Intelligent switching control of pneumatic cylinders by learning vector quantization neural network |
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Authors: | KyoungKwan Ahn ByungRyong Lee |
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Affiliation: | (1) School of Mechanical and Automotive Engineering, University of Ulsan, San 29, Muger2-dong, Nam-gu, 680-749 Ulsan, Korea |
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Abstract: | School of Mechanical and Automotive Engineering, University of Ulsan, San 29, Muger2-dong, Nam-gu, Uhan 680-749, Korea The
development of a fast, accuiate, 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 standardPWM 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
controllei A switching algorithm foi 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 thiough experiments with various external loads |
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Keywords: | Pneumatic Switching Control On/off Solenoid Valve Pulse Width Modulation Neural Network Intelligent Control |
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