Stable computed-torque control of robot manipulators via fuzzyself-tuning

Computed-torque control is a well-known motion control strategy for manipulators which ensures global asymptotic stability for fixed symmetric positive definite (proportional and derivative) gain matrices. In this paper, we show that global asymptotic stability also holds for a class of gain matrices depending on the manipulator state. This feature increases the potential of the computed-torque control scheme to handle practical constraint in actual robots such as presence of friction in the joints and actuators with limited torque capabilities. We illustrate this potential by means of a fuzzy self-tuning algorithm to select the proportional and derivative gains according to the actual tracking position error. Experiments on a two degrees of freedom robot arm show the usefulness of the proposed approach.     

Global Convergence of a Decentralized Adaptive Fuzzy Control for the Motion of Robot Manipulators: Application to the Mitsubishi PA10-7CE as a Case of Study

In general terms, robot control consists in making a robot execute a commanded task. One of the most important cases is the trajectory tracking or motion control. In this paper, a control algorithm that uses adaptive fuzzy systems to approximate local portions of the robot manipulator dynamics is proposed in order to solve the trajectory tracking problem. This scheme is characterized by not requiring any knowledge of the dynamic model and, in contrast to some fuzzy adaptive controllers previously developed, the one proposed here is in a decentralized configuration, wherein each joint is considered as a subsystem and is independently controlled only through its local variables. Furthermore, a study that guarantees the stability and the boundedness of the solutions of the closed-loop system via Lyapunov theory is presented, including a functional analysis which proves for the first time that a decentralized adaptive fuzzy controller satisfies the motion control objective. The theoretical results exposed here are verified via experimentation by applying the designed algorithm to the Mitsubishi PA10-7CE robot arm and the outcomes are reported.     

Global asymptotic stability of a tracking sectorial fuzzy controller for robot manipulators.

This paper shows that fuzzy control systems satisfying sectorial properties are effective for motion tracking control of robot manipulators. We propose a controller whose structure is composed by a sectorial fuzzy controller plus a full nonlinear robot dynamics compensation, in such a way that this structure leads to a very simple closed-loop system represented by an autonomous nonlinear differential equation. We demonstrate via Lyapunov theory, that the closed-loop system is globally asymptotically stable. Experimental results show the feasibility of the proposed controller.