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Robust Adaptive Fuzzy Tracking Control for Pure-Feedback Stochastic Nonlinear Systems With Input Constraints

Wang, Huanqing, Chen, Bing, Liu, Xiaoping, Liu, Kefu, Lin, Chong·2013·IEEE Transactions on Cybernetics

Abstract

This paper is concerned with the problem of adaptive fuzzy tracking control for a class of pure-feedback stochastic nonlinear systems with input saturation. To overcome the design difficulty from nondifferential saturation nonlinearity, a smooth nonlinear function of the control input signal is first introduced to approximate the saturation function; then, an adaptive fuzzy tracking controller based on the mean-value theorem is constructed by using backstepping technique. The proposed adaptive fuzzy controller guarantees that all signals in the closed-loop system are bounded in probability and the system output eventually converges to a small neighborhood of the desired reference signal in the sense of mean quartic value. Simulation results further illustrate the effectiveness of the proposed control scheme.

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Metadata

Authors
Wang, H., Chen, B., Liu, X., Liu, K., & Lin, C.
Venue
IEEE Transactions on Cybernetics
Published
2013-12
Volume
43
Issue
6
Pages
2093-2104
ISSN
  • 2168-2267 (ISSN-L)
  • 2168-2275
OpenAlex
W2086186132
Cited by
445
References
0
FWCI
50.42
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Robust Adaptive Fuzzy Tracking Control for Pure-Feedback Stochastic Nonlinear Systems With Input Constraints. https://app.cochat.ai/papers/10.1109/tcyb.2013.2240296
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Wang, H., Chen, B., Liu, X., Liu, K., & Lin, C. (2013). Robust Adaptive Fuzzy Tracking Control for Pure-Feedback Stochastic Nonlinear Systems With Input Constraints. IEEE Transactions on Cybernetics. https://doi.org/10.1109/tcyb.2013.2240296

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