A System Identification and Implementation of a Soft Sensor for Freeform Bending

The primary goal of this study is the formulation of a soft sensor that predicts industrially relevant mechanical properties for freeform bending. This serves as the foundation of a closed-loop property control. It is hypothesized that by inline measurement of hardness, predictions regarding residual hoop stresses, local strength and strain level can be achieved. A novel hardness-based correlation scheme is introduced, which is implemented into an extended Kalman filter (EKF) and allows an inline prediction of local strength, residual hoop stresses and plasticity. Furthermore, the ultrasonic contact impedance (UCI) method is validated as a suitable inline measuring solution.

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

Lecture Notes in Electrical Engineering - The Proceedings of the 2018 Asia-Pacific International Symposium on Aerospace Technology (APISAT 2018) ◽

10.1007/978-981-13-3305-7_143 ◽

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

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

Mathematical Problems in Engineering ◽

10.1155/2013/768736 ◽

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.

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A Geometric Observer-Assisted Approach to Tailor State Estimation in a Bioreactor for Ethanol Production

Processes ◽

10.3390/pr8040480 ◽

2020 ◽

Vol 8 (4) ◽

pp. 480 ◽

Cited By ~ 4

Author(s):

Silvia Lisci ◽

Massimiliano Grosso ◽

Stefania Tronci

Keyword(s):

Numerical Simulation ◽

Kalman Filter ◽

State Estimation ◽

Extended Kalman Filter ◽

Systematic Approach ◽

Soft Sensor ◽

Structure Design ◽

Dissolved Oxygen Concentration ◽

Substrate Concentrations ◽

Quality Indexes

In this work, a systematic approach based on the geometric observer is proposed to design a model-based soft sensor, which allows the estimation of quality indexes in a bioreactor. The study is focused on the structure design problem where the set of innovated states has to be chosen. On the basis of robust exponential estimability arguments, it is found that it is possible to distinguish all the unmeasured states if temperature and dissolved oxygen concentration measurements are combined with substrate concentrations. The proposed estimator structure is then validated through numerical simulation considering two different measurement processor algorithms: the geometric observer and the extended Kalman filter.

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