Takagi-Sugeno fuzzy control for a wide class of fractional-order chaotic systems with uncertain parameters via linear matrix inequality

Wang, Bin; Xue, Jianyi; Chen, Diyi

doi:10.1177/1077546314546682

Cited by 40 publications

(28 citation statements)

References 32 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Yet, several authors are also interested in the synchronization of the fractional-order a e-mail: g.litak@pollub.pl chaotic systems [22,23,[26][27][28][29][30][31][32][33][34][35]. The transient time preceding the synchronization state of chaotic oscillators is crucial as it unfortunately corresponds to the laps of time during which the encoded message cannot be recovered or sent.…”

Section: Introductionmentioning

confidence: 99%

Finite-time synchronization of fractional-order simplest two-component chaotic oscillators

et al. 2017

View full text Add to dashboard Cite

Abstract. The problem of finite-time synchronization of fractional-order simplest two-component chaotic oscillators operating at high frequency and application to digital cryptography is addressed. After the investigation of numerical chaotic behavior in the system, an adaptive feedback controller is designed to achieve the finite-time synchronization of two oscillators, based on the Lyapunov function. This controller could find application in many other fractional-order chaotic circuits. Applying synchronized fractionalorder systems in digital cryptography, a well secured key system is obtained. Numerical simulations are given to illustrate and verify the analytic results.

show abstract

Section: Introductionmentioning

confidence: 99%

Finite-time synchronization of fractional-order simplest two-component chaotic oscillators

et al. 2017

View full text Add to dashboard Cite

show abstract

“…To compare the performance of the proposed control scheme, Fig. 3 shows the simulation results of the proposed scheme, controller (9) in [44] as well as the traditional PID control. From Fig.…”

Section: Simulation Resultsmentioning

confidence: 99%

Fuzzy generalised predictive control for a fractional‐order nonlinear hydro‐turbine regulating system

Shi

Wang

Chen

2018

IET Renewable Power Generation

Self Cite

View full text Add to dashboard Cite

This study focuses on a fuzzy generalised predictive control method for a fractional-order hydro-turbine regulating system (HTRS). Based on the Grünwald-Letnikov (G-L) definition of fractional calculus and discretisation, the fractional-order hydraulic servo system is transformed into the standard controlled autoregressive integrating moving average (CARMA) model. With the help of fuzzy linearisation theory, the fuzzy predictive model of the integer-order part of the HTRS is presented. Furthermore, by using the fourth-order Runge-Kutta algorithm, the obtained fuzzy predictive model can be easily transformed into the CARMA model. Then, based on the overall CARMA model and the generalised predictive control theory, a novel nonlinear fuzzy generalised predictive controller is designed for the fractional-order HTRS. Finally, numerical simulations are implemented to verify the validity and superiority of the proposed method. It also provides a reference for relevant hydropower systems.

show abstract

“…Recently in [2], a new receding horizon disturbance attenuator (RHDA) for Takagi-Sugeno (T-S) fuzzy switched Hopfield neural networks with external disturbance has been investigated. Recently, many authors have paid much effort to the research on fuzzy logic into neural network [3][4][5][6][7][8][9].…”

Section: Introductionmentioning

confidence: 99%

Dissipativity and passivity analysis of T–S fuzzy neural networks with probabilistic time-varying delays: a quadratic convex combination approach

Nagamani

Radhika

2015

Nonlinear Dyn

View full text Add to dashboard Cite

This paper studied dissipativity and passivity analysis of T-S fuzzy neural networks with distributed and probabilistic time-varying delay via quadratic convex combination approach. By introducing a stochastic variable with the Bernoulli distribution, the fuzzy neural networks with random time delays are transformed into one with deterministic delays and stochastic parameters. Moreover, it is well known that the dissipativity behavior of fuzzy neural networks is very sensitive to the time delay in the leakage term. By constructing proper Lyapunov-Krasovskii functional, new delay-dependent dissipativity and passivity conditions are derived in terms of linear matrix inequalities. Different from previous results, involving the first-order convex combination property, our derivation applies the idea of second-order convex combination and the property of quadratic convex function. Finally, numerical examples are provided to verify the effectiveness of the presented results.

show abstract

Takagi-Sugeno fuzzy control for a wide class of fractional-order chaotic systems with uncertain parameters via linear matrix inequality

Cited by 40 publications

References 32 publications

Finite-time synchronization of fractional-order simplest two-component chaotic oscillators

Finite-time synchronization of fractional-order simplest two-component chaotic oscillators

Fuzzy generalised predictive control for a fractional‐order nonlinear hydro‐turbine regulating system

Dissipativity and passivity analysis of T–S fuzzy neural networks with probabilistic time-varying delays: a quadratic convex combination approach

Contact Info

Product

Resources

About