access icon free Stochastic stability of extended filtering for non-linear systems with measurement packet losses

This study is concerned with stochastic stability of a new extended filtering for non-linear systems subject to measurement packet losses. The measurements sensored are transmitted to the estimator through a packet-dropping network. By introducing a time-stamped packet arrival indicator sequence, the measurement loss process is modelled as an independent, identically distributed (i.i.d.) and therefore a Bernoulli process. The boundedness of estimation error covariance matrices is proved by showing the existence of a critical threshold for measurement packet arrival probability. It is also shown that, under appropriate assumptions, the estimation error remains bounded as long as the noise covariance matrices and the initial estimation error can be ensured small enough. Finally, simulation results validating the effectiveness of this proposed filtering framework are also presented.

Inspec keywords: filtering theory; networked control systems; stochastic systems; nonlinear systems; stability

Other keywords: estimation error covariance matrices; noise covariance matrices; boundedness; nonlinear systems; Bernoulli process; time stamped packet arrival indicator sequence; filtering framework; stochastic stability; packet dropping network; measurement packet arrival probability; measurement packet losses; extended filtering

Subjects: Stability in control theory; Nonlinear control systems; Signal processing theory; Time-varying control systems

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