Influence of insulation model parameters on transfer function zero evaluated for diagnosis of oil-paper insulation

2017 ◽  
Author(s):  
C.M. Banerjee ◽  
Saurabh ◽  
A. Baral ◽  
S. Chakravorti
Keyword(s):  
Transfer Function ◽  
Model Parameters ◽  
Paper Insulation

scholarly journals Parameter Estimation of DC Motor using Adaptive Transfer Function Based on Nelder-Mead Optimisation

2018 ◽  
Vol 9 (3) ◽  
pp. 696 ◽  
Author(s):  
Byamakesh Nayak ◽  
Sangeeta Sahu ◽  
Tanmoy Roy Choudhury
Keyword(s):  
Experimental Data ◽  
Transfer Function ◽  
Adaptive Method ◽  
Dc Motor ◽  
Model Parameters ◽  
Current Response ◽  
Adaptive Model ◽  
Unknown Parameters ◽  
Dc Motors ◽  
Estimated Parameters

<p>This paper explains an adaptive method for estimation of unknown parameters of transfer function model of any system for finding the parameters. The transfer function of the model with unknown model parameters is considered as the adaptive model whose values are adapted with the experimental data. The minimization of error between the experimental data and the output of the adaptive model have been realised by choosing objective function based on different error criterions. Nelder-Mead optimisation Method is used for adaption algorithm. To prove the method robustness and for students learning, the simple system of separately excited dc motor is considered in this paper. The experimental data of speed response and corresponding current response are taken and transfer function parameters of  dc motors are adapted based on Nelder-Mead optimisation to match with the experimental data. The effectiveness of estimated parameters with different objective functions are compared and validated with machine specification parameters.</p>

Individualized Transfer Functions for the Noninvasive Estimation of Central Pressure From Brachial Pressure Readings

2009 ◽  
Author(s):  
Ashis Mookerjee ◽  
Ahmed M. Al-Jumaily ◽  
Andrew Lowe
Keyword(s):  
Blood Pressure ◽  
Transfer Function ◽  
Brachial Artery ◽  
Transfer Functions ◽  
Patient Characteristics ◽  
Patient Specific ◽  
Model Parameters ◽  
Brachial Blood Pressure ◽  
Noninvasive Estimation ◽  
Artery Segment

A model-based investigation is carried out with the aim of developing an ab-initio methodology for the patient-specific estimation of central pressures from brachial blood pressure readings. The subclavian root-brachial artery segment is modeled as a 1-D tube with all model parameters linked to patient characteristics. A simulation is also run with typical physiological parameters, which gives a “first estimate” of the transfer function (TF). The TF derived using the patient characteristics is studied in detail to investigate the change in the arterial TF occurring with changes in patient characteristics. This TF is compared with the “first estimate” to evaluate the feasibility of using standard arterial properties.

scholarly journals Combing Instrumental Variable and Variance Matching for Aircraft Flutter Model Parameters Identification

2019 ◽  
Vol 2019 ◽  
pp. 1-12
Author(s):  
Hong Jianwang ◽  
Ricardo A. Ramirez-Mendoza ◽  
Jorge de J. Lozoya Santos
Keyword(s):  
Transfer Function ◽  
Stochastic Model ◽  
Instrumental Variable ◽  
Covariance Function ◽  
Electrical Current ◽  
Current Loop ◽  
Model Parameters ◽  
Criterion Function ◽  
Variance Method ◽  
New Criterion

When the observed input-output data are corrupted by the observed noises in the aircraft flutter stochastic model, we need to obtain the more exact aircraft flutter model parameters to predict the flutter boundary accuracy and assure flight safety. So, here we combine the instrumental variable method in system identification theory and variance matching in modern spectrum theory to propose a new identification strategy: instrumental variable variance method. In the aircraft flutter stochastic model, after introducing instrumental variable to develop a covariance function, a new criterion function, composed by a difference between the theory value and actual estimation value of the covariance function, is established. Now, the new criterion function based on the covariance function can be used to identify the unknown parameter vector in the transfer function form. Finally, we apply this new instrumental variable variance method to identify the transfer function in one electrical current loop of flight simulator and aircraft flutter model parameters. Several simulation experiments have been performed to demonstrate the effectiveness of the algorithm proposed in this paper.

