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This study presents the design of an adaptive Kalman filter for networked systems involving random `sensor delays, missing measurements and packet dropouts`. Two different adaptive filters are considered to estimate unknown parameter vector associated with the system matrices and subsequently the estimation of state and parameters of the system based on the minimisation of square of the output prediction error is adopted in bootstrap manner. An estimator-based robust controller design has been proposed for asymptotic stability of the system whose parameters can vary within a known bound. The effectiveness of the designed algorithms is tested through a numerical example under different cases.