Dynamics, Control, and Applications of Nonlinear Systems

A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "E2: Control Theory and Mechanics".

Deadline for manuscript submissions: 31 July 2026 | Viewed by 443

Special Issue Editor


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Guest Editor
School of Mathematics and Statistics, Qilu University of Technology (Shandong Academy of Sciences), Jinan 250353, China
Interests: chaos control; chaos synchronization; switched systems; nonlinear systems
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Special Issue Information

Dear Colleagues,

The control problem of nonlinear systems with applications is general in the actual process, and they have attracted many scholars’ attention owing to the wide applications in various fields, such as physics, mathematics, finance, and engineering. Therefore, the analysis and synthesis of control problems play important roles in many practical systems.

The aim of this Special Issue is to bring together the latest/innovative knowledge and analysis and synthesis of the control problem of nonlinear systems. All the submissions are expected to have original ideas and novel approaches. We invite authors to contribute original research articles related to all aspects of this Special Issue.

Potential topics include, but are not limited to, the following:

  • Chaos control, chaos synchronization;
  • Stability and stabilization of nonlinear systems;
  • Control problems of switched systems;
  • Stochastic control;
  • Stochastic differential equation;
  • Insurance risk analysis and control strategy.

Prof. Dr. Rongwei Guo
Guest Editor

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Keywords

  • stability analysis
  • nonlinear systems
  • stochastic control
  • insurance risk analysis and control strategy
  • chaos control, chaos synchronization

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Published Papers (1 paper)

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16 pages, 855 KB  
Article
RBF Neural Network Fusion Disturbance Estimation for Robust Synchronization of Chaotic Systems
by Yuanyuan Mao
Mathematics 2026, 14(6), 1054; https://doi.org/10.3390/math14061054 - 20 Mar 2026
Viewed by 226
Abstract
This paper addresses the problem of complete synchronization of chaotic systems subject to external disturbances and parameter uncertainties, proposing a robust control strategy based on radial basis function (RBF) neural network fusion with a disturbance estimator (DE)-based control method. Firstly, a dynamic feedback [...] Read more.
This paper addresses the problem of complete synchronization of chaotic systems subject to external disturbances and parameter uncertainties, proposing a robust control strategy based on radial basis function (RBF) neural network fusion with a disturbance estimator (DE)-based control method. Firstly, a dynamic feedback controller is designed to stabilize the nominal error system. Subsequently, a set of appropriate filters are constructed, and based on these filters, a disturbance estimator that can asymptotically track external disturbances is developed, thereby realizing asymptotic cancelation of external disturbance effects on the synchronization process. Then, an RBF-based compensator is designed to approximate the unmodeled uncertainties of the system with high precision, effectively suppressing the adverse impacts of uncertainties. By integrating the aforementioned dynamic feedback controller, disturbance estimator, and RBF-based compensator, robust complete synchronization between the master and slave chaotic systems is successfully achieved. Finally, a numerical simulation example is presented to validate the feasibility and effectiveness of the proposed control scheme. Full article
(This article belongs to the Special Issue Dynamics, Control, and Applications of Nonlinear Systems)
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