• Smart Structures and Systems
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• v.6 no.1
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• pp.1-16
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• 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 Journal of Industrial Distribution & Business
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• v.11 no.4
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• pp.7-18
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• 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.

• Journal of Korea Multimedia Society
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• v.15 no.11
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• pp.1391-1398
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• 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.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.12
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• pp.1220-1225
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• 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.

• Journal of Power Electronics
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• v.17 no.5
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• pp.1211-1222
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• 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.

• Journal of Information Technology Applications and Management
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• v.24 no.4
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• pp.93-115
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• 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.

• Proceedings of the KIPE Conference
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• 2018.07a
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• pp.237-239
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• 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.

• Journal of Electrical Engineering and Technology
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• v.9 no.5
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• pp.1454-1470
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• 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.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.27 no.3
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• pp.65-78
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• 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.

• Journal of Information Processing Systems
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• v.13 no.4
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• pp.951-969
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• 2017

In this paper, we newly propose a traffic information service model that collects traffic information sensed by an individual vehicle in real time by using a smart device, and which enables drivers to share traffic information on all roads in real time using an application installed on a smart device. In particular, when the driver requests traffic information for a specific area, the proposed driver-personalized service model provides him/her with traffic information on the driving directions in advance by predicting the driving directions of the vehicle based on the learning of the driving records of each driver. To do this, we propose a traffic information management model to process and manage in real time a large amount of online-generated traffic information and traffic information requests generated by each vehicle. We also propose a road node-based indexing technique to efficiently store and manage location-based traffic information provided by each vehicle. Finally, we propose a driving learning and prediction model based on the hidden Markov model to predict the driving directions of each driver based on the driver's driving records. We analyze the traffic information processing performance of the proposed model and the accuracy of the driving prediction model using traffic information collected from actual driving vehicles for the entire area of Seoul, as well as driving records and experimental data.