Abstract:This paper addresses the position tracking control application of a parallel robot using predictive control techniques. A Generalized Predictive Control strategy (GPC), which considers the linear dynamic model, is used to enhance the tracking position accuracy. The robustification of GPC against measurement noise and neglected dynamics using Youla parameterization is performed. A simulation of the orthoglide robot considering uncertainties related to geometrical and dynamic parameters, sensors noise and fricti… Show more
“…MPC uses the online rolling optimization and feedback correction strategy. The online rolling optimization strategy can compensate the uncertainty influence caused by model mismatch and interference so as to improve the control effect of the system [23]- [25]. After a series of future control variables are determined by the optimization, MPC uses the detected error between actual output and the model prediction output to realize feedback correction to remedy the defect.…”
. (2016). The study of model predictive control algorithm based on the force/position control scheme of the 5-DOF redundant actuation parallel robot. Robotics and Autonomous Systems. DOI: 10.1016DOI: 10. /j.robot.2016 Citing this paper Please note that where the full-text provided on King's Research Portal is the Author Accepted Manuscript or Post-Print version this may differ from the final Published version. If citing, it is advised that you check and use the publisher's definitive version for pagination, volume/issue, and date of publication details. And where the final published version is provided on the Research Portal, if citing you are again advised to check the publisher's website for any subsequent corrections.
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AbstractRedundant actuated parallel robot is a multi-input and multi-output (MIMO) system which usually works in an uncertain environment. In this paper, the force/position hybrid control structure of 6PUS-UPU redundant actuation parallel robot is designed, proportional-integral (PI) and model predictive control (MPC) cascade control strategy are used in the redundant branch of 6PUS-UPU redundant actuation parallel robot. The MPC algorithm is used in the current loop of the permanent magnet synchronous motor (PMSM) to restrain the motor parameter uncertainty and external disturbances influence on motor control. The MATLAB/ADAMS joint simulation method based on virtual 6PUS-UPU redundant actuation parallel robot prototype is used to test the performance of the proposed control strategy. The performance of proposed PI-MPC control strategy is compared with the traditional PI-PI control strategy. The simulation results show that the MPC controller can improve the tracking ability of the motor torque, guarantee the system robustness under the parameter variations and load disturbance environment.
“…MPC uses the online rolling optimization and feedback correction strategy. The online rolling optimization strategy can compensate the uncertainty influence caused by model mismatch and interference so as to improve the control effect of the system [23]- [25]. After a series of future control variables are determined by the optimization, MPC uses the detected error between actual output and the model prediction output to realize feedback correction to remedy the defect.…”
. (2016). The study of model predictive control algorithm based on the force/position control scheme of the 5-DOF redundant actuation parallel robot. Robotics and Autonomous Systems. DOI: 10.1016DOI: 10. /j.robot.2016 Citing this paper Please note that where the full-text provided on King's Research Portal is the Author Accepted Manuscript or Post-Print version this may differ from the final Published version. If citing, it is advised that you check and use the publisher's definitive version for pagination, volume/issue, and date of publication details. And where the final published version is provided on the Research Portal, if citing you are again advised to check the publisher's website for any subsequent corrections.
General rightsCopyright and moral rights for the publications made accessible in the Research Portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognize and abide by the legal requirements associated with these rights.•Users may download and print one copy of any publication from the Research Portal for the purpose of private study or research.•You may not further distribute the material or use it for any profit-making activity or commercial gain •You may freely distribute the URL identifying the publication in the Research Portal Take down policy If you believe that this document breaches copyright please contact librarypure@kcl.ac.uk providing details, and we will remove access to the work immediately and investigate your claim.
AbstractRedundant actuated parallel robot is a multi-input and multi-output (MIMO) system which usually works in an uncertain environment. In this paper, the force/position hybrid control structure of 6PUS-UPU redundant actuation parallel robot is designed, proportional-integral (PI) and model predictive control (MPC) cascade control strategy are used in the redundant branch of 6PUS-UPU redundant actuation parallel robot. The MPC algorithm is used in the current loop of the permanent magnet synchronous motor (PMSM) to restrain the motor parameter uncertainty and external disturbances influence on motor control. The MATLAB/ADAMS joint simulation method based on virtual 6PUS-UPU redundant actuation parallel robot prototype is used to test the performance of the proposed control strategy. The performance of proposed PI-MPC control strategy is compared with the traditional PI-PI control strategy. The simulation results show that the MPC controller can improve the tracking ability of the motor torque, guarantee the system robustness under the parameter variations and load disturbance environment.
This paper aims at analyzing the effect of uncertain friction in the active joints of a 2-DOF planar parallel robot using a fuzzy dynamic approach. The uncertain parameters of friction are modeled as fuzzy variables and the dynamic response of the robot is computed by using fuzzy dynamic analysis. The dynamics of the robot under uncertain friction including a computed torque position controller is analyzed. Numerical simulations illustrate the proposed methodology in order to describe and quantify the effect of uncertain frictions on the dynamic performance of the parallel robot.
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