Incremental Model Predictive Control for Velocity-Controlled Robot Manipulators

In this article, an incremental model predictive controller is proposed for the velocity-controlled robot manipulator. First, the time-delay estimation (TDE) technique is used to approximate the unknown discrepancy between the command and the real joint velocity due to velocity dynamics, and the equation of motion in the incremental form is obtained. Then, on the basis of the resulting equation of motion and taking into account joint position and velocity constraints, the incremental model predictive controller is developed by formulating a constrained optimal control problem (OCP). The constrained OCP is cast to a quadratic programming (QP) problem, making it possible to employ computationally efficient QP solvers to solve the constrained OCP. As a result, real-time control is guaranteed. Finally, experiments on a robot manipulator are implemented to verify the effectiveness of the developed incremental model predictive controller.

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Publication Details

Published
2024-11-03
DOI
https://doi.org/10.1109/iecon55916.2024.10905572
Primary Topic
Advanced Control Systems Optimization
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
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article

Incremental Model Predictive Control for Velocity-Controlled Robot Manipulators

Hengrui Li, Cong Li, Yongchao Wang, Fangzhou Liu
Advanced Control Systems Optimization
article

Incremental Model Predictive Control for Velocity-Controlled Robot Manipulators

Hengrui Li, Cong Li, Yongchao Wang, Fangzhou Liu
article en

Abstract

In this article, an incremental model predictive controller is proposed for the velocity-controlled robot manipulator. First, the time-delay estimation (TDE) technique is used to approximate the unknown discrepancy between the command and the real joint velocity due to velocity dynamics, and the equation of motion in the incremental form is obtained. Then, on the basis of the resulting equation of motion and taking into account joint position and velocity constraints, the incremental model predictive controller is developed by formulating a constrained optimal control problem (OCP). The constrained OCP is cast to a quadratic programming (QP) problem, making it possible to employ computationally efficient QP solvers to solve the constrained OCP. As a result, real-time control is guaranteed. Finally, experiments on a robot manipulator are implemented to verify the effectiveness of the developed incremental model predictive controller.

Xidian University (CN), National University of Defense Technology (CN), Harbin Institute of Technology (CN)
National Science Foundation
Openalex Percentile: Top 65%
Advanced Control Systems Optimization
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