An adaptive dynamic programming in cooperative target tracking for energy acquisition in wireless sensor networks

Abstract

In order to further study the application of energy acquisition model, based on the relevant theory of adaptive dynamic programming, the wireless sensor is tracked by modifying the energy acquisition model, and the relevant data and parameters are quantitatively analyzed according to the test results. Finally, the parameters of different samples are tracked and identified. The results show that the evaluation analysis curve with four different parameters can be divided into two stages according to the different variation trends: fluctuation stage and stable stage. It indicates that the increase of time can effectively improve the stability corresponding to the convergence of neural network. The trajectory under the three different parameter states shows a general trend of rapid decline at first and then tends to be stable. There is a certain disturbance in the rapid decline of the curve, but when the time is between 1 and 2, it corresponds to the drop of the curve, and the curve gradually flattens after rapid decline. Parameters in the adaptive dynamic programming model are shown as follows: parameter W decreases slowly to the lowest point and then rises slowly with the increase of iteration steps; The proportion of parameter W1 in the model shows a trend of slow increase. Relevant research can provide theoretical basis for the application of energy acquisition model based on adaptive dynamic programming and analysis in other fields.