Fuzzy Enhancement of GPS - INS Synergy

摘要

The paper presents a new approach of enhancement of GPS - ENS synergy by the use of a fuzzy system. A new membership function, which allows a better management of its shape, is used in Mamdani-type fuzzy inference systems. There are two main parameters in fuzzy control systems that influence the performances of a system. The first parameter is the overlapping of membership functions and the second is the output value after defuzzification. Both of them are related to the shape of membership functions. This is modified either by the change of classical membership functions or by the use of concentrator and dilator operators. We introduce a novel membership function which has an elliptical shape. This elliptical membership function provides for the same operation effects, but with much more accuracy. Essentially, the new membership function uses one parameter, the curvature, to obtain a flexible and useful set of functions. Furthermore, the curvature parameter is intuitively appealing. The theoretical fundamentals of the function are presented and the practical accuracy aspects are evaluated. A feed forward system using two Mamdani-type fuzzy inference subsystems is built, and then trained by the modification of the shapes of membership functions.