Safety-Critical Control for Nonlinear Affine Systems with Robustness and Attack Recovery
Primary Investigator:
Inseok Hwang
Sungsoo Kim, Minhyun Cho, Sounghwan Hwang
Abstract
We propose a safety-critical controller design for nonlinear affine systems under actuator cyberattacks and model uncertainties. To achieve this, our approach addresses two primary challenges: First, we propose a robust controller that employs a sliding mode-based control barrier function (SM-CBF) to adeptly manage model uncertainties. Second, we devise a CBF-based attack detection mechanism to promptly alert the presence of cyberattacks within the actuator channel. The natural drawback of a conventional CBF-based controller is that its performance (safety guarantees) significantly depends on the model uncertainties. The inclusion of these uncertainties may lead to safety breaches/violations. To overcome this technical challenge, our proposed controller with SM-CBF approach enables us to effectively enforce the safety conditions of the system even in the presence of model uncertainties. Furthermore, we propose a novel CBF-based attack detector such that it can determine whether the system trajectory moves toward the outside of the safety set by cyberattacks. Through the synthesis of the designed robust controller and attack detector, our proposed safety-critical controller can greatly enhance system safety while concurrently achieving control performance. Finally, an illustrative example of the stabilization of quadrotor unmanned aerial vehicles (UAVs) is provided to demonstrate the effectiveness of the proposed methodology.