Extended Kalman Filter Infusion Algorithm Design and Application Characteristics Analysis to Stochastic Closed Loop Fan Speed Control of the Nonlinear Turbo-Fan Engine

2019 ◽  
pp. 1775-1794
Author(s):  
Xiaowu Lv ◽  
Yuansuo Zhang
Keyword(s):  
Kalman Filter ◽  
Extended Kalman Filter ◽  
Closed Loop ◽  
Algorithm Design ◽  
Speed Control ◽  
Characteristics Analysis ◽  
Application Characteristics ◽  
Fan Speed ◽  
Design And Application

scholarly journals A Two-stage Kalman Filter for Sensorless Direct Torque Controlled PM Synchronous Motor Drive

2013 ◽  
Vol 2013 ◽  
pp. 1-12
Author(s):  
Boyu Yi ◽  
Longyun Kang ◽  
Kai Jiang ◽  
Yujian Lin
Keyword(s):  
Kalman Filter ◽  
Extended Kalman Filter ◽  
Closed Loop ◽  
Permanent Magnet Synchronous Motor ◽  
Synchronous Motor ◽  
Motor Drive ◽  
The Novel ◽  
Two Stage ◽  
Effective Implementation ◽  
Pm Synchronous Motor

This paper presents an optimal two-stage extended Kalman filter (OTSEKF) for closed-loop flux, torque, and speed estimation of a permanent magnet synchronous motor (PMSM) to achieve sensorless DTC-SVPWM operation of drive system. The novel observer is obtained by using the same transformation as in a linear Kalman observer, which is proposed by C.-S. Hsieh and F.-C. Chen in 1999. The OTSEKF is an effective implementation of the extended Kalman filter (EKF) and provides a recursive optimum state estimation for PMSMs using terminal signals that may be polluted by noise. Compared to a conventional EKF, the OTSEKF reduces the number of arithmetic operations. Simulation and experimental results verify the effectiveness of the proposed OTSEKF observer for DTC of PMSMs.

Enhanced closed loop State of Charge estimator for lithium-ion batteries based on Extended Kalman Filter

2015 ◽  
Vol 155 ◽  
pp. 834-845 ◽  
Author(s):  
Gustavo Pérez ◽  
Maitane Garmendia ◽  
Jean François Reynaud ◽  
Jon Crego ◽  
Unai Viscarret
Keyword(s):  
Kalman Filter ◽  
Lithium Ion Batteries ◽  
Extended Kalman Filter ◽  
Closed Loop ◽  
Lithium Ion ◽  
State Of Charge

scholarly journals An Extended Kalman Filter, with pre-adjusted covariance matrices, applied to the sensorless speed control of three-phase induction motors

2020 ◽  
pp. 109-126
Author(s):  
Leonardo de Magalhães Lopes ◽  
Zélia Myriam Assis Peixoto
Keyword(s):  
Kalman Filter ◽  
Extended Kalman Filter ◽  
Induction Motors ◽  
Sensorless Control ◽  
Speed Control ◽  
Covariance Matrices ◽  
Operating Conditions ◽  
Control Technique ◽  
State Variables ◽  
Three Phase

With the emergence of sensorless control methods, there was a need for the use of estimators and/or state observers to give it the robustness and precision required in the drive of induction motors. This work deals with the application of the Extended Kalman Filter (EKF) in the estimation of rotor speed and position, aiming at the implementation of the indirect vector control technique in a sensorless speed control system for three-phase induction motors. The mathematical development of the system state variables associated with the EKF stochastic process is presented in this study, and point out its application under variable speed and load conditions, which are imposed on these motors in everyday life. The sensorless control strategy was tested through routine lines in the Matlab® software, simulating operating conditions of this type of engine, being proven its performance, as well as the convergence times consistent with the usual requirements of high performance systems. The main contributions of this work are the use of a reduced-order EKF (ROEKF) and the preset of covariance matrices to accelerate convergence in speed and position estimates for future implementations in currently accessible digital signal processors.

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