Application of an extended Kalman filter to an advanced fire control system

1977 ◽  
Author(s):  
Peter Maybeck ◽  
Robert Lutter
Keyword(s):  
Kalman Filter ◽  
Control System ◽  
Extended Kalman Filter ◽  
Fire Control

Applications of Extended Kalman Filter for Position Sensorless Control of Permanent Magnet Linear Synchronous Motor

2013 ◽  
Vol 834-836 ◽  
pp. 1240-1245 ◽  
Author(s):  
Wei Min Yang ◽  
Li Jiao Pan ◽  
Peng Fei Zheng ◽  
Yong Qiang He
Keyword(s):  
Kalman Filter ◽  
Control System ◽  
Permanent Magnet ◽  
Extended Kalman Filter ◽  
Sensorless Control ◽  
Synchronous Motor ◽  
Position Sensor ◽  
Linear Synchronous Motor ◽  
Close Loop Control ◽  
Position Sensorless

Control system with position sensor is susceptible to the severe environment such as high temperature, humidity and vibration, which reduce the stability of control system. Position sensorless control of permanent magnet linear synchronous motor need not position sensor so that it can use in abominable environment. According to three phases voltage and two phases current measured from motor, the position and speed of motors mover can be estimated directly based on extended Kalman filter algorithm which is a kind of recursive algorithm. So position sensorless close loop control of PMLSM can be realized.

Application of Active Disturbance Rejection Cotroller in Sensorless Vector Control System of PMSM

2013 ◽  
Vol 273 ◽  
pp. 449-453
Author(s):  
Shu Gong Xue ◽  
Xin Zhu Sun
Keyword(s):  
Kalman Filter ◽  
Control System ◽  
Extended Kalman Filter ◽  
Disturbance Rejection ◽  
Permanent Magnet Synchronous Motor ◽  
Estimation Accuracy ◽  
Speed Controller ◽  
Sensorless Vector Control ◽  
Active Disturbance Rejection ◽  
Vector Control System

To improve the anti-disturbance capabilities of sensorless control system of permanent magnet synchronous motor PMSM), study on application of active disturbance rejection controller (ADRC) is put forward.The extended Kalman filter (EKF) algorithm is proprosed to estimate the rotor speed and position of PMSM for the realization of sensorless control.The ADRC is introduced to the control of speed loop to improve the control performances. Simulation results show that extended kalman filter algorithm worked well,and the proposed control strategy is superior to conventional PI speed controller for its no overshoot, high estimation accuracy,stronger capacity of anti-load-torque- disturbance and etc.

THE STUDY TO APPLY FUZZY WEIGHTED INPUT ESTIMATION FOR THE PREDICTION OF TARGET TRAJECTORY IN A FIRE CONTROL SYSTEM

2017 ◽  
Vol 41 (1) ◽  
pp. 1-21
Author(s):  
Yi-Wei Chen ◽  
Yung-Lung Lee ◽  
Yen-Bin Chen
Keyword(s):  
Kalman Filter ◽  
Control System ◽  
Three Dimensional ◽  
Fire Control ◽  
Input Estimation ◽  
Target State ◽  
Maneuvering Target ◽  
Target Trajectory ◽  
Precise Estimation ◽  
Miss Distance

The fuzzy weighted input estimation (FWIE) is proposed in this paper to solve the problem of noise disturbance and combined with the three-dimensional motion equation of target trajectory to construct the tracking rule of fire control system. FWIE can estimate effectively the input data of maneuvering target acceleration to obtain the precise target state and solve the problems from the traditional Kalman filter which cannot compute the precise estimation of target state because of the input information in the system. Simulation results show that FWIE can estimate the change of target state rapidly and precisely compared with the extended Kalman filter and the proposed tracking rule can improve the fire control system to figure out the target intercepting points with shorter miss distance.

THE EXTENDED KALMAN FILTER AUGMENTED BY AN ADAPTIVE DIGITAL FILTER FOR DATA FUSION OF A MOBILE ROBOT CONTROL SYSTEM

2020 ◽  
Vol 2 ◽  
pp. 85-94
Author(s):  
P.A. BEZMEN
Keyword(s):  
Kalman Filter ◽  
Control System ◽  
Data Fusion ◽  
Mobile Robot ◽  
Extended Kalman Filter ◽  
Digital Filter ◽  
Robot Control ◽  
Mobile Robot Control ◽  
Operational Error ◽  
Robot Control System

The paper proposes the combination of the extended Kalman filter and an adaptive digital filter to compensate an operational error of the extended Kalman filter during data fusion of a mobile robot control system. The paper describes the structure and operation of such combination, shows the buffer memory configuration of an adaptive digital filter.

Sign in / Sign up

Export Citation Format

Share Document