微电网通信无线传感器网络链路质量预测与控制研究

发布时间：2018-04-08 07:33

本文选题：微电网　切入点：无线传感器网络　出处：《合肥工业大学》2017年硕士论文

【摘要】：链路质量是微电网通信无线传感器网络领域的研究热点之一。无线链路质量所具有的非线性以及非平稳随机特性是难以对其可靠性实现精确预测与控制的难点。针对这一问题,本文提出一种基于小波神经网络的无线通信链路可靠性置信区间预测算法和基于模糊控制理论的链路可靠性控制算法。通过对无线通信链路质量的解耦预处理,将链路质量的非线性部分和非平稳随机性部分分离后,构建小波神经网络预测模型,并根据预测结果,采用模糊控制模型和方法,对节点发射功率进行控制,以提高链路质量的稳定性和可靠性。本文主要工作如下:1、以微电网对通信网络的可靠性需求为控制目标,分析了微电网中无线传感器网络通信服务质量的特点,无线通信链路可靠性的影响因素,以及无线通信链路的数学模型。2、结合无线通信链路数学模型,分析了链路质量指标和无线通信链路质量中所具有的耦合成分,提出了无线通信链路可靠性置信区间预测算法结构,并分别研究了该算法结构中由信噪比表征的链路质量近似解耦算法和基于小波神经网络的链路质量置信区间预测算法。在微电网环境中对提出的无线通信链路可靠性置信区间预测算法进行仿真测试,并与卡尔曼预测、BP神经网络以及ARIMA预测算法进行对比,验证了本文所提算法的可行性与优越性。3、根据无线通信链路可靠性置信区间预测结果,提出了一种无线传感器网络节点功率控制系统结构,研究了基于模糊控制的微电网无线传感器网络通信链路质量可靠性优化控制算法。并通过微电网环境中的测试,验证了提出的优化控制结果的稳定性和可靠性。4、在太阳能发电微电网系统的无线传感器网络通信系统中,测试了本文提出的无线传感器网络链路质量预测算法以及功率模糊控制算法。结果表明,本文提出的无线通信链路可靠性置信区间预测算法和基于模糊控制的无线传感器网络节点功率控制算法可以实时准确地预测下一时刻链路质量的置信区间界限,并通过调节节点发射功率实现链路质量可靠性的平稳控制。
[Abstract]:Link quality is one of the hotspots in wireless sensor networks for microgrid communication.The nonlinear and non-stationary random characteristics of wireless link quality are difficult to accurately predict and control its reliability.To solve this problem, this paper presents a prediction algorithm for reliability confidence interval of wireless communication link based on wavelet neural network and a link reliability control algorithm based on fuzzy control theory.By decoupling the link quality, the nonlinear part of the link quality is separated from the non-stationary part of the link quality, and the prediction model of wavelet neural network is constructed. According to the prediction results, the fuzzy control model and method are adopted.The transmission power is controlled to improve the stability and reliability of the link quality.The main work of this paper is as follows: 1. Aiming at the requirement of communication network reliability in microgrid, this paper analyzes the characteristics of wireless sensor network communication quality of service and the influencing factors of wireless communication link reliability.And the mathematical model of wireless communication link. 2. Combining with the mathematical model of wireless communication link, the link quality index and the coupling component of wireless communication link quality are analyzed.In this paper, the structure of link reliability confidence interval prediction algorithm for wireless communication is proposed, and the link quality approximate decoupling algorithm and the link quality confidence interval prediction algorithm based on wavelet neural network are studied respectively.In the microgrid environment, the proposed confidence interval prediction algorithm for wireless communication link reliability is simulated and tested, and compared with Kalman prediction BP neural network and ARIMA prediction algorithm.The feasibility and superiority of the proposed algorithm are verified. According to the prediction results of reliability confidence interval of wireless communication link, a structure of node power control system for wireless sensor network is proposed.An optimal quality control algorithm for wireless sensor network communication link based on fuzzy control is studied.The stability and reliability of the proposed optimal control results are verified by testing in the microgrid environment, which is used in the wireless sensor network communication system of the solar power microgrid system.The proposed link quality prediction algorithm and power fuzzy control algorithm are tested.The results show that the proposed confidence interval prediction algorithm for wireless link reliability and the node power control algorithm for wireless sensor networks based on fuzzy control can predict the confidence interval limits of link quality at the next moment in real time and accurately.The steady control of link quality reliability is realized by adjusting the transmit power of the node.
【学位授予单位】：合肥工业大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TM727;TN929.5;TP212.9

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