Modeling and Design Implications of Noncollocated Control in Flexible Systems

1990 ◽  
Vol 112 (2) ◽  
pp. 186-193 ◽  
Author(s):  
V. A. Spector ◽  
H. Flashner
Keyword(s):  
Transfer Function ◽  
Structural Control ◽  
High Sensitivity ◽  
Wave Number ◽  
Model Parameters ◽  
Generic Properties ◽  
Distributed Sensors ◽  
Function Zeros ◽  
Euler Bernoulli Beam ◽  
Qualitative Characteristics

In this paper we investigate generic properties of structural modeling pertinent to structural control, with emphasis on noncollocated systems. Analysis is performed on a representative example of a pinned-free Euler-Bernoulli beam with distributed sensors. Analysis in the wave number plane highlights the crucial qualitative characteristics common to all structural systems. High sensitivity of the transfer function zeros to errors in model parameters and sensor locations is demonstrated. The existence of finite right half plane zeros in noncollocated systems, along with this high sensitivity, further complicates noncollocated controls design. A numerical method for accurate computation of the transfer function zeros is proposed. Wiener-Hopf factorization is used to compute equivalent delay time, which is important in controls design.

scholarly journals A High-Order Load Model and the Control Algorithm for an Aerospace Electro-Hydraulic Actuator

Actuators ◽  
2021 ◽  
Vol 10 (3) ◽  
pp. 53
Author(s):  
Shoujun Zhao ◽  
Keqin Chen ◽  
Xiaosha Zhang ◽  
Yingxin Zhao ◽  
Guanghui Jing ◽  
...  
Keyword(s):  
Transfer Function ◽  
Fourth Order ◽  
Dynamic Pressure ◽  
Resonance Effect ◽  
Notch Filter ◽  
High Order ◽  
Model Parameters ◽  
Hydraulic Actuator ◽  
Control Block ◽  
Load Model

It is difficult to describe precisely, and thus control satisfactorily, the dynamics of an electro-hydraulic actuator to drive a high thrust liquid launcher engine, whose structural resonant frequency is usually low due to its heavy inertia and complicated mass distribution, let alone one to drive a heavy kerolox engine with high-order dynamics. By transforming classic control block diagrams, a baseline two-mass-two-spring load model and a normalized actuator-engine system model were developed for understanding the basic physics and methodology, where a fourth-order transfer function is used to model the multi-resonance-frequency engine body outside of the rod position loop, another fourth-order transfer function with two pairs of conjugated zeros and poles to represent the composite hydro-mechanical resonance effect in the closed rod position loop. A sixth-order model was thereafter proposed for even higher dynamics. The model parameters were identified and optimized by a full factor search approach. To meet the stringent specification of static and dynamic performances, it was demonstrated that a notch filter network combined with other controllers is needed since the traditional dynamic pressure feedback (DPF) is difficult to handle the high-order dynamics. The approach has been validated by simulation, experiments and successful flights. The models, analysis, data and insights were elaborated.

scholarly journals Contrasting open-loop dynamic characteristics of sympathetic and vagal systems during baroreflex-mediated heart rate control in rats

2019 ◽  
Vol 317 (6) ◽  
pp. R879-R890 ◽  
Author(s):  
Toru Kawada ◽  
Hiromi Yamamoto ◽  
Yohsuke Hayama ◽  
Takuya Nishikawa ◽  
Kunihiko Tanaka ◽  
...  
Keyword(s):  
Heart Rate ◽  
Transfer Function ◽  
Dynamic Characteristics ◽  
Carotid Sinus ◽  
Gaussian White Noise ◽  
Open Loop ◽  
Model Parameters ◽  
Before And After ◽  
Dynamic Gain ◽  
Sinus Pressure

Although heart rate (HR) is governed by the sympathetic and parasympathetic nervous systems, a head-to-head comparison of the open-loop dynamic characteristics of the total arc from a baroreceptor pressure input to the HR response has yet to be performed. We estimated the transfer function from carotid sinus pressure input to the HR response ( HCSP→HR) before and after bilateral vagotomy ( n = 7) as well as before and after the administration of a β-blocker propranolol ( n = 8) in anesthetized male Wistar-Kyoto rats. The carotid sinus pressure was perturbed according to a Gaussian white noise signal so that the input power spectra were relatively flat between 0.01 and 1 Hz. The gain plot of HCSP→HR was V-shaped. Vagotomy reduced the dynamic gain at 1 Hz (0.0598 ± 0.0065 to 0.0025 ± 0.0004 beats·min−1·mmHg−1, P < 0.001) but not at 0.01 or 0.1 Hz. β-Blockade reduced the dynamic gain at 0.01 Hz (0.247 ± 0.069 to 0.077 ± 0.017 beats·min−1·mmHg−1, P = 0.020) but not at 0.1 or 1 Hz. We also estimated the efferent limb transfer function from electrical vagal efferent stimulation to the HR response ( HVN→HR) under β-blockade conditions. We associated the model parameters of HVN→HR with the mean HR and the standard deviation of HR so that HVN→HR could be estimated based only on the HR data. We finally estimated the neural arc transfer function from a pressure input to efferent vagal nerve activity by dividing HCSP→HR by HVN→HR. The mathematically determined vagal neural arc showed derivative characteristics with its phase near zero radians at the lowest frequency.

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