The tracking performance of a robot manipulator is controlled using nonlinear active disturbance rejection control (ADRC). The proposed method does not require the complete knowledge of the plant’s parameters, and external disturbances since it is based on the rejection and estimation of the unknown internal dynamics and external disturbances. The proposed method is simple and has minimal tuning parameters. The robustness of the proposed method is discussed against parameter uncertainties and disturbances. First, the mathematical model of the manipulator is developed. ADRC theory is explained. The manipulator is represented in ADRC form. ADRC’s tracking performance for the joints and end-effector is compared to the tracking performance of the robust passivity (RP) control. The simulations prove that the proposed control method achieves good tracking performance compared to RP control. It is shown that ADRC has a lower energy consumption compared to RP control by calculating the power in the input signals.
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ASME 2017 Dynamic Systems and Control Conference
October 11–13, 2017
Tysons, Virginia, USA
Conference Sponsors:
- Dynamic Systems and Control Division
ISBN:
978-0-7918-5828-8
PROCEEDINGS PAPER
Trajectory Tracking Control for a Robotic Manipulator Using Nonlinear Active Disturbance Rejection Control
Mohammed Ali,
Mohammed Ali
Cleveland State University, Cleveland, OH
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Charles K. Alexander
Charles K. Alexander
Cleveland State University, Cleveland, OH
Search for other works by this author on:
Mohammed Ali
Cleveland State University, Cleveland, OH
Charles K. Alexander
Cleveland State University, Cleveland, OH
Paper No:
DSCC2017-5088, V002T12A002; 8 pages
Published Online:
November 14, 2017
Citation
Ali, M, & Alexander, CK. "Trajectory Tracking Control for a Robotic Manipulator Using Nonlinear Active Disturbance Rejection Control." Proceedings of the ASME 2017 Dynamic Systems and Control Conference. Volume 2: Mechatronics; Estimation and Identification; Uncertain Systems and Robustness; Path Planning and Motion Control; Tracking Control Systems; Multi-Agent and Networked Systems; Manufacturing; Intelligent Transportation and Vehicles; Sensors and Actuators; Diagnostics and Detection; Unmanned, Ground and Surface Robotics; Motion and Vibration Control Applications. Tysons, Virginia, USA. October 11–13, 2017. V002T12A002. ASME. https://doi.org/10.1115/DSCC2017-5088
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