scholarly journals Short Data-Based Output-Only Identification for Time-Varying Systems with Fast Dynamic Evolution

2019 ◽  
Vol 2019 ◽  
pp. 1-11
Author(s):  
Zhi-Sai Ma ◽  
Qian Ding
Keyword(s):  
Ordinary Least Squares ◽  
Operating Conditions ◽  
Dynamic Evolution ◽  
Model Parameters ◽  
Time Interval ◽  
Short Time Interval ◽  
Time Varying ◽  
Tracking Accuracy ◽  
Output Only ◽  
Fast Dynamic

Many engineering systems change appreciably over a relatively short time interval due to their fast evolution in the dynamics. Time-varying (TV) system’s ambient excitation is usually difficult to measure under operating conditions, and its dynamics have to be determined without measuring the excitation. Therefore, short data-based output-only identification for TV systems with fast dynamic evolution is considered in this paper. Deterministic parameter evolution methods are known to track fast dynamic evolution by postulating TV model parameters as deterministic functions of time and selecting proper functional subspaces. However, these methods require a significant number of parameters to represent complicated time-dependencies and dynamics characterized by larger numbers of degrees-of-freedom. In such cases, the ordinary least squares estimation may lead to less accurate or even unreliable estimates. A ridge regression-based deterministic parameter evolution method is proposed to overcome ill-posed problems via regularization and subsequently assessed through numerical and experimental validation. Comparative results confirm the advantages of the proposed method in terms of achievable natural frequency and power spectral density tracking, accuracy, and resolution of TV systems with fast dynamic evolution, when the response data length is relatively short.

Using Sliding Mode Control to Adjust Drum Level of a Boiler Unit With Time Varying Parameters

2010 ◽  
Author(s):  
Hamed Moradi ◽  
Firooz Bakhtiari-Nejad ◽  
Majid Saffar-Avval ◽  
Aria Alasty
Keyword(s):  
Water Level ◽  
Transfer Functions ◽  
Sliding Mode ◽  
Operating Conditions ◽  
Model Parameters ◽  
Feed Water ◽  
Time Varying ◽  
Boiler Unit ◽  
Varying Parameters ◽  
Time Varying Parameters

Stable control of water level of drum is of great importance for economic operation of power plant steam generator systems. In this paper, a linear model of the boiler unit with time varying parameters is used for simulation. Two transfer functions between drum water level (output variable) and feed-water and steam mass rates (input variables) are considered. Variation of model parameters may be arisen from disturbances affecting water level of drum, model uncertainties and parameter mismatch due to the variant operating conditions. To achieve a perfect tracking of the desired drum water level, two sliding mode controllers are designed separately. Results show that the designed controllers result in bounded values of control signals, satisfying the actuators constraints.

Development of a Torsional Behavior Powertrain Model for Multiple Misfire Detection

2005 ◽  
Author(s):  
Fabrizio Ponti
Keyword(s):  
Torsional Vibration ◽  
Engine Speed ◽  
Experimental Tests ◽  
Detection Algorithm ◽  
Operating Conditions ◽  
False Alarms ◽  
Time Interval ◽  
Short Time Interval ◽  
Torsional Behavior ◽  
Misfire Detection

Many methodologies have been developed in the past for misfire detection purposes based on the analysis of the instantaneous engine speed. The missing combustion is usually detected thanks to the sudden engine speed decrease that takes place after a misfire event. Misfire detection and in particular cylinder isolation is anyhow still a challenging issue for engines with a high number of cylinders, for engine operating conditions at low load or high engine speed and for multiple misfire events. When a misfire event takes place in fact a torsional vibration is excited and shows up in the instantaneous engine speed waveform. If a multiple misfire occurs this torsional vibration is excited more than once in a very short time interval. The interaction among these successive vibrations can generate false alarms or misdetection, and an increased complexity when dealing with cylinder isolation. The paper presents the development of a powertrain torsional behavior model in order to identify the effects of a misfire event on the instantaneous engine speed signal. The identified waveform has then been used to filter out the torsional vibration effects in order to enlighten the missing combustions even in the case of multiple misfire events. The model response is also used to quicken the setup process for the detection algorithm employed, evaluating before running specific experimental tests on a test bench facility, the values for the threshold and the optimal setup of the procedure. The proposed algorithm is developed in this paper for an SI L4 engine; Its application to other engine configurations is possible, as it is also discussed in the paper.

