Dynamic Event-Triggered Adaptive Fuzzy Leader-Follower Consensus Control of State-Constrained Flexible-Joint Manipulators

This article investigates the leader-follower consensus problem of state-constrained flexible-joint manipulators. Many uncertainties exhibit in flexible-joint manipulators, which brings a great challenge to the leader-follower consensus control design, especially considering state constraints. In this work, a nonlinear state-dependent function is first constructed to deal with the full-state constraint problem. Then, a novel event-triggered adaptive fuzzy control strategy is presented by the function approximate technique, where a dynamic event-triggered mechanism is introduced to avoid continuous updates of the controller, and thereby control resources and communication burden can be effectively reduced. On the basis of Lyapunov stability analysis, it is proven that all error signals in the closed-loop systems are bounded, and the leader-follower consensus of flexible-joint manipulators is realized without violating full-state constraints. Simulation results and some comparisons are provided to validate the effectiveness of the presented control strategy.