an Ultrasonic Motor
Fan, Kuang-Chao,Lai, Zi-Fa Korean Society for Precision Engineering 2008 International Journal of Precision Engineering and Vol.9 No.3
This paper presents a linear positioning system and its control algorithm design with nano accuracy/resolution. The basic linear stage structure is driven by an ultrasonic motor and its displacement feedback is detected by a LDGI (Laser Diffraction Grating Interferometer), which can achieve nanometer resolution. Due to the friction driving property of the ultrasonic motor, the driving situation differs in various ranges along the travel. Experiments have been carried out in order to observe and realize the phenomena of the three main driving modes: AC mode (for mm motion), Gate mode (for ${\mu}m$ motion), and DC mode (for nm motion). A proposed FCMAC (Fuzzy Cerebella Model Articulation Controller) control algorithm is implemented for manipulating and predicting the velocity variation during the motion of each mode respectively. The PCbased integral positioning system is built up with a NI DAQ Device by a BCB (Borland $C^{++}$ Builder) program to accomplish the purpose of an intelligent nanopositioning control.
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