Angle Control of a one-Dimension Pneumatic Muscle Arm using Self-Organizing Fuzzy Control

Pneumatic muscle actuators (PMAs) have the highest power/weight ratio and power/volume ratio of any actuator. Therefore, it can be used not only in the rehabilitation engineering but also as an actuators in robots, including industrial robots and therapy robot. It is difficult to achieve high control accuracy using classical control method, because the compressibility of gas and the nonlinear elasticity of bladder container caused parameter variation. The self-organizing fuzzy control (SOFC) is developed in this study. The linguistic approach learning mechanism is used to modify on-line fuzzy rules. The experimental results show that control strategy can attain excellently control performance.

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