• Title/Summary/Keyword: online estimation

Search Result 201, Processing Time 0.028 seconds

Application of recursive SSA as data pre-processing filter for stochastic subspace identification

  • Loh, Chin-Hsiung;Liu, Yi-Cheng
    • Smart Structures and Systems
    • /
    • v.11 no.1
    • /
    • pp.19-34
    • /
    • 2013
  • The objective of this paper is to develop on-line system parameter estimation and damage detection technique from the response measurements through using the Recursive Covariance-Driven Stochastic Subspace identification (RSSI-COV) approach. To reduce the effect of noise on the results of identification, discussion on the pre-processing of data using recursive singular spectrum analysis (rSSA) is presented to remove the noise contaminant measurements so as to enhance the stability of data analysis. Through the application of rSSA-SSI-COV to the vibration measurement of bridge during scouring experiment, the ability of the proposed algorithm was proved to be robust to the noise perturbations and offers a very good online tracking capability. The accuracy and robustness offered by rSSA-SSI-COV provides a key to obtain the evidence of imminent bridge settlement and a very stable modal frequency tracking which makes it possible for early warning. The peak values of the identified $1^{st}$ mode shape slope ratio has shown to be a good indicator for damage location, meanwhile, the drastic movements of the peak of $2^{nd}$ mode slope ratio could be used as another feature to indicate imminent pier settlement.

Design of a smart MEMS accelerometer using nonlinear control principles

  • Hassani, Faezeh Arab;Payam, Amir Farrokh;Fathipour, Morteza
    • Smart Structures and Systems
    • /
    • v.6 no.1
    • /
    • pp.1-16
    • /
    • 2010
  • This paper presents a novel smart MEMS accelerometer which employs a hybrid control algorithm and an estimator. This scheme is realized by adding a sliding-mode controller to a conventional PID closed loop system to achieve higher stability and higher dynamic range and to prevent pull-in phenomena by preventing finger displacement from passing a maximum preset value as well as adding an adaptive nonlinear observer to a conventional PID closed loop system. This estimator is used for online estimation of the parameter variations for MEMS accelerometers and gives the capability of self testing to the system. The analysis of convergence and resolution show that while the proposed control scheme satisfies these criteria it also keeps resolution performance better than what is normally obtained in conventional PID controllers. The performance of the proposed hybrid controller investigated here is validated by computer simulation.

The Impact of Technology Adoption on Organizational Productivity

  • LAKHWANI, Monika;DASTANE, Omkar;SATAR, Nurhizam Safie Mohd;JOHARI, Zainudin
    • The Journal of Industrial Distribution & Business
    • /
    • v.11 no.4
    • /
    • pp.7-18
    • /
    • 2020
  • Purpose: This research investigates the impact of technology adoption on organisation productivity. The framework has three independent variables viz. technological change, information technology (IT) infrastructure, and IT knowledge management and one dependent variable as organisational productivity. Research design, data and methodology: An explanatory research design with a quantitative research method was employed, and data was collected using a self-administered questionnaire using online as well as an offline survey. The sample consisted of 300 IT managers and senior-level executives (production as well as service team) in leading IT companies in Malaysia selected using snowball sampling. Normality and reliability assessment was performed in the first stage utilising SPSS 22, and Confirmatory Factory Analysis (CFA) was performed with maximum likelihood estimation to assess the internal consistency, convergent validity, and discriminant validity. Finally, Structural Equation Model (SEM) and path analysis are conducted using AMOS 22. Results: The research findings demonstrated that technological change and IT infrastructure positively and significantly impact the organisation's productivity while IT knowledge management has significant but negative impact on organizational productivity of IT companies in Malaysia. Conclusion: The research concludes that all three factors plays important role in deciding organizational producvity. Recommendations, implications, limitations and future research avenues are discussed.