Instantaneous Engine Speed Analysis for Cylinder Isolation in Multiple Misfire Events

2003 ◽  
Author(s):  
Fabrizio Ponti
Keyword(s):  
Torsional Vibration ◽  
Engine Speed ◽  
Operating Conditions ◽  
Spark Ignition Engine ◽  
Detection Methods ◽  
False Alarms ◽  
Time Interval ◽  
Short Time Interval ◽  
Operating Range ◽  
Misfire Detection

Misfire detection is a subject that has been deep studied during the last years and many methodologies have been developed for this purpose. Affordably detecting the misfire event and isolating the cylinder where the missing combustion took place can be considered a solved problem for engines with a limited number of cylinders. Misfire detection and in particular cylinder isolation is still challenging for engine operating conditions at very low load and high engine speed, for engines with a high number of cylinders, or when more than one misfire event is present within the same engine cycle (multiple misfire). In particular this last malfunctioning condition is very challenging, and its detection is enforced by the international regulations without requiring cylinder isolation, but only the number of misfiring cylinders. Many methodologies have been developed in the past based on the analysis of the instantaneous engine speed. The missing combustion effect on this signal is anyway very low when the number of cylinders is high and for engine operating conditions at low engine speed, giving rise to misdetection or false alarms as already mentioned. In addition when a misfire event takes place a torsional vibration is excited and shows up in the instantaneous engine speed waveform. If a multiple misfire occurs this torsional vibration is excited more than once in a very short time interval. The interaction among these successive vibrations can further generate false alarms or misdetection, and an increased complexity when dealing with cylinder isolation is necessary. The approach here presented permits enhancing existing misfire detection methods through optimized algorithm that allows correctly isolating the multiple misfiring cylinders over the entire engine operating range. This has been obtained by proper identifying the effect of the torsional vibration over the instantaneous engine speed. The identified waveform has been then used to filter out the torsional vibration effects in order to enlighten the effects of the missing combustions. In addition a proper instantaneous engine speed windowing has been introduced in order to increase the detection signal to noise ratio over the whole engine operating range. The integration of these two signal processing techniques has proven to be very effective on the engine investigated in this study, and it is easily extendible to other engine architectures. Particular care has been devoted to satisfy on-board implementation requirements in terms of memory allocation and computational power. The tests have been conducted on an L4 1.2 liter spark ignition engine mounted in a test cell. In-cylinder pressure signals have been acquired in order to validate the methodology here developed.

scholarly journals Characterization and Evolution of a Digital Economy Ecosystem Based on an Interspecies Competition Model

2022 ◽  
Vol 2022 ◽  
pp. 1-12
Author(s):  
Han Zhou ◽  
Xiaorui Han ◽  
Le Wang
Keyword(s):  
Decision Making ◽  
Equilibrium Point ◽  
Digital Economy ◽  
Operating Conditions ◽  
Evolution Model ◽  
Dynamic Evolution ◽  
Model Parameters ◽  
Entrepreneurial Ecosystem ◽  
Interspecies Competition ◽  
The Relationship

This paper provides an in-depth study and analysis of the characterization of the digital economy ecosystem and the mechanism of eye-flowering through the method of interspecies competition. The evolutionary game model of symbiotic decision-making in the entrepreneurial ecosystem is constructed, the evolutionary process of symbiotic decision-making of subjects is analyzed through mathematical derivation, and the symbiotic decision-making process of subjects is simulated through computer simulation to answer how the subjects of the entrepreneurial ecosystem make symbiotic decisions and explore the mechanism of symbiotic formation of the entrepreneurial ecosystem. Then, based on the ecological perspective, the symbiotic evolution model of entrepreneurial ecosystem subjects is constructed from the subject level, the equilibrium point of the evolution of entrepreneurial ecosystem subjects, the stability conditions, and the relationship between the equilibrium point and the symbiosis model are analyzed, and the symbiotic evolution paths of entrepreneurial ecosystem subjects under different symbiosis modes, initial population size, maximum size, and natural growth rate are presented with simulation experiments, respectively. The main characteristics and manifestations of the dynamic evolution of the platform ecosystem are analyzed, and the key competitive factors that determine the dynamic evolution of the platform ecosystem are depicted. Then, according to the inherent characteristic laws of the platform ecosystem, the complex network approach is applied to construct a dynamic evolution model with originality and wide applicability for the change of bilateral user scale. Based on the dynamic evolution process, the relationship between model parameters and business performance is explored, and the trajectory of bilateral user size change over time and the range of parameters are derived by numerical calculation. Finally, using Monte Carlo simulation methods, the dynamic evolution model is used to predict the future operating conditions of platform enterprises, providing a valuation basis for investors to make investment decisions and helping platform managers to formulate business strategies.

