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Tracking control of a 3-DOF rehabilitation robot actuated by pneumatic muscle actuators using adaptive self-organising fuzzy sliding mode control

The action of a pneumatic muscle actuator (PMA) is very similar to that of animal skeletal muscle. It also has other advantages such as high power/weight ratio, high power/volume ratio, low price, little maintenance needed, great compliance and inherent safety. Therefore, it can be suitably applied to rehabilitation engineering for persons with neuromuscular or musculoskeletal pathologies affecting extremity functions. However, excellent control performance can hardly be achieved by classical control methods because gas compression and non-linear elasticity of bladder containers cause parameter variations. An adaptive self-organising fuzzy sliding mode control (ASOFSMC) is developed in this study to improve end-effector tracking performance. The use of a fuzzy sliding surface can reduce the number of fuzzy rules required. A self-organising learning mechanism is employed to modify online fuzzy rules. An adaptive law is adopted to adjust scaling factors. Finally, Lyapunov theorem is employed to prove the stability of the ASOFSMC. Experimental results show that this control strategy can achieve excellent tracking performance.