On co-design of filter and fault estimator against randomly occurring nonlinearities and randomly occurring deception attacks

Abstract

In this paper, the co-design problem of filter and fault estimator is studied for a class of time-varying non-linear stochastic systems subject to randomly occurring nonlinearities and randomly occurring deception attacks. Two mutually independent random variables obeying the Bernoulli distribution are employed to characterize the phenomena of the randomly occurring nonlinearities and randomly occurring deception attacks, respectively. By using the augmentation approach, the co-design problem of the robust filter and fault estimator is converted into the recursive filter design problem. A new compensation scheme is proposed such that, for both randomly occurring nonlinearities and randomly occurring deception attacks, an upper bound of the filtering error covariance is obtained and such an upper bound is minimized by properly designing the filter gain at each sampling instant. Moreover, the explicit form of the filter gain is given based on the solution to two Riccati-like difference equations. It is shown that the proposed co-design algorithm is of a recursive form that is suitable for online computation. Finally, a simulation example is given to illustrate the usefulness of the developed filtering approach.

Keywords:

• Time-varying systems
• robust filter
• fault estimator
• randomly occurring nonlinearities
• randomly occurring deception attacks

Notes

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work was supported in part by the National Natural Science Foundation of China [grant number 11301118]; the Youth Science Foundation of Heilongjiang Province of China [grant number QC2015085]; the China Postdoctoral Science Foundation [grant number 2014M560376], [grant number 2015T80482]; Jiangsu Planned Projects for Postdoctoral Research Funds [grant number 1402004A]; the Alexander von Humboldt Foundation of Germany.