State Estimation of Stochastic Impulsive System Via Stochastic Adaptive Impulsive Observer

This paper develops stochastic adaptive impulsive observer SAIO for state estimation of stochastic impulsive systems. Proposed observer is applicable to linear and a class of nonlinear stochastic impulsive systems. In addition to stochastic noises, the observer considers effect of parametric uncertainty and estimates unknown parameters by suitable adaptation laws. Interestingly, for certain impulsive systems, SAIO gives continuous state estimations from a discrete sequence of system output measurements. New theorems related to stochastic impulsive systems' boundedness are also developed and utilized to prove the boundedness of SAIO state estimation errors. Presented simulation results illustrate the effectiveness of the observer.

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