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Intelligent Switching Control of a Pneumatic Artificial Muscle Robot using Learning Vector Quantization Neural Network  

Yoon, Hong-Soo (Department of Mechanical and Automotive Engineering, Univ. of Ulsan)
Ahn, Kyoung-Kwan (School of Mechanical and Automotive Engineering, Univ of Ulsan)
Publication Information
Journal of the Korean Society for Precision Engineering / v.26, no.4, 2009 , pp. 82-90 More about this Journal
Abstract
Pneumatic cylinder is one of the low cost actuation sources which have been applied in industrial and prosthetic application since it has a high power/weight ratio, a high-tension force and a long durability However, the control problems of pneumatic systems, oscillatory motion and compliance, have prevented their widespread use in advanced robotics. To overcome these shortcomings, a number of newer pneumatic actuators have been developed such as McKibben Muscle, Rubber Actuator and Pneumatic Artificial Muscle (PAM) Manipulators. In this paper, one solution for position control of a robot arm, which is driven by two pneumatic artificial muscles, is presented. However, some limitations still exist, such as a deterioration of the performance of transient response due to the changes in the external load of the robot arm. To overcome this problem, a switching algorithm of the control parameter using a learning vector quantization neural network (LVQNN) is proposed in this paper. This estimates the external load of the pneumatic artificial muscle manipulator. The effectiveness of the proposed control algorithm is demonstrated through experiments with different external working loads.
Keywords
Pneumatic Artificial; Neural Network Switching Control; Intelligent Control; Pneumatic Manipulator;
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Times Cited By KSCI : 1  (Citation Analysis)
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