scholarly journals Nonlinear Observer for Vehicle Velocity with Friction and Road Bank Angle Adaptation - Validation and Comparison with an Extended Kalman Filter

2007 ◽  
Author(s):  
Lars Imsland ◽  
Håvard Fjær Grip ◽  
Tor A. Johansen ◽  
Thor I. Fossen ◽  
Jens C. Kalkkuhl ◽  
...  
Keyword(s):  
Kalman Filter ◽  
Extended Kalman Filter ◽  
Nonlinear Observer ◽  
Bank Angle ◽  
Vehicle Velocity

Dynamic Sliding Mode Control of Air-to-Fuel Ratio in Internal Combustion Engines Using the Hybrid Extended Kalman Filter

2012 ◽  
Vol 433-440 ◽  
pp. 2092-2098 ◽  
Author(s):  
Majid Zohari ◽  
Mohamadreza Ahmadi ◽  
Hamed Mojallali
Keyword(s):  
Kalman Filter ◽  
Sliding Mode Control ◽  
Extended Kalman Filter ◽  
Sliding Mode ◽  
Nonlinear Observer ◽  
Superior Performance ◽  
Fuel Ratio ◽  
Mode Control ◽  
Dynamic Sliding Mode Control ◽  
Dynamic Sliding Mode

The large modeling uncertainties and the nonlinearities associated with air manifold and fuel injection in spark ignition (SI) engines has given rise to difficulties in the task of designing an adequate controller for air-to-fuel ratio (AFR) control. Although sliding mode control approaches has been suggested, the inescapable time-delay between control action and measurement update results in chattering. This paper proposes the implementation of a nonlinear observer based control scheme incorporating the hybrid extended Kalman filter (HEKF) and the dynamic sliding mode control (DSMC). The results established upon the proposed methodology are given which demonstrate superior performance in terms of reducing the chattering magnitude.

H∞-Property of the Continuous-Time Extended Kalman Filter

2016 ◽  
Author(s):  
Jennifer L. Bonniwell ◽  
Susan C. Schneider ◽  
Edwin E. Yaz
Keyword(s):  
Kalman Filter ◽  
Extended Kalman Filter ◽  
Continuous Time ◽  
Estimation Error ◽  
Finite Energy ◽  
Minimum Variance ◽  
Nonlinear Observer ◽  
Minimum Variance Estimator ◽  
Error Energy ◽  
Special Case

This work elucidates another theoretical property of the ubiquitous extended Kalman filter by analyzing the energy gain of the continuous-time extended Kalman filter used as a nonlinear observer in the presence of finite-energy disturbances. The analysis provides a bound on the ratio of estimation error energy to disturbance energy, which shows that the extended Kalman filter inherently has the H∞-property along with being the locally optimal minimum variance estimator. A special case of this result is also shown to be the H2-property of the extended Kalman filter.

NONLINEAR OBSERVER VIA EXTENDED KALMAN FILTER ALGORITHM FOR EULER ANGLES ESTIMATION WITHOUT ATTITUDE SENSOR MEASUREMENTS

2015 ◽  
Vol 77 (28) ◽  
Author(s):  
Nor Hazadura Hamzah ◽  
Sazali Yaacob ◽  
Hariharan Muthusamy ◽  
Norhizam Hamzah ◽  
Teoh Vil Cherd ◽  
...  
Keyword(s):  
Kalman Filter ◽  
Extended Kalman Filter ◽  
Moment Equation ◽  
Nonlinear Observer ◽  
Euler Angles ◽  
Satellite Attitude ◽  
Observer Model ◽  
Kalman Filter Algorithm ◽  
Sensor Measurement ◽  
Attitude Sensor

This paper designs and investigates an observer system via Extended Kalman Filter algorithm to estimate the satellite’s Euler angles attitude during the absence of the attitude sensor measurement. This work contributes as a backup or an alternative system during unavailable attitude sensor measurement due to malfunction sensor or for cost reduction by reducing the number of sensors. In this work, the observer model for satellite attitude is presented in their non-simplified nonlinear form by combining the Euler’s Moment Equation and kinematics Euler angles parameter. The performance of the designed observer via Extended Kalman Filter algorithm is analyzed and verified using real flight data of Malaysian satellite.

scholarly journals Globally stable velocity estimation using normalized velocity measurement

2019 ◽  
Vol 39 (1) ◽  
pp. 143-157
Author(s):  
Elias Bjørne ◽  
Edmund F Brekke ◽  
Torleiv H Bryne ◽  
Jeff Delaune ◽  
Tor Arne Johansen
Keyword(s):  
Kalman Filter ◽  
Extended Kalman Filter ◽  
Inertial Measurement Unit ◽  
Velocity Estimation ◽  
Nonlinear Observer ◽  
Measurement Unit ◽  
Velocity Measurements ◽  
Nonlinear Methods ◽  
Inertial Measurement ◽  
Globally Stable

The problem of estimating velocity from a monocular camera and calibrated inertial measurement unit (IMU) measurements is revisited. For the presented setup, it is assumed that normalized velocity measurements are available from the camera. By applying results from nonlinear observer theory, we present velocity estimators with proven global stability under defined conditions, and without the need to observe features from several camera frames. Several nonlinear methods are compared with each other, also against an extended Kalman filter (EKF), where the robustness of the nonlinear methods compared with the EKF are demonstrated in simulations and experiments.

scholarly journals A Nonlinear Observer to Estimate the Effective Reproduction Number of Infectious Diseases

2021 ◽  
Vol 4 (1) ◽  
pp. 39-45
Author(s):  
Agus Hasan
Keyword(s):  
Kalman Filter ◽  
Infectious Diseases ◽  
Extended Kalman Filter ◽  
Discrete Time ◽  
Reproduction Number ◽  
Epidemiological Data ◽  
Sir Model ◽  
Nonlinear Observer ◽  
Linear Matrix ◽  
Matrix Inequality

In this paper, we design a Nonlinear Observer (NLO) to estimate the effective reproduction number (Rt) of infectious diseases. The NLO is designed from a discrete-time augmented Susceptible-Infectious-Removed (SIR) model. The observer gain is obtained by solving a Linear Matrix Inequality (LMI). The method is used to estimate Rt in Jakarta using epidemiological data during COVID-19 pandemic. If the observer gain is tuned properly, this approach produces similar result compared to existing approach such as Extended Kalman filter (EKF).

Road Bank Estimation on Uneven Terrain for Unmanned Ground Vehicles

2010 ◽  
Author(s):  
Lowell S. Brown ◽  
Jeremy J. Dawkins ◽  
Ryan S. Hill ◽  
David M. Bevly
Keyword(s):  
Kalman Filter ◽  
Extended Kalman Filter ◽  
Unmanned Ground Vehicles ◽  
Ground Vehicles ◽  
Bank Angle ◽  
The Road ◽  
Uneven Terrain ◽  
Suspension Geometry ◽  
Vehicle Information

Knowledge of non-negligible bank angle is important for preventing rollover on uneven terrain. This article shows the effect of uneven terrain on rollover and explores a method to calculate the bank of the uneven terrain. An Extended Kalman Filter (EKF) is implemented to estimate the total roll of the vehicle. Information on the relative roll of the vehicle is acquired from suspension geometry and suspension deflections. The combination of EKF estimated roll and measured suspension deflections yields an estimate of the road bank angle.

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