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在卫星星上系统设计与研制的许多领域中应用软计算技术将获益匪浅。本文介绍星上GPS姿态确定应用的各种模糊逻辑和类属算法的部分研究成果。上述算法在卡尔曼滤波器动态自适应方案中的应用结果表明,它们非常有效。特别是,姿态确定系统的核心部件是一台滤波器,该滤波器可根据GPS差分相位测量值计算出卫星姿态状态的估计值。接收机测量值由于受到各种误差源的影响,通常随时间而变化。模糊规则除了可以辅助滤波器减小各种误差影响外,还可补偿由于姿态滤波器传播模型过于简化而降低的精度。模糊规则集合以及模糊隶属函数通常是依据专家系统知识设计的。在许多情况下,往往难以精确描述隶属函数,因此行之有效的办法就是想出一种能自动地修正这些函数的方法。类属算法便应运而生,它能根据给定的性能指标自修正与模糊隶属函数形式有关的基本参数。本文发表了姿态确定系统的软件仿真结果,目的是将从滤波器获得的结果与系统辅以模糊规则和自修正技术后所获得的结果作一个比较。
The benefits of using soft computing technology in many areas of system design and development on the satellite arena. This article describes some of the research results of various fuzzy logic and generic algorithms applied to the on-board GPS attitude determination. The application of the above algorithm to the Kalman filter dynamic adaptive scheme shows that they are very effective. In particular, the core component of the attitude determination system is a filter that computes an estimate of the attitude of the satellite based on GPS differential phase measurements. Receiver measurements, which are subject to various sources of error, usually change over time. In addition to assisting the filter to reduce various error effects, the fuzzy rule can also compensate for the reduced accuracy due to the simplification of the attitude filter propagation model. Fuzzy rule sets and fuzzy membership functions are usually designed based on expert system knowledge. In many cases, it is often difficult to describe membership functions accurately, so an effective solution is to come up with a way to automatically correct these functions. The generic algorithm came into being, which can self-modify the basic parameters related to the form of fuzzy membership function according to the given performance index. This paper presents the software simulation results of the attitude determination system. The purpose of this paper is to compare the results obtained from the filters with those obtained after the system is supplemented by fuzzy rules and self-correction techniques.