Adaptive fuzzy tracking switching control for unknown nonstrict-feedback nonlinear systems | Zendy

Yaguang Li | Zendy; Han Zhang | Zendy; Fei Wu | Zendy; Feifei He | Zendy; Jiacheng Ma | Zendy; Yingxin Song | Zendy

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Adaptive fuzzy tracking switching control for unknown nonstrict-feedback nonlinear systems

Author(s) -

Yaguang Li,

Han Zhang,

Fei Wu,

Feifei He,

Jiacheng Ma,

Yingxin Song

Publication year - 2025

Publication title -

ieee access

Language(s) - English

Resource type - Magazines

SCImago Journal Rank - 0.587

H-Index - 127

eISSN - 2169-3536

DOI - 10.1109/access.2025.3608714

Subject(s) - aerospace , bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , engineered materials, dielectrics and plasmas , engineering profession , fields, waves and electromagnetics , general topics for engineers , geoscience , nuclear engineering , photonics and electrooptics , power, energy and industry applications , robotics and control systems , signal processing and analysis , transportation

This paper investigates an adaptive switching control strategy for output tracking in unknown n -dimensional nonstrict-feedback nonlinear systems (NFSs). To address the challenges posed by the unknown nonstrict terms (each involving all state variables), fuzzy systems are employed for function approximation. Specifically, a novel fuzzy basis function inequality is developed to enlarge the modulus of the fuzzy system in a way that restricts its dependence to only the first i state variables. This facilitates a smooth implementation of the backstepping design. Furthermore, by introducing switching functions, a switching controller is constructed to guarantee the convergence of the tracking error within a predetermined time. The controller ensures that the absolute tracking error eventually falls below a prescribed positive threshold, thereby achieving practical finite-time stability for the NFS. Simulation studies are conducted to validate the feasibility, effectiveness, and robustness of the proposed control scheme.

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