Adaptive Observer-Based Sliding Mode Secure Control for Nonlinear Descriptor Systems Against Deception Attacks
Guardado en:
| Publicado en: | International Journal of Advanced Computer Science and Applications vol. 16, no. 5 (2025) |
|---|---|
| Autor principal: | |
| Publicado: |
Science and Information (SAI) Organization Limited
|
| Materias: | |
| Acceso en línea: | Citation/Abstract Full Text - PDF |
| Etiquetas: |
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
MARC
| LEADER | 00000nab a2200000uu 4500 | ||
|---|---|---|---|
| 001 | 3222641087 | ||
| 003 | UK-CbPIL | ||
| 022 | |a 2158-107X | ||
| 022 | |a 2156-5570 | ||
| 024 | 7 | |a 10.14569/IJACSA.2025.0160583 |2 doi | |
| 035 | |a 3222641087 | ||
| 045 | 2 | |b d20250101 |b d20251231 | |
| 100 | 1 | |a PDF | |
| 245 | 1 | |a Adaptive Observer-Based Sliding Mode Secure Control for Nonlinear Descriptor Systems Against Deception Attacks | |
| 260 | |b Science and Information (SAI) Organization Limited |c 2025 | ||
| 513 | |a Journal Article | ||
| 520 | 3 | |a This paper delves into an advanced control scheme that combines the sliding mode control (SMC) strategy with a meta-heuristic method to examine the issue of security control for non-linear systems that are vulnerable to deception attacks on their sensors and actuators. The proposed approach focuses on the development of a secure SMC law for nonlinear descriptor systems described by TS fuzzy models. A fuzzy observer is designed to accurately estimate the states that may affected by unpredictable sensor attacks, and an adaptive SMC controller is synthesized based on the estimated information to drive the observer’s state trajectories towards the sliding surface and then maintaining the sliding motion thereafter. Afterward, sufficient conditions are established to ensure the admissibility of the closed-loop system. Then, the secretary bird optimization algorithm (SBOA), is explored for tackling an optimization problem with non-convex and nonlinear constraints as is defined to enhance the system’s performance under threats. Ultimately, a simulation study through a practical example is performed to showcase the effectiveness of the proposed control scheme in maintaining system performance, even in the presence of attacks. | |
| 653 | |a Sliding mode control | ||
| 653 | |a Control systems | ||
| 653 | |a Nonlinear systems | ||
| 653 | |a Nonlinear control | ||
| 653 | |a Feedback control | ||
| 653 | |a Actuators | ||
| 653 | |a Heuristic methods | ||
| 653 | |a Optimization | ||
| 653 | |a Closed loops | ||
| 653 | |a Fuzzy sets | ||
| 653 | |a Computer science | ||
| 653 | |a Genetic algorithms | ||
| 653 | |a Sensors | ||
| 653 | |a Process controls | ||
| 653 | |a Controllers | ||
| 653 | |a Computer engineering | ||
| 653 | |a Deception | ||
| 773 | 0 | |t International Journal of Advanced Computer Science and Applications |g vol. 16, no. 5 (2025) | |
| 786 | 0 | |d ProQuest |t Advanced Technologies & Aerospace Database | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/3222641087/abstract/embedded/75I98GEZK8WCJMPQ?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/3222641087/fulltextPDF/embedded/75I98GEZK8WCJMPQ?source=fedsrch |