Adaptive fuzzy control for multilateral cooperative teleoperation of multiple robotic manipulators under random network-induced delays

In this paper, an adaptive fuzzy control is investigated for multilateral teleoperation of two cooperating robotic manipulators that manipulate an object with constrained trajectory/force in the presence of dynamics uncertainties and random network-induced delays. First, the interconnected dynamics that consist of two master robots and cooperating slave robots are formulated. To consider multiple stochastic delays in communication channels, Markov processes are used to model these random network-induced delays. The interconnected dynamics of the teleoperation are divided into a local master/slave position/force subsystem and a stochastic-delayed motion synchronization subsystem. Then, an adaptive fuzzy control strategy, which is based on linear matrix inequalities (LMIs) that combine adaptive update techniques, is proposed to suppress the dynamics uncertainties, the external disturbances, and the multiple stochastic delays in communication channels. The control approach ensures that the defined synchronization errors converge to zero. The stochastic stability in mean square of the closed-loop system is proved using LMIs based on Lyapunov-Krasovskii functional synthesis. The proposed controls are validated using extensive simulation studies.