Fuzzy Adaptive Extended Kalman Filter

نویسندگان

  • Vasko Sazdovski
  • Tatjana Kolemishevska-Gugulovska
  • Mile Stankovski
چکیده

Kalman filtering is a method for estimating state variables of a dynamic systems recursively from noise-contaminated measurements. For systems with nonlinear dynamics, a natural extension of the Linear Kalman Filter (LKF), called Extended Kalman filter (EKF) is used. The Kalman filter represents one of the most popular estimation techniques for integrating signals from navigation systems, like Inertial Navigation System (INS) and Global Positioning System (GPS). However, a significant difficulty in designing a Kalman Filter (refers to both LKF and EKF) can often be traced to incomplete a priori information about R and Q matrices. It has been shown that incorrect a priori information can lead to practical divergence of the filter. The use of fuzzy-rule based adaptation scheme to cope with divergence problem is explored. The Fuzzy Logic Adaptive Controller (FLAC) was implemented in Integrated INS/GPS Navigation Systems to detect the uncertainties, adapt the Kalman Filter on-line and prevent divergence.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

A New Adaptive Extended Kalman Filter for a Class of Nonlinear Systems

This paper proposes a new adaptive extended Kalman filter (AEKF) for a class of nonlinear systems perturbed by noise which is not necessarily additive. The proposed filter is adaptive against the uncertainty in the process and measurement noise covariances. This is accomplished by deriving two recursive updating rules for the noise covariances, these rules are easy to implement and reduce the n...

متن کامل

Doppler and bearing tracking using fuzzy adaptive unscented Kalman filter

The topic of Doppler and Bearing Tracking (DBT) problem is to achieve a target trajectory using the Doppler and Bearing measurements. The difficulty of DBT problem comes from the nonlinearity terms exposed in the measurement equations. Several techniques were studied to deal with this topic, such as the unscented Kalman filter. Nevertheless, the performance of the filter depends directly on the...

متن کامل

Tuning of Extended Kalman Filter using Self-adaptive Differential Evolution Algorithm for Sensorless Permanent Magnet Synchronous Motor Drive

In this paper, a novel method based on a combination of Extended Kalman Filter (EKF) with Self-adaptive Differential Evolution (SaDE) algorithm to estimate rotor position, speed and machine states for a Permanent Magnet Synchronous Motor (PMSM) is proposed. In the proposed method, as a first step SaDE algorithm is used to tune the noise covariance matrices of state noise and measurement noise i...

متن کامل

Performance Analysis and Comparison of Adaptive Filters for Wireless Channel Equalization

In this paper we have applied radial basis function neural networks for equalization of wireless channel in the presence of additive noise. We have been tested the adaptive filter algorithms of simple Kalman filter, extended Kalman filter, rbfn Kalman filter, rbfn extended Kalman filter, fuzzy Kalman filter and fuzzy extended Kalman filter which might be considered applicable for wireless chann...

متن کامل

Fuzzy Logic Applications in Filtering and Fusion for Target Tracking

A fuzzy Kalman filter algorithm is developed for target tracking applications and its performance evaluated using several numerical examples. The approach is relatively novel. A comparison with Kalman filter and an adaptive tuning algorithm is carried out. The applicability and usefulness of fuzzy logic in data fusion is also demonstrated. The performance of both the extended Kalman filter and ...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2005