Adaptive neural network based position tracking control for Dual-master/Single-slave teleoperation system under communication constant time delays. (October 2019) - Ji, Yude; Liu, Danyang; Guo, Yanping
Abstract: The novel trajectory tracking control strategies for trilateral teleoperation systems with Dual-master/Single-slave robot manipulators under communication constant time delays are proposed in this article. By incorporating this design technique into the neural network (NN) based adaptive control framework, two controllers are designed for the trilateral teleoperation systems in free motion. First, with acceleration measurements, an adaptive controller under the synchronization variables containing the position and velocity error is constructed to guarantee the position and velocity tracking errors between the trilateral teleoperation systems asymptotically converge to zero. Second, without acceleration measurements, an adaptive controller under the new synchronization variables is presented such that the trilateral teleoperation systems can obtain the same trajectory tracking performance as the first controller. Third, in term of establishing suitable Lyapunov–Krasovskii functionals, the asymptotic tracking performances of the trilateral teleoperation systems can be derived independent of the communication constant time delays. Moreover, these two controllers are obtained without the knowledge of upper bounds of the NN approximation errors, respectively. Finally, simulation results are presented to demonstrate the validity of the proposed methods. Highlights: The novel trajectory tracking strategies for trilateral teleoperation systems are proposed. Two new controllers with and without acceleration measurements are designed in free motion, respectively. The asymptotic tracking performances are obtained without the upper bound of approximation error. Simulation results are presented to demonstrate the validity of the proposed methods.