Global Event‐Triggered Adaptive Control of Nonstrict‐Feedback Non‐Linear Systems With Unknown Functions and Time‐Varying Delay Using Neural Networks
ABSTRACT This article aims to achieve global adaptive control of nonstrict‐feedback non‐linear systems with unknown functions and time‐varying delay. Unlike traditional methods, this approach introduces switching functions at each step of the backstepping design, in addition to utilizing neural networks (NNs) to approximate the unknown functions, resulting in globally bounded outcomes. By employing appropriate Lyapunov‐Krasovskii (L‐K) functionals, the negative effects of time‐varying delays are effectively compensated. The proposed control scheme integrates the design of both the controller and the event‐triggering mechanism (ETM), effectively removing the need for input‐to‐state stability assumptions while reducing measurement errors. Furthermore, the ETM, based on an adaptive threshold strategy, not only ensures superior system performance but also optimizes network resource utilization. Finally, two simulation examples are provided to demonstrate the validity of the proposed control approach.
Authors
- Hongtao Sun (ORCID: https://orcid.org/0000-0002-8454-806X)
- Xinrui Ma
- Cheng Tan (ORCID: https://orcid.org/0000-0003-2343-9166)
- Ziran Chen (ORCID: https://orcid.org/0000-0002-4105-7578)
Institutions
- Qufu Normal University (CN)
Publication Details
- Journal
- International Journal of Robust and Nonlinear Control
- Published
- 2025-02-26
- DOI
- https://doi.org/10.1002/rnc.7877
- Primary Topic
- Adaptive Control of Nonlinear Systems
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China
- China Postdoctoral Science Foundation
- Taishan Scholar Project of Shandong Province
- Science and Technology Support Plan for Youth Innovation of Colleges and Universities of Shandong Province of China