Lyapunov-guided adaptive tuning of lupaş q-bernstein polynomial coefficients for precision object handling in multi-robot electrical manipulators

Saleh Mobayen, Alireza Izadbakhsh and Paweł Skruch

Mathematics and Computers in Simulation (MATCOM), 2026, vol. 246, issue C, 414-439

Abstract: This paper presents an adaptive output feedback tracking controller for cooperative multiple electrically driven robotic arms. The main innovation lies in employing the Lupaş q-analogue of the Bernstein polynomials as an uncertainty approximator whose coefficients are updated through Lyapunov-based learning laws, marking the first engineering application of this operator within an adaptive control framework. Unlike conventional adaptive, neural, or fuzzy-based schemes, the proposed method is regressor-free, relies solely on joint-position measurements, and avoids the intricate tuning procedures and computational burden typically associated with neuro-fuzzy approximators. A rigorous Lyapunov analysis ensures that all position and force tracking errors remain uniformly ultimately bounded. The controller is implemented on a dual-arm cooperative manipulation setup and quantitatively compared with two state-of-the-art approximation techniques. The simulation results confirm the proposed method’s superior precision, robustness, and real-time efficiency in the presence of model uncertainties and external disturbances.

Keywords: Eelectrically driven cooperative arms; Lupaş q-analogue of the Bernstein polynomials; Lyapunov stability (search for similar items in EconPapers)
Date: 2026
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Persistent link: https://EconPapers.repec.org/RePEc:eee:matcom:v:246:y:2026:i:c:p:414-439

DOI: 10.1016/j.matcom.2026.02.006

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