Experimental Parameter Identification of a Time Delayed Oscillator

2005 ◽  
Author(s):  
Brian P. Mann ◽  
Keith A. Young ◽  
Amy M. Helvey ◽  
Raul E. Zapata
Keyword(s):  
Parameter Identification ◽  
Experimental Parameter ◽  
Parametric Identification ◽  
Model Parameters ◽  
Element Analysis ◽  
Delayed Systems ◽  
Infinite Dimensional ◽  
Novel Approach ◽  
Dimensional Phase Space ◽  
The Stability

This paper departs from the more traditional focus of systems with time delays — the loss of stability — to examine an intrinsic benefit of time-delayed systems and a novel approach for parametric identification. For instance, it is well-known that the presence of a time delay will result in an infinite dimensional phase space and can compromise the stability characteristics of a dynamical system. This paper explores the utilization the system higher dimensional transients to provide benefit to the common problem of system identification. Observations are first made about which experimental milling tests can be utilized for parameter identification. A model for the milling experiment is then introduced and a temporal finite element analysis is performed to transform the original delay equations into the form of a dynamic map. Experimental data is then examined with empirical Floquet theory and principal orthogonal decomposition to estimate the reduced order dynamics, or truncated state space dimension, and to identify the empirical Floquet multipliers of the system. Parametric identification is performed through the optimization of model parameters that satisfy the characteristic equation.

An empirical approach for delayed oscillator stability and parametric identification

2006 ◽  
Vol 462 (2071) ◽  
pp. 2145-2160 ◽  
Author(s):  
Brian P Mann ◽  
Keith A Young
Keyword(s):  
Numerical Data ◽  
Parametric Identification ◽  
Empirical Approach ◽  
Accurate Estimation ◽  
Model Parameters ◽  
Machining Processes ◽  
Feedback Control Systems ◽  
Reconstructed Time Series ◽  
The Stability ◽  
Characteristic Multipliers

This paper investigates a semi-empirical approach for determining the stability of systems that can be modelled by ordinary differential equations with a time delay. This type of model is relevant to biological oscillators, machining processes, feedback control systems and models for wave propagation and reflection, where the motion of the waves themselves is considered to be outside the system model. A primary aim is to investigate the extension of empirical Floquet theory to experimental or numerical data obtained from time-delayed oscillators. More specifically, the reconstructed time series from a numerical example and an experimental milling system are examined to obtain a finite number of characteristic multipliers from the reduced order dynamics. A secondary goal of this work is to demonstrate a benefit of empirical characteristic multiplier estimation by performing system identification on a delayed oscillator. The principal results from this study are the accurate estimation of delayed oscillator characteristic multipliers and the utilization the empirical results for parametric identification of model parameters. Combining these results with previous research on an experimental milling system provides a particularly relevant result—the first approach for identifying all model parameters for stability prediction directly from the cutting process vibration history.

scholarly journals Dynamics of the rumor-spreading model with hesitation mechanism in heterogenous networks and bilingual environment

2020 ◽  
Vol 2020 (1) ◽  
Author(s):  
Shuai Yang ◽  
Haijun Jiang ◽  
Cheng Hu ◽  
Juan Yu ◽  
Jiarong Li
Keyword(s):  
Lyapunov Method ◽  
Reproduction Number ◽  
Model Parameters ◽  
Rumor Spreading ◽  
Spreading Model ◽  
Reductio Ad Absurdum ◽  
The Stability ◽  
The Impact ◽  
Theoretical Results ◽  
The Basic Reproduction Number

Abstract In this paper, a novel rumor-spreading model is proposed under bilingual environment and heterogenous networks, which considers that exposures may be converted to spreaders or stiflers at a set rate. Firstly, the nonnegativity and boundedness of the solution for rumor-spreading model are proved by reductio ad absurdum. Secondly, both the basic reproduction number and the stability of the rumor-free equilibrium are systematically discussed. Whereafter, the global stability of rumor-prevailing equilibrium is explored by utilizing Lyapunov method and LaSalle’s invariance principle. Finally, the sensitivity analysis and the numerical simulation are respectively presented to analyze the impact of model parameters and illustrate the validity of theoretical results.

scholarly journals Explaining Neural Networks Using Attentive Knowledge Distillation

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1280
Author(s):  
Hyeonseok Lee ◽  
Sungchan Kim
Keyword(s):  
Neural Networks ◽  
Model Prediction ◽  
Saliency Map ◽  
Model Parameters ◽  
Learning Capability ◽  
Fine Grained ◽  
Network Layers ◽  
Saliency Maps ◽  
Novel Approach ◽  
Knowledge Distillation

