Abstract

The ankle is the most weight-bearing joint in the body, which plays a vital role in ensuring people’s walking. Aiming at the problems of complex mechanism, rigid drive and difficult control of the current ankle joint rehabilitation equipment, a 3-SPS/S type ankle parallel rehabilitation mechanism based on pneumatic artificial muscles is developed, and a self-tuning PID controller based on BP neural network is proposed to improve the accuracy of the control system. According to the static characteristics of the pneumatic artificial muscle, the physicians mathematical model of the artificial muscle is optimized, the kinematic position inverse solution of the ankle joint parallel rehabilitation mechanism is analysed and the control system is established. Combined with traditional PID control and BP neural network control algorithm, the BP_PID controller is completed, the control system is simulated and analysed. The simulation results show that BP_PID controller can meet design requirements for the ankle joint parallel rehabilitation mechanism, and is obviously superior to the PID controller in response speed and control accuracy.

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