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.

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.

Iterative learning control for a distributed cloud robot with payload delivery

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Jiehao Li ◽  
Shoukun Wang ◽  
Junzheng Wang ◽  
Jing Li ◽  
Jiangbo Zhao ◽  
...  
Keyword(s):  
Trajectory Tracking ◽  
Tracking Control ◽  
Iterative Learning Control ◽  
Learning Control ◽  
Iterative Learning ◽  
Robot System ◽  
Trajectory Tracking Control ◽  
Content Type ◽  
Motion Models ◽  
Distributed Cloud

Purpose When it comes to the high accuracy autonomous motion of the mobile robot, it is challenging to effectively control the robot to follow the desired trajectory and transport the payload simultaneously, especially for the cloud robot system. In this paper, a flexible trajectory tracking control scheme is developed via iterative learning control to manage a distributed cloud robot (BIT-6NAZA) under the payload delivery scenarios. Design/methodology/approach Considering the relationship of six-wheeled independent steering in the BIT-6NAZA robot, an iterative learning controller is implemented for reliable trajectory tracking with the payload transportation. Meanwhile, the stability analysis of the system ensures the effective convergence of the algorithm. Findings Finally, to evaluate the developed method, some demonstrations, including the different motion models and tracking control, are presented both in simulation and experiment. It can achieve flexible tracking performance of the designed composite algorithm. Originality/value This paper provides a feasible method for the trajectory tracking control in the cloud robot system and simultaneously promotes the robot application in practical engineering.

scholarly journals Safety-Guaranteed Trajectory Tracking Control for the Underactuated Hovercraft with State and Input Constraints

2017 ◽  
Vol 2017 ◽  
pp. 1-12 ◽  
Author(s):  
Mingyu Fu ◽  
Shuang Gao ◽  
Chenglong Wang
Keyword(s):  
Dynamic System ◽  
Trajectory Tracking ◽  
Sliding Mode ◽  
Control Input ◽  
Input Constraints ◽  
Tracking Errors ◽  
Trajectory Tracking Control ◽  
Trajectory Tracking Controller ◽  
Relationship Of ◽  
The Relationship

This paper develops a safety-guaranteed trajectory tracking controller for hovercraft by using a safety-guaranteed auxiliary dynamic system, an integral sliding mode control, and an adaptive neural network method. The safety-guaranteed auxiliary dynamic system is designed to implement system state and input constraints. By considering the relationship of velocity and resistance hump, the velocity of hovercraft is constrained to eliminate the effect of resistance hump and obtain better stability. And the safety limit of drift angle is well performed to guarantee the light safe maneuvers of hovercraft tracking with high velocities. In view of the natural capabilities of actuators, the control input is constrained. High nonlinearity and model uncertainties of hovercraft are approximated by employing adaptive radical basis function neural networks. The proposed controller guarantees the boundedness of all the closed-loop signals. Specifically, the tracking errors are uniformly ultimately bounded. Numerical simulations are implemented to demonstrate the efficacy of the designed controller.

A robust trajectory tracking control of a polishing robot system based on CAM data

2001 ◽  
Vol 17 (1-2) ◽  
pp. 177-183 ◽  
Author(s):  
M.C. Lee ◽  
S.J. Go ◽  
M.H. Lee ◽  
C.S. Jun ◽  
D.S. Kim ◽  
...  
Keyword(s):  
Trajectory Tracking ◽  
Tracking Control ◽  
Robot System ◽  
Trajectory Tracking Control

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.

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