H∞ Bipartite Synchronization Composite Antidisturbance Control of Hidden Markov Jump Reaction–Diffusion Neural Networks
Date
Authors
Wang, X
Sun, L
Wang, YL
Lie, T
Supervisor
Item type
Journal Article
Degree name
Journal Title
Journal ISSN
Volume Title
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Abstract
This article investigates the problem of composite H∞ control for cooperation–competition networks with hidden Markov jump parameters reaction–diffusions dynamics. Considering the difficulty of directly obtaining the mode information of systems, a continuous-time hidden Markov jump model is employed to represent the joint jump process. Specifically, the hidden process stands for the dynamics of real systems, which cannot be precisely known but can be observed through a detector. Due to the existence of multiple disturbances, the performance of the aforementioned systems can be deteriorated. To reduce the influence of these disturbances, a composite disturbance observer-based controller is constructed, which combines a disturbance observer with a feedback control mechanism. This design significantly improves the robustness and antidisturbance capability of systems. Then, sufficient criteria are derived to guarantee that the bipartite synchronization error system (BSES) is stochastically stable and meets a desired performance index. Finally, the effectiveness of the proposed control method is verified through the performance analysis.Description
Keywords
4611 Machine Learning, 46 Information and Computing Sciences, 4602 Artificial Intelligence, 4603 Computer Vision and Multimedia Computation, Bipartite synchronization, composite disturbance rejection control (CDRC), cooperation–competition networks, hidden Markov jump model, reaction–diffusion
Source
IEEE Transactions on Cybernetics, ISSN: 2168-2267 (Print); 2168-2275 (Online), Institute of Electrical and Electronics Engineers (IEEE), PP(99), 1-11. doi: 10.1109/TCYB.2025.3647665
Publisher's version
Rights statement
This is the Author's Accepted Manuscript of an article published in IEEE Transactions on Cybernetics. The Version of Record will be available at DOI: 10.1109/TCYB.2025.3647665