Output Feedback Adaptive Fuzzy Inverse Optimal Security Control Against Sensor and Actuator Attacks for Nonlinear Cyber-Physical Systems

The optimal control problem of Cyber-Physical Systems (CPSs) under network attacks is of practical significance, but it has yet to be thoroughly studied. This paper focuses on this problem, and proposes an adaptive fuzzy inverse optimal output feedback control strategy for a class of nonlinear CPSs suffering from actuator and sensor attacks. Firstly, a state transformation is implemented to change the attacked system into a new system for which output feedback control becomes feasible. Moreover, the Nussbaum gain function method is adopted to overcome the design difficulties caused by uncertain network attacks and unknown control coefficients. By combining inverse optimal control (IOC) design theory, fuzzy logic systems (FLS) method, and adaptive backstepping technique, a novel adaptive inverse optimal output feedback control scheme is developed to guarantee the security of the closed-loop system, i.e., the semi-global uniform ultimate boundedness (SGUUB) of all signals in the closed-loop system. Meanwhile, the cost function is minimized to meet the control requirement on low power consumption. At last, the effectiveness and practicality of the proposed control method are verified through two simulation examples.