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A Genetic-Based Fuzzy Clustering Algorithm for Fault Diagnosis in Satellite Attitude Determination System

机译:卫星姿态确定系统中基于遗传的模糊聚类故障诊断算法

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The paper presents a genetic-based fuzzy clustering algorithm for fault diagnosis in satellite attitude determination system (ADS). The traditional fuzzy c-means(FCM) algorithm is local search techniques that search for the optimum by using a hill-climbing techniques. Thus, it often fail in the search for global optimum. Genetic algorithm is a stochastic global optimization algorithm, their combination can prevent FCM being trapped in a local optimum and sensitive to the initializations. Simulation results show that the proposed approach have much higher probabilities of finding global optimal solutions than traditional FCM algorithm, and provide accurate clustering for fault mode
机译:提出了一种基于遗传的模糊聚类算法,用于卫星姿态确定系统(ADS)的故障诊断。传统的模糊c均值(FCM)算法是通过使用爬山技术来搜索最优值的局部搜索技术。因此,它在寻找全局最优时常常失败。遗传算法是一种随机全局优化算法,它们的组合可以防止FCM陷入局部最优状态并对初始化敏感。仿真结果表明,与传统的FCM算法相比,该方法具有更高的寻找全局最优解的概率,并且可以为故障模式提供准确的聚类。

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