Adaptive tuning of a Kalman filter using the fuzzy integral for an intelligent navigation system

被引:9
|
作者
Rahbari, R [1 ]
Leach, BW [1 ]
Dillon, J [1 ]
de Silva, CW [1 ]
机构
[1] NRC Innovat Ctr, Vancouver, BC, Canada
关键词
fuzzy logic; fuzzy integral; fuzzy measure; expert system; inference methods; multivariable systems; intelligent system; inertial navigation system; Global Positioning System; adaptive Kalman filter; aircraft maneuver;
D O I
10.1109/ISIC.2002.1157771
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This paper describes the development of an intelligent, adaptive tuning system for a Kalman filter to optimally integrate data from an Inertial Navigation System (INS) and a Global Positioning System (GPS). This system is particularly useful for accurate navigation of an aircraft during maneuvering periods. The tuning algorithm is based on fuzzy logic. Specifically, the inference method in the fuzzy rulebase uses the concepts of fuzzy measure and fuzzy integral. This method of inference is particularly useful for multivariable fuzzy systems that are embedded in expert systems. Typical results obtained from the developed approach are presented and discussed in the paper, illustrating satisfactory performance.
引用
收藏
页码:252 / 257
页数:6
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