This paper explores a novel model to describe a linear dynamic system with random delays. Compared with existing studies, the probabilities of random delays in the novel model are calculated by conditional probabilities. Therefore, the process and measurement noises in the new model for random delay problems are infinitely correlated. By treating the model as a random parameter matrix Kalman filter and a random parameter matrix Kalman filter with one-step correlated noises approximately, the new state estimators are presented. The numerical examples show that these new estimators work better than the existing algorithm in many cases.
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