Decentralized robust control of robot manipulators

Abstract

This paper presents a novel robust decentralized control for robots. It follows the design procedure for a class of interconnected nonlinear mechanical systems presented recently in [8]. The rationale under this design procedure is to compensate high-order interconnections in states among subsystems. The resulting controller is extremely simple, consisting of a linear state-feedback plus a signal designed to compensate for the coupling among the joints, parameter uncertainty and bounded disturbances. The implementation of the controller needs no robot model knowledge. This feature plus its suitability for parallel processing implementation makes the proposed controller a promise for a robot to perform fast-tracking tasks. Experiment results are included to illustrate the performance of this controller.

ADAPTIVE SLIDING MODE CONTROL OF MOBILE MANIPULATOR WELDING SYSTEM FOR FLAT HULL BLOCK Author:

“…A study proposed a singularity control method for the manipulator using closedform kinematic solutions (Lloyd et al, 1993). A previous scholar proposed a decentralized robust control of a robot manipulator (Tang et al, 1998).…”

A set of decentralized PID controllers for an n – link robot manipulator

“…The solution of decentralized tracking control problem for robot manipulator is slightly complex since we cannot split the overall system into several subsystems whose states and input torques are not isolated from each other due to the coupling caused by nonlinear inertial terms. Among the works reported in this area are Narendra & Oleng (2002), Tang et al (2000), Tarokh (1996), Tang & Guerrero (1998), Wang & Wend (1999), Liu (1999) and Seraji (1989). Narendra & Oleng (2002) have shown that in strictly decentralized adaptive control systems, it is theoretically possible to track desired outputs with zero error.…”

“…Tang et al (2000) and Tarokh (1996) have presented an asymptotically stable decentralized adaptive control scheme to enable accurate trajectory tracking. Tang & Guerrero (1998) obtained an extremely simple controller, consisting of a linear state-feedback with an additional signal designed to compensate for the coupling among the joints, parameter uncertainty and bounded disturbances. In Wang & Wend (1999) the dynamics of the subsystems are divided into two parts: a nominal system and uncertainties.…”