Task-space coordinated tracking of multiple heterogeneous manipulators via controller-estimator approaches

TL;DR

This paper introduces distributed controller-estimator algorithms for coordinated task-space tracking of multiple heterogeneous manipulators, handling uncertainties and disturbances, with proven stability conditions and simulation validation.

Contribution

It develops novel distributed controller-estimator algorithms for heterogeneous manipulators with uncertainties, ensuring stable coordinated tracking in task space.

Findings

Algorithms achieve asymptotic stability of tracking errors.

Conditions for stability are rigorously derived.

Simulations confirm effectiveness of the proposed methods.

Abstract

This paper studies the task-space coordinated tracking of a time-varying leader for multiple heterogeneous manipulators (MHMs), containing redundant manipulators and nonredundant ones. Different from the traditional coordinated control, distributed controller-estimator algorithms (DCEA), which consist of local algorithms and networked algorithms, are developed for MHMs with parametric uncertainties and input disturbances. By invoking differential inclusions, nonsmooth analysis, and input-to-state stability, some conditions (including sufficient conditions, necessary and sufficient conditions) on the asymptotic stability of the task-space tracking errors and the subtask errors are developed. Simulation results are given to show the effectiveness of the presented DCEA.