Event-Triggered-Based Adaptive Fuzzy Finite-Time Resilient Output Feedback Control for MIMO Stochastic Nonlinear System Subject to Deception Attacks

• Published in: IEEE transactions on fuzzy systems Vol. 32; no. 11; pp. 6534 - 6547
• Main Authors: Zhao, Jipeng, Yang, Guang-Hong
• Format: Journal Article
• Language: English
• Published: IEEE 01.11.2024
• Subjects: Adaptive resilient control; Adaptive systems; Backstepping; Control systems; event-triggered control; fuzzy state observer; multiple inputs and multiple outputs (MIMO) nonlinear stochastic systems; Nonlinear systems; Observers; Output feedback; Stochastic systems; unknown deception attacks
• ISSN: 1063-6706; 1941-0034
• DOI: 10.1109/TFUZZ.2024.3452278

In this article, the event-triggered-based adaptive finite-time resilient control problem is investigated for the uncertain multiple inputs and multiple outputs (MIMO) nonlinear stochastic system with unknown sensor deception attacks. Firstly, based on the compromised output signals and the FLSs, a new fuzzy state observer is constructed to estimate the unmeasured states. Then, the Nussbaum gain technique is utilized to address the issue of unknown control coefficients that arise due to unknown deception attacks. Furthermore, by combining the event-triggered control and backstepping recursive control principle, a novel event-triggered based finite-time resilient fuzzy adaptive output feedback control scheme is developed involving the attacked and estimated state variables. The results of the developed output feedback control show that all the signals of the overall system are semiglobal finite-time stability in probability. Contrary to the current state feedback resilient control results, the designed resilient control scheme not only handles the output feedback control problem, but also eliminates the assumption that the attack weight sign is positive. In addition, the growing assumptions of coexistence unknown nonlinear uncertainties are removed. Ultimately, a simulation example is used to illustrate the feasibility and the rationality of the designed controller.