Research on RBF NN tuning PD control arithmetic of tele-presence bilateral servo system

Aiming to the problem of big impact feedback force and bad position tracking of parallel force feedback bilateral hydraulic servo control system, a novel force feedback bilateral servo system is presented, which regards the difference between the masterpsilas manipulative force and the slavepsilas resistance as command signal, simultaneity, the difference between the slavepsilas displacement and the masterpsilas displacement is fed back for driving movement of the master. In order to control master-slave displacement follows and feel ldquoforce senserdquo by joy stick, in view of the novel force feedback bilateral servo control system, it was proposed that one kind of RBF neural network tuning PD on-line from study, adaptive control strategy, through optimizing two parameters of PD by RBF neural network, which can approach willfully the continuous function characteristic using the RBF neural network by the free precision. Simulation experimental results show that this control algorithm of novel force sense bilateral servo system is practical and feasible, and let the operator feel ldquothe force senserdquo well from feedback, thus improves the human and the environment interaction characteristic and enhances the working efficiency. Moreover, this control arithmetic has taken on control briefness, constringency rate rapidness, real-time well, strong robustness, self-adapted and the rapidity.