In this paper, a predictor-based controller for a 7-DOF Baxter manipulator is formulated to compensate a time-invariant input delay during a pick-and-place task. Robot manipulators are extensively employed because of their reliable, fast, and precise motions although they are subject to large time delays like many engineering systems. The time delay may lead to the lack of high precision required and even catastrophic instability. Using common control approaches on such delay systems can cause poor control performance, and uncompensated input delays can produce hazards when used in engineering applications. Therefore, destabilizing time delays need to be regarded in designing control law. First, delay-free dynamic equations are derived using the Lagrangian method. Then, we formulate a predictor-based controller for a 7-DOF Baxter manipulator, in the presence of input delay, in order to track desirable trajectories. Finally, the results are experimentally evaluated.
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ASME 2018 Dynamic Systems and Control Conference
September 30–October 3, 2018
Atlanta, Georgia, USA
Conference Sponsors:
- Dynamic Systems and Control Division
ISBN:
978-0-7918-5189-0
PROCEEDINGS PAPER
Analytical and Experimental Predictor-Based Time Delay Control of Baxter Robot
Mostafa Bagheri,
Mostafa Bagheri
University of California San Diego, La Jolla, CA
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Miroslav Krstić,
Miroslav Krstić
University of California San Diego, La Jolla, CA
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Peiman Naseradinmousavi
Peiman Naseradinmousavi
San Diego State University, San Diego, CA
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Mostafa Bagheri
University of California San Diego, La Jolla, CA
Miroslav Krstić
University of California San Diego, La Jolla, CA
Peiman Naseradinmousavi
San Diego State University, San Diego, CA
Paper No:
DSCC2018-9101, V001T04A011; 9 pages
Published Online:
November 12, 2018
Citation
Bagheri, M, Krstić, M, & Naseradinmousavi, P. "Analytical and Experimental Predictor-Based Time Delay Control of Baxter Robot." Proceedings of the ASME 2018 Dynamic Systems and Control Conference. Volume 1: Advances in Control Design Methods; Advances in Nonlinear Control; Advances in Robotics; Assistive and Rehabilitation Robotics; Automotive Dynamics and Emerging Powertrain Technologies; Automotive Systems; Bio Engineering Applications; Bio-Mechatronics and Physical Human Robot Interaction; Biomedical and Neural Systems; Biomedical and Neural Systems Modeling, Diagnostics, and Healthcare. Atlanta, Georgia, USA. September 30–October 3, 2018. V001T04A011. ASME. https://doi.org/10.1115/DSCC2018-9101
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