Journal of Mechanical Science and Technology

The Korean Society of Mechanical Engineers (대한기계학회)
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Intelligent Switching Control of Pneumatic Cylinders by Learning Vector Quantization Neural Network

  • Ahn KyoungKwan (School of Mechanical and Automotive Engineering, University of Ulsan) ;
  • Lee ByungRyong (School of Mechanical and Automotive Engineering, University of Ulsan)
  • Published : 2005.02.01
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Abstract

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.

Keywords

References

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