Explaining the prediction of deep neural networks makes the networks more understandable and trusted, leading to their use in various mission critical tasks. Recent progress in the learning capability of networks has primarily been due to the enormous number of model parameters, so that it is usually hard to interpret their operations, as opposed to classical white-box models. For this purpose, generating saliency maps is a popular approach to identify the important input features used for the model prediction. Existing explanation methods typically only use the output of the last convolution layer of the model to generate a saliency map, lacking the information included in intermediate layers. Thus, the corresponding explanations are coarse and result in limited accuracy. Although the accuracy can be improved by iteratively developing a saliency map, this is too time-consuming and is thus impractical. To address these problems, we proposed a novel approach to explain the model prediction by developing an attentive surrogate network using the knowledge distillation. The surrogate network aims to generate a fine-grained saliency map corresponding to the model prediction using meaningful regional information presented over all network layers. Experiments demonstrated that the saliency maps are the result of spatially attentive features learned from the distillation. Thus, they are useful for fine-grained classification tasks. Moreover, the proposed method runs at the rate of 24.3 frames per second, which is much faster than the existing methods by orders of magnitude.

scholarly journals Inlay-Retained Dental Bridges—A Finite Element Analysis

2021 ◽  
Vol 11 (9) ◽  
pp. 3770
Author(s):  
Monica Tatarciuc ◽  
George Alexandru Maftei ◽  
Anca Vitalariu ◽  
Ionut Luchian ◽  
Ioana Martu ◽  
...  
Keyword(s):  
Finite Element ◽  
Young Patients ◽  
Maximum Pressure ◽  
Class Iii ◽  
Element Analysis ◽  
Dental Prostheses ◽  
Abutment Teeth ◽  
Fixed Dental Prostheses ◽  
Implant Therapy ◽  
The Stability

Inlay-retained dental bridges can be a viable minimally invasive alternative when patients reject the idea of implant therapy or conventional retained full-coverage fixed dental prostheses, which require more tooth preparation. Inlay-retained dental bridges are indicated in patients with good oral hygiene, low susceptibility to caries, and a minimum coronal tooth height of 5 mm. The present study aims to evaluate, through the finite element method (FEM), the stability of these types of dental bridges and the stresses on the supporting teeth, under the action of masticatory forces. The analysis revealed the distribution of the load on the bridge elements and on the retainers, highlighting the areas of maximum pressure. The results of our study demonstrate that the stress determined by the loading force cannot cause damage to the prosthetic device or to abutment teeth. Thus, it can be considered an optimal economical solution for treating class III Kennedy edentation in young patients or as a provisional pre-implant rehabilitation option. However, special attention must be paid to its design, especially in the connection area between the bridge elements, because the connectors and the retainers represent the weakest parts.

scholarly journals Use of Dynamic Analysis to Investigate the Behaviour of Short Neutral Sections in the Overhead Line Electrification

2021 ◽  
Vol 6 (5) ◽  
pp. 62
Author(s):  
John Morris ◽  
Mark Robinson ◽  
Roberto Palacin
Keyword(s):  
Dynamic Analysis ◽  
Dynamic Simulation ◽  
Model Simulation ◽  
Analysis Tool ◽  
Overhead Line ◽  
Element Analysis ◽  
Novel Approach ◽  
Section Model ◽  
The Uk ◽  
Neutral Section

The ‘short’ neutral section is a feature of alternating current (AC) railway overhead line electrification that is often unreliable and a source of train delays. However hardly any dynamic analysis of its behaviour has been undertaken. This paper briefly describes the work undertaken investigating the possibility of modelling the behaviour using a novel approach. The potential for thus improving the performance of short neutral sections is evaluated, with particular reference to the UK situation. The analysis fundamentally used dynamic simulation of the pantograph and overhead contact line (OCL) interface, implemented using a proprietary finite element analysis tool. The neutral section model was constructed using physical characteristics and laboratory tests data, and was included in a validated pantograph/OCL simulation model. Simulation output of the neutral section behaviour has been validated satisfactorily against real line test data. Using this method the sensitivity of the neutral section performance in relation to particular parameters of its construction was examined. A limited number of parameter adjustments were studied, seeking potential improvements. One such improvement identified involved the additional inclusion of a lever arm at the trailing end of the neutral section. A novel application of pantograph/OCL dynamic simulation to modelling neutral section behaviour has been shown to be useful in assessing the modification of neutral section parameters.

scholarly journals Parameter Identification and State-of-Charge Estimation for Lithium-Ion Batteries Using Separated Time Scales and Extended Kalman Filter

Energies ◽  
2021 ◽  
Vol 14 (4) ◽  
pp. 1054
Author(s):  
Kuo Yang ◽  
Yugui Tang ◽  
Zhen Zhang
Keyword(s):  
Kalman Filter ◽  
Parameter Identification ◽  
Open Circuit Voltage ◽  
Lithium Ion ◽  
Open Circuit ◽  
State Of Charge ◽  
Recursive Least Squares ◽  
Model Parameters ◽  
Soc Estimation ◽  
Battery Model

With the development of new energy vehicle technology, battery management systems used to monitor the state of the battery have been widely researched. The accuracy of the battery status assessment to a great extent depends on the accuracy of the battery model parameters. This paper proposes an improved method for parameter identification and state-of-charge (SOC) estimation for lithium-ion batteries. Using a two-order equivalent circuit model, the battery model is divided into two parts based on fast dynamics and slow dynamics. The recursive least squares method is used to identify parameters of the battery, and then the SOC and the open-circuit voltage of the model is estimated with the extended Kalman filter. The two-module voltages are calculated using estimated open circuit voltage and initial parameters, and model parameters are constantly updated during iteration. The proposed method can be used to estimate the parameters and the SOC in real time, which does not need to know the state of SOC and the value of open circuit voltage in advance. The method is tested using data from dynamic stress tests, the root means squared error of the accuracy of the prediction model is about 0.01 V, and the average SOC estimation error is 0.0139. Results indicate that the method has higher accuracy in offline parameter identification and online state estimation than traditional recursive least squares methods.