scholarly journals Real-Time Prediction of Operating Parameter of TBM during Tunneling

2021 ◽  
Vol 11 (7) ◽  
pp. 2967
Author(s):  
Hang-Lo Lee ◽  
Ki-Il Song ◽  
Chongchong Qi ◽  
Jin-Seop Kim ◽  
Kyoung-Su Kim
Keyword(s):  
Real Time ◽  
Operating Parameter ◽  
Tunnel Boring Machine ◽  
Ordinary Least Squares ◽  
Operating Conditions ◽  
Operating Parameters ◽  
Time Varying ◽  
Practical Applications ◽  
Time Prediction ◽  
Geological Conditions

With the increasing use of the tunnel boring machine (TBM), attempts have been made to predict TBM operating parameters. Prediction of operating parameters is still an important step in the adaptability of the TBM for the future. In this study, we employ a walk forward (WF) prediction method based on ARIMAX, which can consider time-varying features and geological conditions. This method is applied to two different TBM projects to evaluate its performance, and is then compared with WF based on ordinary least squares (OLS). The simulation results show that the ARIMAX predictor outperforms the OLS predictor in both projects. For practical applications, an additional analysis is carried out according to the real-time prediction distance. The results show that time series-based ARIMAX provides meaningful results in 8 rings (11 m) or less of real-time prediction distance. The WF based on ARIMAX can provide reasonable TBM operating conditions with time-varying data and can be utilized in decision-making to improve excavation performance.

Model Transformations to Evaluate Transient Thermal Responses at a Tissue Surface

2001 ◽  
Vol 123 (4) ◽  
pp. 370-372
Author(s):  
Gerald M. Saidel and ◽  
Erin H. Liu
Keyword(s):  
Numerical Solutions ◽  
Temperature Response ◽  
Model Transformations ◽  
Distributed Model ◽  
Transient Temperature ◽  
Model Parameters ◽  
Time Interval ◽  
Short Time Interval ◽  
Tissue Surface ◽  
Transient Thermal

For a spatially distributed model describing the transient temperature response of a thermistor-tissue system, Wei et al., [J. Biomech. Eng., 117:74–85, 1995] obtained an approximate transformation for fast analysis of the temperature response at the tissue surface. This approximate transformation reduces the model to a single ordinary differential equation. Here, we present an exact transformation that yields a single differential-integral equation. Numerical solutions from the approximate and exact transformations were compared to evaluate the differences with several sets of parameter values. The maximum difference between the exact and approximate solutions did not exceed 15 percent and occurred for only a short time interval. The root-mean-square error of the approximate solution was no more than 5 percent and within the level of experimental noise. Under the experimental conditions used by Wei et al., the approximate transformation is justified for estimating model parameters from transient thermal responses.

Development of a Torsional Behavior Powertrain Model for Multiple Misfire Detection

2008 ◽  
Vol 130 (2) ◽  
Author(s):  
Fabrizio Ponti
Keyword(s):  
Torsional Vibration ◽  
Engine Speed ◽  
Detection Algorithm ◽  
Operating Conditions ◽  
Wave Form ◽  
False Alarms ◽  
Time Interval ◽  
Short Time Interval ◽  
Torsional Behavior ◽  
Misfire Detection

Many methodologies have been developed in the past for misfire detection purposes based on the analysis of the instantaneous engine speed. The missing combustion is usually detected, thanks to the sudden engine speed decrease that takes place after a misfire event. Misfire detection and, in particular, cylinder isolation are nevertheless still a challenging issue for engines with a high number of cylinders, for engine operating conditions at low load or high engine speed, and for multiple misfire events. When a misfire event takes place, a torsional vibration is excited and shows up in the instantaneous engine speed wave form. If a multiple misfire occurs, this torsional vibration is excited more than once in a very short time interval. The interaction between these successive vibrations can generate false alarms or misdetection, and an increased complexity when dealing with cylinder isolation. This paper presents the development of a powertrain torsional behavior model in order to identify the effects of a misfire event on the instantaneous engine speed signal. The identified wave form has then been used to filter out the torsional vibration effects in order to enlighten the missing combustions even in the case of multiple misfire events. The model response is also used to speed up the setup process for the detection algorithm employed, thus evaluating, before running specific experimental tests on a test bench facility, the values for the threshold and the optimal setup of the procedure. The proposed algorithm is developed in this paper for an SI L4 engine; its application to other engine configurations is possible, as is also discussed in this paper.

