Closed-Loop Error Learning Control for Uncertain Nonlinear Systems With Experimental Validation on a Mobile Robot

Kayacan, Erkan

doi:10.1109/tmech.2019.2932757

Closed-Loop Error Learning Control for Uncertain Nonlinear Systems With Experimental Validation on a Mobile Robot

Journal Article · Mon Aug 05 00:00:00 EDT 2019 · IEEE/ASME Transactions on Mechatronics

DOI:https://doi.org/10.1109/tmech.2019.2932757· OSTI ID:1799041

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Univ. of Queensland, Brisbane, QLD (Australia); Univ. of Queensland, Brisbane, QLD (Australia)

This article develops a closed-loop error learning control (CLELC) algorithm for feedback linearizable systems with experimental validation on a mobile robot. Traditional feedback and feedforward controllers are designed based on the nominal model by using the feedback linearization control (FLC) method. Then, an intelligent controller is designed based on the sliding mode learning algorithm that utilizes closed-loop error dynamics to learn the system behavior. The controllers are working in parallel, and the intelligent controller can gradually replace the feedback controller from the control of the system. In addition to the stability of the sliding mode learning algorithm, the closed-loop stability of an nth-order feedback linearizable system is proven. The simulation results demonstrate that the CLELC algorithm can improve control performance (e.g., smaller rise time, settling time, and overshoot) in the absence of uncertainties, and also provides robust control performance in the presence of uncertainties as compared to traditional FLC method. To test the efficiency and efficacy of the CLELC algorithm, the trajectory tracking problem of a tracked mobile robot is studied in real time. The experimental results demonstrate that the CLELC algorithm ensures highly accurate trajectory tracking performance than traditional FLC method.

View Accepted Manuscript (DOE)

Research Organization:: Univ. of Illinois at Urbana-Champaign, IL (United States)

Sponsoring Organization:: USDOE Advanced Research Projects Agency - Energy (ARPA-E)

Grant/Contract Number:: AR0000598

OSTI ID:: 1799041

Journal Information:: IEEE/ASME Transactions on Mechatronics, Journal Name: IEEE/ASME Transactions on Mechatronics Journal Issue: 5 Vol. 24; ISSN 1083-4435

Publisher:: IEEE - ASMECopyright Statement

Country of Publication:: United States

Language:: English

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