An Asymptotically Stable Self-Adjusting Adaptive Fuzzy Logic-Based Robust Controller Formulation for Robot Manipulators

YILMAZ B. M., TATLICIOĞLU E., SELİM E., Zergeroglu E.

International Journal of Robust and Nonlinear Control, cilt.36, sa.5, ss.2377-2387, 2026 (SCI-Expanded, Scopus) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 36 Sayı: 5
  • Basım Tarihi: 2026
  • Doi Numarası: 10.1002/rnc.70271
  • Dergi Adı: International Journal of Robust and Nonlinear Control
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Compendex, INSPEC, MathSciNet, zbMATH
  • Sayfa Sayıları: ss.2377-2387
  • Anahtar Kelimeler: adaptive fuzzy logic, fuzzy approximation, Lyapunov methods, robot manipulators, uncertain dynamics
  • Manisa Celal Bayar Üniversitesi Adresli: Evet

Özet

This work focuses on the trajectory tracking control of robot manipulators subject to model uncertainties and unknown additive disturbances. The controller design makes use of a self-adjusting adaptive fuzzy logic-based term, fused with a robust integral of the sign of the error feedback. In the proposed adaptive fuzzy logic framework, means and variances of the membership functions are updated dynamically during each iteration, allowing for a more precise estimation of the parametric uncertainties. The stability of the closed-loop system and the convergence properties of the states are established via Lyapunov-based arguments, where asymptotic stability of the joint tracking error is ensured. Numerical simulations have been conducted to further support the theoretical findings.