Distributed Neurodynamics Controller-Based Two-Phase Strength Converging Law for Synchronization of Multimanipulator Systems

In this article, a distributed neurodynamics controller-based strength converging law is proposed for the multimanipulator systems (MMSs) with joint uncertainties and external disturbances. By utilizing the potential form of Nash equilibrium, a distributed optimization scheme of minimum velocity norm (MVN) for synchronous manipulators is constructed. Then a novel two-phase strength converging law is presented and analyzed for the solution of the distributed scheme and a fast consensus convergence of the MMSs is guaranteed by adjusting the law variables according to the varying range of the joint velocities. With the proposed neurodynamics controller, both high convergent precision and synchronous tracking performances of the collaborative manipulators are achieved in an accurate fixed-time expression of the joint velocities. Theoretical analyses and comparisons are provided to verify the synchronization property and antiinterference of the MMSs with the proposed method.