Robust Kalman Filtering for Discrete-Time Systems with Multiple Time-Delayed Measurements

摘要

This paper addresses the robust Kalman filtering problem for linear time-delayed systems with multiple delays. The norm-bounded parameter uncertainties enter into the system matrix of the state-space model. The calculation of the robust filters for the discrete-time case involves 2(l + 1) Riccati difference equations which have the same dimension as the original system. It is shown that the proposed approach is much more computationally attractive than the traditional augmentation approach. The result has extended the single-delay case, which is simpler in structure and computation. A comparison between the two cases is also given. The proposed approach has been extended to solving the robust Kalman filtering problem for continuous-time systems. A numerical example is also given to show the efficiency of the proposed approach.