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Multisensor Information Fusion Predictive Control

Using the Kalman filtering method, based on linear minimum variance optimal information fusion criterion, the multisensor information fusion predictive control algorithm is presented for the multisensor system with correlated noises statistic. This algorithm applies information fusion Kalman filter weighted by diagonal matrices to predictive control. It avoids the complex Diophantine equation and can obviously reduce the computational burden. Compared to the single sensor case, the performance of the predictive control is improved. A simulation example with 3-sensor shows its effectiveness and correctness.