DISTURBANCE OBSERVER-BASED ADAPTIVE NETWORK EVENT-TRIGGERED BACKSTEPPING SYNCHRONIZATION CONTROL FOR FRACTIONAL ORDER CHAOTIC SYSTEMS

Hui Lv, Wei Xiang () and Jun Zhu
Additional contact information
Hui Lv: State Key Laboratory of Mechanics and Control for Aerospace Structures, Key Laboratory of Mathematical Modelling and High Performance, Computing of Air Vehicles (NUAA), Ministry of Industry and Information Technology (MIIT), Nanjing University of Aeronautics and Astronautics, Nanjing 210016, P. R. China†School of Finance and Mathematics, Huainan Normal University, Huainan 232038, P. R. China
Wei Xiang: ��School of Finance and Mathematics, Huainan Normal University, Huainan 232038, P. R. China
Jun Zhu: State Key Laboratory of Mechanics and Control for Aerospace Structures, Key Laboratory of Mathematical Modelling and High Performance, Computing of Air Vehicles (NUAA), Ministry of Industry and Information Technology (MIIT), Nanjing University of Aeronautics and Astronautics, Nanjing 210016, P. R. China

FRACTALS (fractals), 2025, vol. 33, issue 04, 1-13

Abstract: This paper supplies an event-triggered adaptive synchronization control scheme is proposed for fractional-order chaotic systems with unknown external disturbances. Neural networks are used to approximate unknown nonlinear functions. In order to solve the “complexity explosion†problem caused by the traditional backstepping program, a command filter is designed. A compensation signal is introduced to eliminate the influence of filtering error on the chaotic synchronization performance, and a disturbance observer is proposed to deal with external disturbances. A dynamic event triggering mechanism is established by using the linear relationship between the measurement error and the control input to effectively reduce the computing and communication resources. Based on stability analysis, the proposed event-triggered synchronization control scheme ensures that the synchronization error converges to a small neighborhood close to zero, and all signals in the closed-loop system are bounded without the Zeno phenomenon. Finally, two simulation experiments are conducted to verify the practicality and superiority of the proposed control method.

Keywords: Fractional Order Chaotic System; Neural Network; Synchronization Control; Event-Triggered Mechanism; Disturbance Observer (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.worldscientific.com/doi/abs/10.1142/S0218348X25400754
Access to full text is restricted to subscribers

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:wsi:fracta:v:33:y:2025:i:04:n:s0218348x25400754

Ordering information: This journal article can be ordered from

DOI: 10.1142/S0218348X25400754

Access Statistics for this article

FRACTALS (fractals) is currently edited by Tara Taylor

More articles in FRACTALS (fractals) from World Scientific Publishing Co. Pte. Ltd.
Bibliographic data for series maintained by Tai Tone Lim ().