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Intelligent Switching Control of Pneumatic Cylinders by Learning Vector Quantization Neural Network
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  • Intelligent Switching Control of Pneumatic Cylinders by Learning Vector Quantization Neural Network
  • Intelligent Switching Control of Pneumatic Cylinders by Learning Vector Quantization Neural Network
저자명
Ahn. KyoungKwan,Lee. ByungRyong
간행물명
Journal of mechanical science and technology
권/호정보
2005년|19권 2호|pp.529-539 (11 pages)
발행정보
대한기계학회
파일정보
정기간행물|ENG|
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기타
이 논문은 한국과학기술정보연구원과 논문 연계를 통해 무료로 제공되는 원문입니다.
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기타언어초록

The development of a fast, accurate, and inexpensive position-controlled pneumatic actuator that may be applied to various practical positioning applications with various external loads is described in this paper. A novel modified pulse-width modulation (MPWM) valve pulsing algorithm allows on/off solenoid valves to be used in place of costly servo valves. A comparison between the system response of the standard PWM technique and that of the modified PWM technique shows that the performance of the proposed technique was significantly increased. A state-feedback controller with position, velocity and acceleration feedback was successfully implemented as a continuous controller. A switching algorithm for control parameters using a learning vector quantization neural network (LVQNN) has newly proposed, which classifies the external load of the pneumatic actuator. The effectiveness of this proposed control algorithm with smooth switching control has been demonstrated through experiments with various external loads.