计算机应用 ›› 2016, Vol. 36 ›› Issue (3): 616-619.DOI: 10.11772/j.issn.1001-9081.2016.03.616

• 网络与通信 • 上一篇    下一篇

基于遗传算法的无线传感器/执行器网络故障检测滤波器设计

刘勇1, 沈轩帆2, 廖勇2, 赵明2   

  1. 1. 人工智能四川省重点实验室(四川理工学院), 四川 自贡 643000;
    2. 飞行器测控与通信教育部重点实验室(重庆大学), 重庆 400044
  • 收稿日期:2015-08-04 修回日期:2015-10-19 出版日期:2016-03-10 发布日期:2016-03-17
  • 通讯作者: 廖勇
  • 作者简介:刘勇(1981-),男,四川富顺人,讲师,硕士,主要研究方向:无线网络控制;沈轩帆(1994-),男,云南昆明人,主要研究方向:通信工程;廖勇(1982-),男,四川自贡人,副研究员,博士,主要研究方向:宽带无线通信、无线网络控制;赵明(1994-),女,陕西西安人,主要研究方向:通信工程。
  • 基金资助:
    人工智能四川省重点实验室开放基金资助项目(2015RZJ03)。

Fault detection filter design based on genetic algorithm in wireless sensor and actuator network

LIU Yong1, SHEN Xuanfan2, LIAO Yong2, ZHAO Ming2   

  1. 1. Key Laboratory of Artificial Intelligence of Sichuan Province (Sichuan University of Science and Engineering), Zigong Sichuan 643000, China;
    2. Key Laboratory of Aerocraft Tracking Telemetering & Command and Communication, Ministry of Education (Chongqing University), Chongqing 400044, China
  • Received:2015-08-04 Revised:2015-10-19 Online:2016-03-10 Published:2016-03-17
  • Supported by:
    This work is partially supported by the Open Fund of Key Laboratory of Artificial Intelligence of Sichuan Province (2015RZJ03).

摘要: 为提高无线传感器/执行器网络(WSAN)的可靠性,提出一种基于遗传算法(GA)的WSAN故障检测滤波器的优化设计方法。在系统建模时将无线网络传输延迟对网络控制系统的影响建模为一种系统扰动噪声,将由敏感度和鲁棒性构成的复合优化指标作为故障检测滤波器的优化目标函数,即适应度函数。同时根据优化目标在自动控制系统中的数值特性,选择与之相适应的实数编码、均匀变异和算术交叉等处理方法,以期在加快收敛速度的同时也兼顾计算结果的精确度。所提的优化滤波器设计,不仅能抑制滤波器信号中的噪声分量,而且能放大故障信号。最后,通过Matlab/OMNET++的仿真平台验证了这一设计的有效性。

关键词: 遗传算法, 无线传感器/执行器网络, 故障检测, 滤波器, 鲁棒性, 灵敏度

Abstract: To improve the reliability of the Wireless Sensor and Actuator Network (WSAN), an optimal design method based on Genetic Algorithm (GA) for WSAN fault detection filter was proposed. In system modeling, the influence of the wireless network transmission delay on network control system was modeled as an external noise, the composite optimization index which is composed of sensitivity and robustness was made as the design goal of fault detection filter, and the optimization objective was made as the core of GA—the fitness function. At the same time, according to the numerical characteristics of optimization objective in WSAN, the corresponding real coding, uniform mutation, arithmetic crossover and other processing methods were selected to speed up the convergence rate, meanwhile taking the accuracy of the calculation results into account. The optimized filter design mentioned herein, not only restrains the noise signal, but also amplifies the fault signal. Finally, the effectiveness of the proposed design is demonstrated by the results of Matlab/OMNET++ hybrid simulations.

Key words: Genetic Algorithm (GA), Wireless Sensor and Actuator Network (WSAN), fault detection, filter, robustness, sensitivity

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