Decentralized direct adaptive output feedback fuzzy H ∞ tracking design of large-scale nonaffine nonlinear systems

Huang, Yeou‐Lih; Zhou, Dequn; Chen, Xiaoxin

doi:10.1007/s11071-009-9468-1

Cited by 26 publications

(28 citation statements)

References 47 publications

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“…It should be accentuated that Assumption 3 and Assumption 2 do not pose strong restrictions upon the class of interconnected systems, because they both are able to be met by a variety of practical large-scale nonlinear systems given in [30,31,33,34,36,37,[39][40][41][42]. Furthermore, Chua's circuits, aircraft wing rocks, Duffing chaotic systems, and induction servo-motor drives are none other than their special cases.…”

Section: Remarkmentioning

confidence: 99%

“…However, the intelligent control algorithms take full state feedback schemes. In contrast, decentralized output feedback fuzzy or neural control schemes were introduced for interrelated nonlinear systems in the papers [36][37][38][39][40][41][42][43][44]. Notwithstanding, there exist the following disadvantages in the matter of practical application.…”

Section: Introductionmentioning

confidence: 99%

“…Firstly, the decentralized IAC or DAC designs based upon radial basis neural networks need to presuppose that the input gains are positive constants rather than unknown nonlinearities in [36][37][38], where backstepping techniques were utilized. Secondly, although the decentralized IAFC or DAFC syntheses have been introduced predicated upon H ∞ tracking control methodology in [39][40][41], they still cannot dispense with the conservative assumption that the modeling error stays squared integrable. Thirdly, it is worthwhile to be noted in the articles [36,37,41,42] that either cooperation or communication is required between all the individual subsystems such that none of the proposed decentralized control algorithms numbers among strict (or classical) decentralized control technique in nature.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Decentralized adaptive output feedback fuzzy controller for a class of large-scale nonlinear systems

Huang

Zhou

2010

Nonlinear Dyn

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In the previous work of Huang et al., a coordinated decentralized hybrid adaptive output feedback fuzzy control scheme of large-scale nonlinear systems is obtained predicated upon this prerequisite assumption that the local controllers can share the a priori information about their individual reference models. In this note, we concentrate in the absence of the coordination assumption on developing a classical decentralized combined indirect and direct adaptive fuzzy controller for a class of uncertain large-scale nonlinear systems. The output feedback and adaptation mechanisms proposed for each subsystem hinges just upon its individual output, regardless of any other output reference. Neither the famous strictly positive real (SPR) condition nor a high-gain observer (HGO) is required to realize the overall output feedback algorithm. The tracking errors of the closed-loop largescale system are shown to converge to tunable neighborhoods of the origin. Simulation results on correlated inverted pendulums verify the validity of the decentralized controller modification.

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Section: Remarkmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Decentralized adaptive output feedback fuzzy controller for a class of large-scale nonlinear systems

Huang

Zhou

2010

Nonlinear Dyn

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“…Various adaptive fuzzy and neural decentralized control approaches have been developed for large-scale nonlinear systems [3][4][5][6][7]. Generally, adaptive fuzzy and neural decentralized control approaches can deal with a larger class of largescale systems with unknown nonlinear functions or without a priori knowledge about the interconnections, and can achieve satisfactory control performances.…”

Section: Introductionmentioning

confidence: 99%

Adaptive fuzzy decentralized control for nonlinear large-scale systems based on high-gain observer

Tong

Ren

2011

Sci. China Inf. Sci.

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An adaptive fuzzy decentralized backstepping output-feedback control approach is proposed for a class of nonlinear large-scale systems with completely unknown functions, the interconnections mismatched in control inputs, and without the measurements of the states. Fuzzy logic systems are employed to approximate the unknown nonlinear functions, and an adaptive high-gain observer is developed to estimate the unmeasured states. Using the designed high-gain observer, and combining the fuzzy adaptive control theory with backstepping approach, an adaptive fuzzy decentralized backstepping output-feedback control scheme is developed. It is proved that the proposed control approach can guarantee that all the signals of the closed-loop system are semiglobally uniformly ultimately bounded (SUUB), and that the observer errors and the tracking errors converge to a small neighborhood of the origin by appropriate choice of the design parameters. Finally, a simulation example is provided to show the effectiveness of the proposed approach.Keywords nonlinear large-scale systems, fuzzy logic system, high-gain state observer, adaptive decentralized control, stability analysis CitationTong S C, Ren C E, Li Y M. Adaptive fuzzy decentralized control for nonlinear large-scale systems based on high-gain observer.

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“…The direct adaptive output-feedback control approaches using FLS or FNN were also given in [19][20][21]. The combined adaptive output-feedback control schemes are designed in [22,23]. These results proposed in [15-20, 22, 23] can guarantee that the corresponding closed-loop system is stable in the sense of the Lyapunov stability theory.…”

Section: Introductionmentioning

confidence: 99%

Adaptive fuzzy output-feedback control of uncertain SISO nonlinear systems

Liu

2010

Nonlinear Dyn

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The output-feedback control problem of a class of uncertain SISO nonlinear systems is investigated based on an indirect adaptive fuzzy approach. Because the system states are not required to be available for measurement, an observer is designed to estimate the system states. Compared with the existing results in the observer design, the main advantages of the proposed adaptive fuzzy output-feedback control approach are as follows: (1) It does not require to assume that the sign of the control gain coefficient is known and Nussbaum-gain technique is utilized to control the nonlinear systems with both the unknown control direction and the unmeasured states; (2) The observer in this paper is designed for the states rather than the tracking errors, then it is convenient to compute; (3) The controller singularity problem is perfectly avoided. The stability of the closed-loop system is analyzed by using Lyapunov method. A simulation example is given to verify the feasibility of the proposed approach.

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Decentralized direct adaptive output feedback fuzzy H ∞ tracking design of large-scale nonaffine nonlinear systems

Cited by 26 publications

References 47 publications

Decentralized adaptive output feedback fuzzy controller for a class of large-scale nonlinear systems

Decentralized adaptive output feedback fuzzy controller for a class of large-scale nonlinear systems

Adaptive fuzzy decentralized control for nonlinear large-scale systems based on high-gain observer

Adaptive fuzzy output-feedback control of uncertain SISO nonlinear systems

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