An improved nonlinear innovation-based parameter identification algorithm for ship models

2021 ◽  
pp. 1-9
Author(s):  
Baigang Zhao ◽  
Xianku Zhang
Keyword(s):  
Parameter Identification ◽  
Test Data ◽  
Stochastic Gradient ◽  
Least Square ◽  
Gradient Algorithm ◽  
Model Parameters ◽  
Identification Algorithm ◽  
Process Innovations ◽  
Stochastic Gradient Algorithm ◽  
Tangent Function

Abstract To solve the problem of identifying ship model parameters quickly and accurately with the least test data, this paper proposes a nonlinear innovation parameter identification algorithm for ship models. This is based on a nonlinear arc tangent function that can process innovations on the basis of an original stochastic gradient algorithm. A simulation was carried out on the ship Yu Peng using 26 sets of test data to compare the parameter identification capability of a least square algorithm, the original stochastic gradient algorithm and the improved stochastic gradient algorithm. The results indicate that the improved algorithm enhances the accuracy of the parameter identification by about 12% when compared with the least squares algorithm. The effectiveness of the algorithm was further verified by a simulation of the ship Yu Kun. The results confirm the algorithm's capacity to rapidly produce highly accurate parameter identification on the basis of relatively small datasets. The approach can be extended to other parameter identification systems where only a small amount of test data is available.

scholarly journals A Novel Approach to Fabricate Foam Ceramics from Steel Slag

2020 ◽  
Vol 2020 ◽  
pp. 1-7
Author(s):  
Yu Zheng ◽  
Xudong Luo ◽  
Jinlong Yang ◽  
Wenlong Huo ◽  
Chi Kang
Keyword(s):  
Compressive Strength ◽  
Ph Value ◽  
Steel Slag ◽  
Raw Material ◽  
Solid Loading ◽  
Insulation Material ◽  
Ceramic Foams ◽  
Novel Approach ◽  
The Stability ◽  
First Time

A novel approach is used for fabricating steel slag foam ceramics based on the particle-stabilized foaming method. In this work, steel slag was used as the raw material and propyl gallate (PG) was used as the surface modifier. For the first time, steel slag ceramic foams were successfully fabricated based on particle-stabilized foams. The results show that the stability of the ceramic foams was closely related to the pH value and PG concentration. The porosity and compressive strength could be controlled by changing the solid loading of steel slag and sintering temperature. The porosity of steel slag foam ceramics ranged from 85.6% to 62.53%, and the compressive strength was from 1.74 MPa to 10.42 MPa. The thermal conductivity of steel slag foam ceramics was only 0.067 W (m·K)−1, which shows that it could be used as a thermal insulation material.

Model and Stability of the Traffic Flow Consisting of Heterogeneous Drivers

2015 ◽  
Vol 10 (3) ◽  
Author(s):  
Da Yang ◽  
Liling Zhu ◽  
Yun Pu
Keyword(s):  
Traffic Flow ◽  
Heterogeneous Traffic ◽  
Model Parameters ◽  
Optimal Velocity ◽  
Stability Functions ◽  
Car Following Model ◽  
Traffic Wave ◽  
The Stability ◽  
Different Characteristics ◽  
Stationary Velocity

Although traffic flow has attracted a great amount of attention in past decades, few of the studies focused on heterogeneous traffic flow consisting of different types of drivers or vehicles. This paper attempts to investigate the model and stability analysis of the heterogeneous traffic flow, including drivers with different characteristics. The two critical characteristics of drivers, sensitivity and cautiousness, are taken into account, which produce four types of drivers: the sensitive and cautious driver (S-C), the sensitive and incautious driver (S-IC), the insensitive and cautious driver (IS-C), and the insensitive and incautious driver (IS-IC). The homogeneous optimal velocity car-following model is developed into a heterogeneous form to describe the heterogeneous traffic flow, including the four types of drivers. The stability criterion of the heterogeneous traffic flow is derived, which shows that the proportions of the four types of drivers and their stability functions only relating to model parameters are two critical factors to affect the stability. Numerical simulations are also conducted to verify the derived stability condition and further explore the influences of the driver characteristics on the heterogeneous traffic flow. The simulations reveal that the IS-IC drivers are always the most unstable drivers, the S-C drivers are always the most stable drivers, and the stability effects of the IS-C and the S-IC drivers depend on the stationary velocity. The simulations also indicate that a wider extent of the driver heterogeneity can attenuate the traffic wave.

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