Realtime Clock Skew Estimator for Time Synchronization in Wireless Sensor Networks of WUSB and WBAN (무선 센서네트워크에서의 시각동기를 위한 실시간 클럭 스큐 추정)

  • Hur, Kyeong
    • Journal of Korea Multimedia Society
    • /
    • v.15 no.11
    • /
    • pp.1391-1398
    • /
    • 2012
  • Time synchronization is crucial in wireless sensor networks such as Wireless USB and WBAN for diverse purposes from the MAC to the application layer. This paper proposes online clock skew estimators to achieve energy-efficient time synchronization for wireless sensor networks. By using recursive least squares estimators, we not only reduce the amount of data which should be stored locally in a table at each sensor node, but also allow offset and skew compensations to be processed simultaneously. Our skew estimators can be easily integrated with traditional offset compensation schemes. The results of simulation and experiment show that the accuracy of time synchronization can be greatly improved through our skew compensation algorithm.

Intelligent IIR Filter based Multiple-Channel ANC Systems (지능형 IIR 필터 기반 다중 채널 ANC 시스템)

  • Cho, Hyun-Cheol;Yeo, Dae-Yeon;Lee, Young-Jin;Lee, Kwon-Soon
    • Journal of Institute of Control, Robotics and Systems
    • /
    • v.16 no.12
    • /
    • pp.1220-1225
    • /
    • 2010
  • This paper proposes a novel active noise control (ANC) approach that uses an IIR filter and neural network techniques to effectively reduce interior noise. We construct a multiple-channel IIR filter module which is a linearly augmented framework with a generic IIR model to generate a primary control signal. A three-layer perceptron neural network is employed for establishing a secondary-path model to represent air channels among noise fields. Since the IIR module and neural network are connected in series, the output of an IIR filter is transferred forward to the neural model to generate a final ANC signal. A gradient descent optimization based learning algorithm is analytically derived for the optimal selection of the ANC parameter vectors. Moreover, re-estimation of partial parameter vectors in the ANC system is proposed for online learning. Lastly, we present the results of a numerical study to test our ANC methodology with realistic interior noise measurement obtained from Korean railway trains.

Low Parameter Sensitivity Deadbeat Direct Torque Control for Surface Mounted Permanent Magnet Synchronous Motors

  • Zhang, Xiao-Guang;Wang, Ke-Qin;Hou, Ben-Shuai
    • Journal of Power Electronics
    • /
    • v.17 no.5
    • /
    • pp.1211-1222
    • /
    • 2017
  • In order to decrease the parameter sensitivity of deadbeat direct torque control (DB-DTC), an improved deadbeat direct torque control method for surface mounted permanent-magnet synchronous motor (SPMSM) drives is proposed. First, the track errors of the stator flux and torque that are caused by model parameter mismatch are analyzed. Then a sliding mode observer is designed, which is able to predict the d-q axis currents of the next control period for one-step delay compensation, and to simultaneously estimate the model parameter disturbance. The estimated disturbance of this observer is used to estimate the stator resistance offline. Then the estimated resistance is required to update the designed sliding-mode observer, which can be used to estimate the inductance and permanent-magnetic flux linkage online. In addition, the flux and torque estimation of the next control period, which is unaffected by the model parameter disturbance, is achieved by using predictive d-q axis currents and estimated parameters. Hence, a low parameter sensitivity DB-DTC method is developed. Simulation and experimental results show the validity of the proposed direct control method.

Using Choice-Based Conjoint Analysis to Determine Smartphone Choice - a Student's Perspective

  • Baganzi, Ronald;Shin, Geon-Cheol;Wu, Shali
    • Journal of Information Technology Applications and Management
    • /
    • v.24 no.4
    • /
    • pp.93-115
    • /
    • 2017
  • The ability of smartphones to facilitate various services like mobile banking, e-commerce and mobile payments has made them part of consumers' lives. Conjoint analysis (CA) is a marketing research approach used to assess how consumers' preferences for products or services develop. The potential applications of CA are numerous in consumer electronics, banking and insurance services, job selection and workplace loyalty, consumer packaged goods, and travel and tourism. Choice-Based Conjoint (CBC) analysis is the most commonly used CA approach in marketing research. The purpose of this study is to utilise CBC analysis to investigate the relative importance of smartphone attributes that influence consumer smartphone preference. An experiment was designed using Sawtooth CBC Software. 326 students attempted the online survey. Utility values were derived by Hierarchical Bayes (HB) estimation and used to explain consumers' smartphone preferences. All the six attributes used for the study were found to significantly influence smartphone preference. Smartphone brand was the most important, followed by the price, camera, RAM, battery life, and storage. This study is one of the first to use Sawtooth CBC analysis to assess consumer smartphone preference based on the six attributes. We provide implications for the development of new smartphones based on attributes.

