Secure tracking control against sensor and actuator attacks: A robust model-reference adaptive control method

Abstract

This paper is concerned with secure tracking control problems for cyber-physical systems subjected to a class of sensor and actuator attacks via the model-reference control techniques. The considered attack signals are the unknown bounded signals generated from any linear or nonlinear finite-L2-gain exogenous dynamical system. The auxiliary outputs produced from a high-gain approximate differentiator are first used in co-design for the inputs of the systems and introduced filter, so that the matching condition on the system input and output matrices in the existing results is relaxed. Furthermore, with the aid of the auxiliary outputs, attack’s property and small-gain control methods, a novel model-reference controller with a robust adaptive attack compensator is proposed, such that (a) the tracking error converges to a small set around zero where the set bound can be adjusted by the design parameters, and (b) the desired disturbance attenuation performance is obtained. Different from the existing results, the developed one not only compensates the effect of the attacks automatically by online adjusting the adaptive parameter, but also improves the robustness against the attacks efficiently. Finally, the developed method is validated by a simulation example.