Algorithm of Multi Sensor Data Fusion Based on BP Neural Network and Multi-scale Model Predictive Control

Multi sensor data fusion is the data from multiple sensors and information from the relevant database are combined, which obtained judgment and description that can not achieve the goal, more accurate and complete by any single sensor. BP neural network is a kind of artificial neural network based on error back-propagation algorithm. It adopts adding hidden layer, to estimate the error directly leading layer of output layer by the error output. The paper presents Algorithm of multi sensor data fusion based on BP neural network and multi-scale model predictive control. The multi-scale model predictive control can not only obtain the previous information, and increase the flexibility in modeling and optimal phase.