Abstract
In this study, a novel Fault-Tolerant Control Methodology (FTCM) is developed for robot manipulators. First, to overcome singularity glitch and to enhance convergence time of conventional Terminal Sliding Mode Control (TSMC), a new Fast Terminal Sliding Mode Surface (FTSMS) is constructed. Next, to reduce the computation complexity and to provide requirements about undefined nonlinear functions for the control system, a Disturbance Observer (DO) to estimate uncertain dynamics, external disturbances, or faults. Besides, a Super-Twisting Reaching Control Law (STRCL) is designed to compensate for the estimated error of disturbance observer with chattering rejection. Final, a novel, robust, FTCM was developed for robot manipulators to obtain the stability goal of the system, to reach the prescribed performance, and to overcome the effects of disturbances, nonlinearities, or faults. Accordingly, the proposed FTCM has remarkable features, such as fast convergence speeds, robust precision, high tracking performance, significant alleviation of chattering behavior, and finite-time convergence. The position tracking computer simulations were implemented to exhibit the effectiveness and feasibility of the suggested FTCM compared with other control algorithms.
Highlights
INTRODUCTION RRobots are essential for manufacturing, human life, and performing complex tasks nowadays and in the future
Our goal is to propose a robust, active Fault-Tolerant Control Methodology (FTCM) such that this control algorithm can provide the prescribed performance regardless of disturbances, uncertainties, and faults
The kinematic and dynamic model with the crucial parameters found in a 3-DOF PUMA560 robot manipulator has been previously described in detail [65]
Summary
Robots are essential for manufacturing, human life, and performing complex tasks nowadays and in the future. With the need for high-quality products, the robot is more widely used. To achieve quality products with high productivity, the robot system must be operated smoothly, reliably, and safely. Robotic manipulators unavoidably face many complicated uncertainties caused by unmodeled and unknown dynamic models, nonlinear frictional forces, exterior disturbances, or faults. This leads to obstacles for the control design process and precise control of robot manipulators. The tracking control of robotic manipulators has concerned many scientists in studying its potential capability. The tracking control method of robotic systems that
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