scholarly journals Trajectory Tracking Control for Uncertain Robot Manipulators with Repetitive Motions in Task Space

2021 ◽  
Vol 2021 ◽  
pp. 1-17
Author(s):  
Jiutai Liu ◽  
Xiucheng Dong ◽  
Yong Yang ◽  
Hongyu Chen
Keyword(s):  
Trajectory Tracking ◽  
Robot Manipulators ◽  
Tracking Error ◽  
Task Space ◽  
Learning Gain ◽  
Trajectory Tracking Control ◽  
Adaptive Iterative Learning Control ◽  
Tracking Tasks ◽  
Control Schemes ◽  
Composite Energy

This paper aims at the trajectory tracking problem of robot manipulators performing repetitive tasks in task space. Two control schemes are presented to conduct trajectory tracking tasks under uncertain conditions including unmodeled dynamics of robot and additional disturbances. The first controller, pure adaptive iterative learning control (AILC), is based upon the use of a proportional-derivative-like (PD-like) feedback structure, and its design seems very simple in the sense that the only requirement on the learning gain and control parameters is the positive definiteness condition. The second controller is designed with a combination of AILC and neural networks (NNs) where the AILC is adopted to learn the periodic uncertainties that attribute to the repetitive motion of robot manipulators while the add-on NNs are used to approximate and compensate all nonperiodic ones. Moreover, a combined error factor (CEF), which is composed of the weighted sum of tracking error and its derivative, is designed for network updating law to improve the learning speed as well as tracking accuracy of the system. Stabilities of the controllers and convergence are proved rigorously by a Lyapunov-like composite energy function. The simulations performed on two-link manipulator are provided to verify the effectiveness of the proposed controllers. The results of compared simulations illustrate that our proposed control schemes can significantly conduct trajectory tracking tasks.

scholarly journals Robust Task Space Trajectory Tracking Control of Robotic Manipulators

2016 ◽  
Vol 21 (3) ◽  
pp. 547-568 ◽  
Author(s):  
M. Galicki
Keyword(s):  
Trajectory Tracking ◽  
Lyapunov Stability Theory ◽  
Task Space ◽  
Redundant Manipulator ◽  
Trajectory Tracking Control ◽  
Finite Time Convergence ◽  
Robot Trajectory ◽  
Vector Variable ◽  
Control Schemes ◽  
Chattering Free

Abstract This work deals with the problem of the accurate task space trajectory tracking subject to finite-time convergence. Kinematic and dynamic equations of a redundant manipulator are assumed to be uncertain. Moreover, globally unbounded disturbances are allowed to act on the manipulator when tracking the trajectory by the end-effector. Furthermore, the movement is to be accomplished in such a way as to reduce both the manipulator torques and their oscillations thus eliminating the potential robot vibrations. Based on suitably defined task space non-singular terminal sliding vector variable and the Lyapunov stability theory, we propose a class of chattering-free robust controllers, based on the estimation of transpose Jacobian, which seem to be effective in counteracting both uncertain kinematics and dynamics, unbounded disturbances and (possible) kinematic and/or algorithmic singularities met on the robot trajectory. The numerical simulations carried out for a redundant manipulator of a SCARA type consisting of the three revolute kinematic pairs and operating in a two-dimensional task space, illustrate performance of the proposed controllers as well as comparisons with other well known control schemes.

Simultaneous Trajectory Tracking and Stiffness Control of Cable Actuated Parallel Manipulator

2009 ◽  
Author(s):  
Kun Yu ◽  
Leng-Feng Lee ◽  
Venkat N. Krovi
Keyword(s):  
Trajectory Tracking ◽  
Parallel Manipulators ◽  
Control Input ◽  
Robot System ◽  
Trajectory Tracking Control ◽  
Implementation Framework ◽  
Actuation Redundancy ◽  
Cable Robot ◽  
Control Schemes ◽  
Stiffness Control

Cable-actuated parallel manipulators combine benefits of large workspaces, significant payload capacities and high stiffness by virtue of the cable actuation. However, redundant/surplus cables are required to overcome the unidirectional nature of forces exertable by cables. This leads to actuation redundancy which needs to be resolved in order to realize some of the benefits. We study the implication of using actuation redundancy to tailor the workspace (task space) stiffness of the cable robot system. Suitable trajectory tracking control schemes are developed that additionally achieve secondary goal of active stiffness control to improve disturbance rejection, under positive control input constraint We demonstrate the performance of these control schemes using a point-mass cable robot system modeled within a virtual prototyping (VP) implementation framework.

Rapid iterative learning algorithm of nonlinear time-delay system with initial deviation

2020 ◽  
pp. 002072092094057
Author(s):  
Xiaoyan Cheng ◽  
Hongbin Wang ◽  
Qinzhao Wang ◽  
Shaochan Feng
Keyword(s):  
Time Delay ◽  
Trajectory Tracking ◽  
Learning Algorithm ◽  
Tracking Error ◽  
Iterative Learning ◽  
Forgetting Factor ◽  
Initial State ◽  
Trajectory Tracking Control ◽  
Joint Rotation ◽  
Variable Forgetting Factor

A rapid iterative learning control algorithm with variable forgetting factor is applied for a class of nonlinear system with initial error and time-delay. This algorithm eliminats the limitation that the initial state should be reset to the expected one or fixed value at the start of iteration in the learning process of conventional algorithms. The error and the differences between two adjacent error is adopted to correct the controller avoiding the unstable influence of the derivative for PD type algorithm and the available information is fully used to increase convergence rate. Furthermore variable forgetting factor introduced guaranteed a fast convergence of trajectory tracking error Then, with applying the rapid algorithm to the trajectory tracking control of manipulator, the learning speed and tracking performance are both greatly improved. Meanwhile, the control strategy is proposed for the limitation of each joint rotation. The convergence of the method is also proved theoretically. Finally, simulation results illustrates the effectiveness and the real-time ability of the proposed way.

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