Online Identification of Li-ion Battery's Internal Resistance based on a Recursive Least Squares Method to Prevent Overvoltage/Undervoltage (리튬이온 배터리의 과전압/저전압을 막기 위한 회기 최소 자승법 기반의 실시간 내부 저항 추정방법)

  • Kim, Woo-Yong;Lee, Pyeong-Yeon;Kim, Jonghoon;Kim, Kyung-Soo
    • Proceedings of the KIPE Conference
    • /
    • 2018.07a
    • /
    • pp.237-239
    • /
    • 2018
  • This paper proposes an on-line estimation algorithm of internal resistance of Li-ion battery based on the recursive least squares method to prevent the overvoltage and undervoltage casing degradation of life cycle of battery. An equivalent circuit model with single time constant is adopted, and under assumptions that the terminal voltage, current and SOC are measured accurately, the discrete time based nonlinear equation of the model can be converted to the linear equation which can be applied to recursive least squares method. Since the coefficients of the discrete time linear equation can be expressed by the parameters of the equivalent circuit model, it is shown that an internal resistance (Ri) can be estimated in real time using the least square method.

  • PDF

A Simple Power Management Scheme with Enhanced Stability for a Solar PV/Wind/Fuel Cell Fed Standalone Hybrid Power Supply using Embedded and Neural Network Controller

  • Thangavel, S.;Saravanan, S.
    • Journal of Electrical Engineering and Technology
    • /
    • v.9 no.5
    • /
    • pp.1454-1470
    • /
    • 2014
  • This paper propose a new power conditioner topology with intelligent power management controller that integrates multiple renewable energy sources such as solar energy, wind energy and fuel cell energy with battery backup to make best use of their operating characteristics and obtain better reliability than that could be obtained by single renewable energy based power supply. The proposed embedded controller is programmed for maintaining a constant voltage at PCC, maximum power point tracking for solar PV panel and WTG and power flow control by regulating the reference currents of the controller on instantaneous basis based on the power delivered by the sources and load demand. Instantaneous variation in reference currents of the controller enhances the controller response as it accommodates the effect of continuously varying solar insolation and wind speed in the power management. The power conditioner uses a battery bank with embedded controller based online SOC estimation and battery charging system to suitably sink or source the input power based on the load demand. The simulation results of the proposed power management system for a standalone solar/WTG/fuel cell fed hybrid power supply with real time solar radiation and wind velocity data collected from solar centre, KEC for a sporadically varying load demand is presented in this paper and the results are encouraging in reliability and stability perspective.

A Study on the Integrated Simulation and Condition Monitoring Scheme for a PMSG-Based Variable Speed Grid-Connected Wind Turbine System under Fault Conditions (PMSG 적용 가변속 계통연계형 풍력발전 시스템의 통합 시뮬레이션 및 스위치 개방고장 진단기법 연구)

  • Kim, Kyeong-Hwa;Song, Hwa-Chang;Choi, Byoung-Wook
    • Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
    • /
    • v.27 no.3
    • /
    • pp.65-78
    • /
    • 2013
  • To analyze influences under open fault conditions in switching devices, an integrated simulation and condition monitoring scheme for a permanent magnet synchronous generator (PMSG) based variable speed grid-connected wind turbine system are presented. Among various faults in power electronics components, the open fault in switching devices may arise when the switches are destructed by an accidental over current, or a fuse for short protection is blown out. Under such a faulty condition, the grid-side inverter as well as the generator-side converter does not operate normally, producing an increase of current harmonics, and a reduction in output and efficiency. As an effective way for a condition monitoring of generation system by online basis without requiring any diagnostic apparatus, the estimation schemes for generated voltage, flux linkage, and stator resistance are proposed and the validity of the proposed scheme is proved through comparative simulations.