Abstract

Control systems need to be able to operate under uncertainty and especially under attacks. To address such challenges, this paper formulates the solution of robust control for uncertain systems under time-varying and unknown time-delay attacks in cyber-physical systems (CPSs). A novel control method able to deal with thwart time-delay attacks on closed-loop control systems is proposed. Using a descriptor model and an appropriate Lyapunov functional, sufficient conditions for closed-loop stability are derived based on linear matrix inequalities (LMIs). A design procedure is proposed to obtain an optimal state feedback control gain such that the uncertain system can be resistant under an injection time-delay attack with variable delay. Furthermore, various fault detection frameworks are proposed by following the dynamics of the measured data at the system's input and output using statistical analysis such as correlation analysis and K-L (Kullback-Leibler) divergence criteria to detect attack's existence and to prevent possible instability. Finally, an example is provided to evaluate the proposed design method's effectiveness.

Highlights

  • During the last few years, uncertain systems have been widely encountered because of the environmental changes, systems’ failures, and disturbances [1, 2]

  • Closed-loop security has been guaranteed by calculating the optimal feedback control gain in linear matrix inequalities (LMIs)

  • Numerical results illustrated that the closed-loop uncertain system could remain stable with the proposed robust controller under time-delay attacks

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Summary

Introduction

During the last few years, uncertain systems have been widely encountered because of the environmental changes, systems’ failures, and disturbances [1, 2]. The finite-time H∞ filtering method for networked state-dependent uncertain systems under multiple attacks (DoS, deception, and replay attacks) by considering the event-triggered approach is investigated in [43]. Another control strategy of nonlinear time-delayed CPSs under unspecific deception attacks is developed in [44], in which an adaptive, resilient, dynamic surface control using the neural-network scheme is proposed for deception attacks on both sensor and actuator sides.

Problem statement
Delay-independent stability for an uncertain system with time–delay attack
Fault detection based on maximum correlation
Fault detection based on K-L divergence analysis
Numerical simulations
Conclusions
Full Text
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