Adaptive control of time-varying non-linear plants by speed-gradient algorithms

2019 ◽  
pp. 37-44 ◽  
Author(s):  
O. P. Tomchina ◽  
D. N. Polyakhov ◽  
O. I. Tokareva ◽  
A. L. Fradkov
Keyword(s):  
Adaptive Control ◽  
Adaptive Systems ◽  
Reference Model ◽  
Maximum Deviation ◽  
Model Parameters ◽  
Time Varying ◽  
System Solution ◽  
Non Linear ◽  
Initial Uncertainty ◽  
Speed Gradient

Introduction: The motion of many real world systems is described by essentially non-linear and non-stationary models. A number of approaches to the control of such plants are based on constructing an internal model of non-stationarity. However, the non-stationarity model parameters can vary widely, leading to more errors. It is only assumed in this paper that the change rate of the object parameters is limited, while the initial uncertainty can be quite large.Purpose: Analysis of adaptive control algorithms for non-linear and time-varying systems with an explicit reference model, synthesized by the speed gradient method.Results: An estimate was obtained for the maximum deviation of a closed-loop system solution from the reference model solution. It is shown that with sufficiently slow changes in the parameters and a small initial uncertainty, the limit error in the system can be made arbitrarily small. Systems designed by the direct approach and systems based on the identification approach are both considered. The procedures for the synthesis of an adaptive regulator and analysis of the synthesized system are illustrated by an example.Practical relevance: The obtained results allow us to build and analyze a broad class of adaptive systems with reference models under non-stationary conditions.

On Multiple Access of a Large Number of Machine-Type Devices in Cellular Networks

2018 ◽  
pp. 105-114
Author(s):  
O. S. Galinina ◽  
S. D. Andreev ◽  
A. M. Tyurlikov
Keyword(s):  
Success Probability ◽  
Random Access ◽  
Time Interval ◽  
Short Time Interval ◽  
Control Mechanisms ◽  
Network Access ◽  
Smart Meters ◽  
Machine To Machine ◽  
Machine To Machine Communication ◽  
Machine Communication

Introduction: Machine-to-machine communication assumes data transmission from various wireless devices and attracts attention of cellular operators. In this regard, it is crucial to recognize and control overload situations when a large number of such devices access the network over a short time interval.Purpose:Analysis of the radio network overload at the initial network entry stage in a machine-to-machine communication system.Results: A system is considered that features multiple smart meters, which may report alarms and autonomously collect energy consumption information. An analytical approach is proposed to study the operation of a large number of devices in such a system as well as model the settings of the random-access protocol in a cellular network and overload control mechanisms with respect to the access success probability, network access latency, and device power consumption. A comparison between the obtained analytical results and simulation data is also offered. 

scholarly journals Lie-Algebraic Approach for Pricing Zero-Coupon Bonds in Single-Factor Interest Rate Models

2013 ◽  
Vol 2013 ◽  
pp. 1-9 ◽  
Author(s):  
C. F. Lo
Keyword(s):  
Interest Rate ◽  
Algebraic Approach ◽  
Dynamical Symmetry ◽  
Bond Pricing ◽  
Model Parameters ◽  
Time Varying ◽  
Single Factor ◽  
Bond Price ◽  
Interest Rate Models ◽  
Root Model

The Lie-algebraic approach has been applied to solve the bond pricing problem in single-factor interest rate models. Four of the popular single-factor models, namely, the Vasicek model, Cox-Ingersoll-Ross model, double square-root model, and Ahn-Gao model, are investigated. By exploiting the dynamical symmetry of their bond pricing equations, analytical closed-form pricing formulae can be derived in a straightfoward manner. Time-varying model parameters could also be incorporated into the derivation of the bond price formulae, and this has the added advantage of allowing yield curves to be fitted. Furthermore, the Lie-algebraic approach can be easily extended to formulate new analytically tractable single-factor interest rate models.

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