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Journal ArticleDOI

Fuzzy adaptive observer backstepping control for MIMO nonlinear systems

Tong Shaocheng, +2 more
- 01 Oct 2009 - 
- Vol. 160, Iss: 19, pp 2755-2775
TLDR
It is proved that the proposed fuzzy adaptive control approach can guarantee the semi-global uniform ultimate boundedness for all the signals and the tracking error to a small neighborhood of the origin.
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This article is published in Fuzzy Sets and Systems.The article was published on 2009-10-01. It has received 272 citations till now. The article focuses on the topics: Adaptive neuro fuzzy inference system & Fuzzy control system.

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Citations
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Journal ArticleDOI

Observer-Based Adaptive Fuzzy Backstepping Control for a Class of Stochastic Nonlinear Strict-Feedback Systems

TL;DR: It is proved that these two control approaches can guarantee that all the signals of the closed-loop system are semi-globally uniformly ultimately bounded (SGUUB) in mean square, and the observer errors and the output of the system converge to a small neighborhood of the origin.
Journal ArticleDOI

Observer-Based Adaptive Backstepping Consensus Tracking Control for High-Order Nonlinear Semi-Strict-Feedback Multiagent Systems

TL;DR: An observer-based adaptive consensus tracking control strategy is developed for a class of high-order nonlinear multiagent systems, of which each follower agent is modeled in a semi-strict-feedback form.
Journal ArticleDOI

Observer-Based Adaptive Fuzzy Tracking Control of MIMO Stochastic Nonlinear Systems With Unknown Control Directions and Unknown Dead Zones

TL;DR: The main features of the proposed adaptive control approach are that it can guarantee the stability of the closed-loop system, and the tracking errors converge to a small neighborhood of zero, and it can solve the problems of unknown control direction, unknown dead-zone, and unmeasured states simultaneously.
Journal ArticleDOI

Composite Adaptive Fuzzy Output Feedback Control Design for Uncertain Nonlinear Strict-Feedback Systems With Input Saturation

TL;DR: A new fuzzy controller with the composite parameters adaptive laws are developed and it is proved that all the signals of the closed-loop system are bounded and the system output can follow the given bounded reference signal.
Journal ArticleDOI

Observer-Based Adaptive Fuzzy Backstepping Dynamic Surface Control for a Class of MIMO Nonlinear Systems

TL;DR: An adaptive fuzzy backstepping dynamic surface control approach is developed for a class of multiple-input-multiple-output nonlinear systems with immeasurable states and is proved that all the signals of the closed-loop adaptive-control system are semiglobally uniformly ultimately bounded, and the tracking errors converge to a small neighborhood of the origin.
References
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Book

Nonlinear and adaptive control design

TL;DR: In this paper, the focus is on adaptive nonlinear control results introduced with the new recursive design methodology -adaptive backstepping, and basic tools for nonadaptive BackStepping design with state and output feedbacks.
Book

Adaptive Fuzzy Systems and Control: Design and Stability Analysis

TL;DR: This paper presents a meta-analysis of the design and stability analysis of fuzzy identifiers of nonlinear dynamic systems fuzzy adaptive filters of adaptive fuzzy controllers using input-output linearization concepts.
Journal ArticleDOI

Systematic design of adaptive controllers for feedback linearizable systems

TL;DR: A systematic procedure for the design of adaptive regulation and tracking schemes for a class of feedback linearizable nonlinear systems is developed, which substantially enlarges the class of non linear systems with unknown parameters for which global stabilization can be achieved.
Journal ArticleDOI

H/sup /spl infin// tracking design of uncertain nonlinear SISO systems: adaptive fuzzy approach

TL;DR: Computer simulation results confirm that the effect of both the fuzzy approximation error and external disturbance on the tracking error can be attenuated efficiently by the proposed adaptive fuzzy control algorithm.
Journal ArticleDOI

Stable adaptive control using fuzzy systems and neural networks

TL;DR: It is proved that with or without such knowledge both adaptive schemes can "learn" how to control the plant, provide for bounded internal signals, and achieve asymptotically stable tracking of a reference input.
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