Adaptive Resilient Control for a Class of Strict-Feedback Nonlinear Systems Under Replay Attacks

This paper focuses on adaptive tracking control for a class of strict-feedback nonlinear systems suffering from the replay attack in the sensor-controller channel. To address the challenges posed by repeating information and complex nonlinearity in nonlinear systems, an adaptive resilient controller based on the multidimensional Taylor network is designed. This controller guarantees that the tracking error converges to zero exponentially in the absence of replay attacks, and it achieves bounded tracking in the presence of replay attacks. Finally, the effectiveness of the proposed control strategy is verified using a chemical reactor with circulating flow simulation. Copyright (c) 2024 The Authors.