4.8 Article

Fuzzy Functional Observer-Based Finite-Time Adaptive Sliding-Mode Control for Nonlinear Systems With Matched Uncertainties

Journal

IEEE TRANSACTIONS ON FUZZY SYSTEMS
Volume 30, Issue 4, Pages 918-932

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TFUZZ.2021.3050846

Keywords

Adaptive integral sliding-mode control (SMC); finite time boundedness (FTB); fuzzy Lyapunov functional; fuzzy functional observer (FFO); H-infinity control

Funding

  1. National Natural Science Foundation of China [61773099, 62022044]
  2. Jiangsu Natural Science Foundation for Distinguished Young Scholars [BK20190039]

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This article presents a fuzzy functional observer-based finite-time adaptive sliding-mode control method for nonlinear systems, which reduces conservatism and increases solution space by introducing relaxed matrices and fuzzy Lyapunov functional approach.
This article is concerned with the fuzzy functional observer-based finite-time adaptive sliding-mode control for non-linear systems with the partly unmeasurable states and some matched uncertainties. First, considering that the upper bound of the uncertain function exists but unknown, a fuzzy functional observer (FFO) with an adaptive compensator is constructed. Second, an FFO-based fuzzy integral sliding mode controller (ISMCr) is designed such that the closed-loop fuzzy systems are finite-time bounded with H-infinity performance over the reaching phase, the sliding phase, and the whole finite-time interval, respectively. To reduce the conservatism and increase the solution space of linear matrix inequality conditions, the fuzzy Lyapunov functional approach and equivalent fuzzy relaxed matrices technique are developed by introducing some relaxed matrices in the derivative of the fuzzy normalized membership function. Compared with the common Luenberger-type observer-based approach, the gain matrices of ISMCr depend on the FFO designed, which also enhances the flexibility of controller design. Finally, a simulation example with some comparison is given to show the effectiveness of the proposed method.

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