Fuzzy Adaptive Fault-Tolerant Control of Fractional-Order Nonlinear Systems

Li, Yuan‐Xin; Wang, Quanyu; Tong, Shaocheng

doi:10.1109/tsmc.2019.2894663

Cited by 68 publications

(47 citation statements)

References 52 publications

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“…Such inequalities have been considerately used for facilitating Lyapunov based stability analysis (e.g. in global stability analysis in fractionalorder neural networks [71] and in time-delay systems [72]) and introducing Lyapunov based control methods (for example, in design of stabilizing static controllers [73] and adaptive ones [74] [75] for nonlinear fractional-order systems). It is worth noting that for using the inequalities in the form (23), the assumption on differentiability of x(t) is required, whereas in the general case the solution of system (18) may be not differentiable (for more details, see [76]).…”

Section: Stability Analysis Based On Lyapunov Direct Methodsmentioning

confidence: 99%

Nonlinear Fractional-Order Circuits and Systems: Motivation, A Brief Overview, and Some Future Directions

Tavazoei

Tavakoli-Kakhki

Bizzarri

2020

IEEE Open J. Circuits Syst.

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In recent years, fractional-order differential operators, and the dynamic models constructed based on these generalized operators have been widely considered in design and practical implementation of electrical circuits and systems. Simultaneously, facing with fractional-order dynamics and the nonlinear ones in electrical circuits and systems enforces us to use more advanced tools (in comparison to those commonly used in design and analysis of linear fractional-order/nonlinear integer-order circuits and systems) for their analysis, design, and implementation. Discussing on such a motivation, this tutorial paper aims to provide an overview on the recent achievements in proposing effective tools for analysis and design of nonlinear fractional-order circuits and systems. Moreover, some open problems, which can specify future directions for continuing research works on the aforementioned subject, are discussed.

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Section: Stability Analysis Based On Lyapunov Direct Methodsmentioning

confidence: 99%

Nonlinear Fractional-Order Circuits and Systems: Motivation, A Brief Overview, and Some Future Directions

Tavazoei

Tavakoli-Kakhki

Bizzarri

2020

IEEE Open J. Circuits Syst.

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“…where w * i,j ideal parameter vectors defined over bounded sets Ω i,j , and δ i,j satisfies |δ i,j | ≤ δ * i,j with δ * i,j > 0. Remark 4: It is worth noting that, like references [9,12,35,39], this paper selects FLSs as the approximator to address unknown nonlinear functions in the controlled systems (1). However, there are some other nonlinear approximators, such as NNs [10,11,13,38,40] and neuro-fuzzy network system [15,36], which can replace FLSs and achieve the same purpose.…”

Section: B Preliminariesmentioning

confidence: 99%

Adaptive Fuzzy Decentralized Control for Fractional-Order Nonlinear Large-Scale Systems With Unmodeled Dynamics

et al. 2021

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This paper addresses the decentralized control issue for the fractional-order (FO) nonlinear large-scale strict-feedback systems with unmodeled dynamics. The unknown nonlinear functions are identified by fuzzy logic systems (FLSs) and the FO dynamic signals are introduced to dominate the unmodeled dynamics. Additionally, the fractional-order dynamic surface control (FODSC) design technique is introduced into the adaptive backstepping control algorithm to avoid the issue of "explosion of complexity". Then, an adaptive fuzzy decentralized control scheme is developed via the FO Lyapunov stability criterion. It is proved that the controlled FO systems are stable and the tracking errors can converge to a small neighborhood of zero. The simulation example is provided to confirm the validity of the put forward control scheme.INDEX TERMS Fractional-order system, large-scale systems, DSC, adaptive fuzzy decentralized control, backstepping, unmodeled dynamics.

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“…Thus, FOS is attracting more and more attention. A large number of work on FOS have been reported, such as stability [5–8], robust control [9–11], fuzzy control [12, 13] and sliding mode control [14].…”

Section: Introductionmentioning

confidence: 99%

Static and dynamic output feedback stabilisation of descriptor fractional order systems

Zhang

Zhao

Wang

2020

IET Control Theory & Applications

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Fuzzy Adaptive Fault-Tolerant Control of Fractional-Order Nonlinear Systems

Cited by 68 publications

References 52 publications

Nonlinear Fractional-Order Circuits and Systems: Motivation, A Brief Overview, and Some Future Directions

Nonlinear Fractional-Order Circuits and Systems: Motivation, A Brief Overview, and Some Future Directions

Adaptive Fuzzy Decentralized Control for Fractional-Order Nonlinear Large-Scale Systems With Unmodeled Dynamics

Static and dynamic output feedback stabilisation of descriptor fractional order systems

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