Adaptive optimal coordination control of perturbed Bilateral Teleoperators with variable time delays using Actor-Critic Reinforcement Learning algorithm

In this article, we study the unification of coordination control problem between two sides and optimal control effectiveness for an unknown Bilateral Teleoperators (BTs) under variable time delays in communication between two sides and external disturbance. We proposed the control frame of Actor/Critic strategy and the Robust Integral of the Sign of the Error (RISE), in which the synchronization effectiveness is discussed in two sections with different conditions. The sliding variable is given to transform a BT dynamic model into order reduction model, which can be designed more favourable. By fully analysing optimization problem in designing the training weights of Actor/Critic structure based on the property of Hamiltonian term, Reinforcement Learning (RL) control scheme in each side is proposed for a BT system. Consequently, we incorporate the RISE term into proposed control frame to mathematically prove that the tracking errors asymptotically converge to zero. Furthermore, the proposed control strategy can also guarantee the convergence of learning process. Simulation results and the comparisons demonstrate the performance of the proposed control framework.