Multisensor information fusion predictive control algorithm

Using the multisensor information fusion Kalman filter in the linear minimum variance sense, a multisensor information fusion predictive control algorithm is presented. This algorithm applies information fusion Kalman filter weighted by scalars to predictive control and avoids the complex Diophantine equation, so it can obviously reduce the computational burden. Compared to the single sensor case, the performance of the predictive control is improved. A simulation example for the target tracking system with 3-sensor shows its effectiveness and correctness.