Metaheuristic methods to identify parameters and orders of fractional-order chaotic systems

Sattar, Dunia; Braik, Malik

doi:10.1016/j.eswa.2023.120426

Cited by 6 publications

(1 citation statement)

References 55 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Fractional-order nonlinear systems (FONSs) established by fractional calculus can present the physical systems accurately for lots of different areas such as infectious diseases [1,2], image processing [3,4], secret communication [5,6], circuit [7,8], vehicle engineering [9,10], etc. Furthermore, many controller design problem for FONSs have been researched, in which the adaptive technique as a very powerful tool have been investigated by combining with backstepping mechanism to deal with the uncertainties in FONSs [11][12][13][14][15][16][17][18][19][20][21][22][23][24][25].…”

Section: Introductionmentioning

confidence: 99%

Finite-Time Adaptive Event-Triggered Control for Full States Constrained FONSs with Uncertain Parameters and Disturbances

Wang,

Li,

Liang

2024

Fractal Fract

View full text Add to dashboard Cite

This article focuses the event-triggered adaptive finite-time control scheme for the states constrained fractional-order nonlinear systems (FONSs) under uncertain parameters and external disturbances. The backstepping scheme is employed to construct the finite-time controller via a series of barrier Lyapunov function (BLF) to solve that all the state constraints are not violated. Different from the trigger condition with fixed value, the event-triggered strategy is applied to overcome the communication burden of controller caused by the limited communication resources. By utilizing fractional-order Lyapunov analysis, all variables in the resulted system are proven to be bounded, and the tracking error converges to the small neighborhood around origin in finite time and without the Zeno behavior. Finally, the effectiveness of the proposed control scheme is verified by the simulation analysis of a bus power system.

show abstract

Section: Introductionmentioning

confidence: 99%

Finite-Time Adaptive Event-Triggered Control for Full States Constrained FONSs with Uncertain Parameters and Disturbances

Wang,

Li,

Liang

2024

Fractal Fract

View full text Add to dashboard Cite

show abstract

An in-depth survey of the artificial gorilla troops optimizer: outcomes, variations, and applications

Hussien,

Bouaouda,

Alzaqebah

et al. 2024

Artif Intell Rev

View full text Add to dashboard Cite

A recently developed algorithm inspired by natural processes, known as the Artificial Gorilla Troops Optimizer (GTO), boasts a straightforward structure, unique stabilizing features, and notably high effectiveness. Its primary objective is to efficiently find solutions for a wide array of challenges, whether they involve constraints or not. The GTO takes its inspiration from the behavior of Gorilla Troops in the natural world. To emulate the impact of gorillas at each stage of the search process, the GTO employs a flexible weighting mechanism rooted in its concept. Its exceptional qualities, including its independence from derivatives, lack of parameters, user-friendliness, adaptability, and simplicity, have resulted in its rapid adoption for addressing various optimization challenges. This review is dedicated to the examination and discussion of the foundational research that forms the basis of the GTO. It delves into the evolution of this algorithm, drawing insights from 112 research studies that highlight its effectiveness. Additionally, it explores proposed enhancements to the GTO’s behavior, with a specific focus on aligning the geometry of the search area with real-world optimization problems. The review also introduces the GTO solver, providing details about its identification and organization, and demonstrates its application in various optimization scenarios. Furthermore, it provides a critical assessment of the convergence behavior while addressing the primary limitation of the GTO. In conclusion, this review summarizes the key findings of the study and suggests potential avenues for future advancements and adaptations related to the GTO.

show abstract

Design of Neuro-Stochastic Bayesian Networks for Nonlinear Chaotic Differential Systems in Financial Mathematics

Syed,

Fang,

Kiani

et al. 2024

Comput Econ

View full text Add to dashboard Cite

Metaheuristic methods to identify parameters and orders of fractional-order chaotic systems

Cited by 6 publications

References 55 publications

Finite-Time Adaptive Event-Triggered Control for Full States Constrained FONSs with Uncertain Parameters and Disturbances

Finite-Time Adaptive Event-Triggered Control for Full States Constrained FONSs with Uncertain Parameters and Disturbances

An in-depth survey of the artificial gorilla troops optimizer: outcomes, variations, and applications

Design of Neuro-Stochastic Bayesian Networks for Nonlinear Chaotic Differential Systems in Financial Mathematics

Contact Info

Product

Resources

About