Terminal sliding mode control of acupuncture robot based on RBF neural network

To solve the problem of trajectory tracking control when the acupuncture robot performs treatments, a terminal sliding mode controller which is based on RBF neural network was designed. Firstly, the acupuncture robot treatment system was established. Then, the dynamic model of the acupuncture robot was developed based on Lagrange equations. Next, the control strategy which is used in the trajectory tracking of the acupuncture robot was proposed. In this control scheme, with the introduction of non-singular fast terminal sliding mode function, the issue of singular value was avoided, and the unmodeled characteristics and external disturbances of the acupuncture robot by using RBF neural network. Additionally, according to the Lyapunov theory, it is proved that the designed controller is stable. Finally, by means of visual simulation and the comparative analysis, it shows that the designed controller has faster convergence speed, higher control accuracy and better anti-jamming performance.