Adaptive Control of a Two-Link Robot Using Batch Least-Square Identifier

Mostafa Bagheri; Iasson Karafyllis; Peiman Naseradinmousavi; Miroslav Krstić

doi:10.1109/JAS.2020.1003459

Volume 8 Issue 1

Jan. 2021

IEEE/CAA Journal of Automatica Sinica

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Article Navigation > IEEE/CAA Journal of Automatica Sinica > 2021 > 8(1): 86-93

Mostafa Bagheri, Iasson Karafyllis, Peiman Naseradinmousavi and Miroslav Krstić, "Adaptive Control of a Two-Link Robot Using Batch Least-Square Identifier," IEEE/CAA J. Autom. Sinica, vol. 8, no. 1, pp. 86-93, Jan. 2021. doi: 10.1109/JAS.2020.1003459

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Mostafa Bagheri, Iasson Karafyllis, Peiman Naseradinmousavi and Miroslav Krstić, "Adaptive Control of a Two-Link Robot Using Batch Least-Square Identifier," IEEE/CAA J. Autom. Sinica, vol. 8, no. 1, pp. 86-93, Jan. 2021. doi: 10.1109/JAS.2020.1003459

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Adaptive Control of a Two-Link Robot Using Batch Least-Square Identifier

doi: 10.1109/JAS.2020.1003459

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Author Bio:
Mostafa Bagheri is the Chief Technology Officer of NXT Robotics Corporation and a research assistant at the University of California San Diego and San Diego State University (SDSU). He received his Ph.D. in mechanical and aerospace engineering from UC San Diego & SDSU in 2019. He received his B.Sc. and M.Sc. degrees in mechanical engineering in 2010 and 2013, respectively, from Amirkabir University of Technology (Tehran Polytechnic). He won the 2011 best B.Sc. thesis annual award in mechanical engineering by ISME. Bagheri was a graduate researcher in the Department of Advanced Robotics at Italian Institute of Technology (IIT), and worked on WALK-MAN humanoid robot in 2014. His research interests include robotics, control theory, delay systems, adaptive control & identification, and extremum seeking

Iasson Karafyllis is an Associate Professor in the Department of Mathematics, National Technical University of Athens (NTUA), Greece. He is a coauthor (with Z.-P. Jiang) of the book Stability and Stabilization of Nonlinear Systems, Springer-Verlag London (Series: Communications and Control Engineering), 2011 and a coauthor (with M. Krstić) of the books Predictor Feedback for Delay Systems: Implementations and Approximations, Birkhäuser, Boston (Series: Mathematics, Systems & Control: Foundations & Applications), 2017 and Input-to-State Stability for PDEs, Springer-Verlag London (Series: Communications and Control Engineering), 2019. Since 2013 he is an Associate Editor for the International Journal of Control and for the IMA Journal of Mathematical Control and Information. His research interests include mathematical control theory and nonlinear systems theory

Peiman Naseradinmousavi is an Associate Professor of the Mechanical Engineering Department at Dynamic Systems and Control Laboratory (DSCL) of San Diego State University. He received his Ph.D. and B.Sc. degrees in mechanical engineering (dynamics and control) from Villanova and Tabriz universities in 2012 and 2002, respectively. His research interests include robotics, smart flow distribution network, nonlinear dynamics, control theory, optimization, magnetic bearings, and mathematical modeling. He serves as Associate Editor of ASME Letters in Dynamic Systems and Control, and the Journal of Vibration and Control (JVC)

Miroslav Krstić is Distinguished Professor of Mechanical and Aerospace Engineering, holds the Alspach endowed chair, and is the founding director of the Cymer Center for Control Systems and Dynamics at UC San Diego. He also serves as Senior Associate Vice Chancellor for Research at UCSD. As a graduate student, Krstić won the UC Santa Barbara best dissertation award and student best paper awards at CDC and ACC. Krstić has been elected Fellow of seven scientific societies - IEEE, IFAC, ASME, SIAM, AAAS, IET (UK), and AIAA (Assoc. Fellow) - and as a foreign member of the Serbian Academy of Sciences and Arts and of the Academy of Engineering of Serbia. He has received the SIAM Reid Prize, ASME Oldenburger Medal, Nyquist Lecture Prize, Paynter Outstanding Investigator Award, Ragazzini Education Award, Chestnut textbook prize, Control Systems Society Distinguished Member Award, the PECASE, NSF Career, and ONR Young Investigator awards, the Axelby and Schuck paper prizes, and the first UCSD Research Award given to an engineer. Krstić has also been awarded the Springer Visiting Professorship at UC Berkeley, the Distinguished Visiting Fellowship of the Royal Academy of Engineering, and the Invitation Fellowship of the Japan Society for the Promotion of Science. He serves as Editor-in-Chief of Systems & Control Letters and has been serving as Senior Editor in Automatica and IEEE Transactions on Automatic Control, as editor of two Springer book series, and has served as Vice President for Technical Activities of the IEEE Control Systems Society and as Chair of the IEEE CSS Fellow Committee. Krstić has coauthored thirteen books on adaptive, nonlinear, and stochastic control, extremum seeking, control of PDE systems including turbulent flows, and control of delay systems
Corresponding author: M. Bagheri is with the Department of Mechanical and Aerospace Engineering, University of California San Diego and San Diego State University, La Jolla, CA 92037 USA (e-mail: mstf.bagheri@gmail.com)
Received Date: 2020-07-01
Accepted Date: 2020-08-01

Available Online: 2020-08-27

Abstract

Abstract

We design a regulation-triggered adaptive controller for robot manipulators to efficiently estimate unknown parameters and to achieve asymptotic stability in the presence of coupled uncertainties. Robot manipulators are widely used in telemanipulation systems where they are subject to model and environmental uncertainties. Using conventional control algorithms on such systems can cause not only poor control performance, but also expensive computational costs and catastrophic instabilities. Therefore, system uncertainties need to be estimated through designing a computationally efficient adaptive control law. We focus on robot manipulators as an example of a highly nonlinear system. As a case study, a 2-DOF manipulator subject to four parametric uncertainties is investigated. First, the dynamic equations of the manipulator are derived, and the corresponding regressor matrix is constructed for the unknown parameters. For a general nonlinear system, a theorem is presented to guarantee the asymptotic stability of the system and the convergence of parameters’ estimations. Finally, simulation results are discussed for a two-link manipulator, and the performance of the proposed scheme is thoroughly evaluated.
- Backstepping,
- least-square identifier,
- robot manipulators,
- trigger-based adaptive control

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References

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First application in robotics of regulation-triggered adaptive control with batch least-squares (BaLSI) identification.
Performs piecewise-constant, rather than continuous, updates of parameter estimates.
Parameter estimation settles in finite time and reaches the true unknown parameters, even in the absence of persistency of excitation.
After a finite learning transient, recovers the performance of the non-adaptive design, including exponential regulation.

Adaptive Control of a Two-Link Robot Using Batch Least-Square Identifier

doi: 10.1109/JAS.2020.1003459

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