期刊
NEURAL COMPUTING & APPLICATIONS
卷 27, 期 6, 页码 1543-1551出版社
SPRINGER LONDON LTD
DOI: 10.1007/s00521-015-1954-4
关键词
Adaptive critic designs; Adaptive dynamic programming; Approximate dynamic programming; Neuro-dynamic programming; Neural networks; Wireless sensor networks; Scheduling
资金
- National Natural Science Foundation of China [61304079, 61374105]
- Beijing Natural Science Foundation [4132078, 4143065]
- China Postdoctoral Science Foundation [2013M530527]
- Fundamental Research Funds for the Central Universities [FRF-TP-14-119A2]
- SKLMCCS [20150104, 20120106]
This paper proposes a novel sensor scheduling scheme based on adaptive dynamic programming, which makes the sensor energy consumption and tracking error optimal over the system operational horizon for wireless sensor networks with solar energy harvesting. Neural network is used to model the solar energy harvesting. Kalman filter estimation technology is employed to predict the target location. A performance index function is established based on the energy consumption and tracking error. Critic network is developed to approximate the performance index function. The presented method is proven to be convergent. Numerical example shows the effectiveness of the proposed approach.
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