• 제어로봇시스템학회:학술대회논문집
• /
• 2004.08a
• /
• pp.552-557
• /
• 2004

This paper presents a disturbance observer based on an $H_{\infty}$ controller synthesis for the trajectory control of a hydraulic excavator. Compared to conventional robot manipulators driven by electrical motors, the hydraulic excavator has more nonlinear and coupled dynamics. In particular, the interactions between an excavation tool and the materials being excavated are unstructured and complex. In addition, its operating modes depend on working conditions, which make it difficult to not only derive the exact mathematical model but also design a controller systematically. In this study, the approximated linear model obtained through off-line system identification is used as nominal plant model for a disturbance observer. A disturbance observer based tracking controller which considers the effect of disturbance and model uncertainty is synthesized in $H_{\infty}$ frameworks. Simulation results are used to demonstrate the applicability of the proposed control scheme.

• Proceedings of the Korea Association of Information Systems Conference
• /
• 1996.11a
• /
• pp.217-227
• /
• 1996

The new field of learning control develops controllers that learn to improve their performance at executing a given task, based on experience performin this specific task. In a previous work［6］, the authors presented a theory of indirect learning control based on use of indirect adaptive control concepts employing simultaneous identification ad control. This paper develops improved indirect learning control algorithms, and studies the use of such controllers in decentralized systems. The original motivation of the learning control field was learning in robots doing repetitive tasks such as on an assembly line. This paper starts with decentralized discrete time systems, and progresses to the robot application, modeling the robot as a time varying linear system in the neighborhood of the nominal trajectory, and using the usual robot controllers that are decentralized, treating each link as if it is independent of any coupling with other links. The basic result of the paper is to show that stability of the indirect learning controllers for all subsystems when the coupling between subsystems is turned off, assures convergence to zero tracking error of the decentralized indirect learning control of the coupled system, provided that the sample time in the digital learning controller is sufficiently short.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
• /
• 2004.04a
• /
• pp.49-54
• /
• 2004

Ubiquitous computing support to use various informations through any machine which can connect the computer in any where and any time. Recently barcode and RFID which is improved business model to store large scale information and certify security in on- and off-line internet technology is applied the credit curd and payment service and so on However this technology has serious problem that RFID In this paper, we investigate method used example of 2D barcode and RFID and compare and analysis characteristics of recent technology to solve former problem in Ubiquitous environment.

• Proceedings of the Korea Society for Industrial Systems Conference
• /
• 1996.10a
• /
• pp.217-227
• /
• 1996

The new filed of learning control develops controllers that learn to improve their performance at executing a given task , based on experience performing this specific task. In a previous work[6], authors presented a theory of indirect learning control based on use of indirect adaptive control concepts employing simultaneous identification and control. This paper develops improved indirect learning control algorithms, and studies the use of such controller indecentralized systems. The original motivation of the learning control field was learning in robots doing repetitive tasks such as on an asssembly line. This paper starts with decentralized discrete time systems. and progresses to the robot application, modeling the robot as a time varying linear system in the neighborhood of the nominal trajectory, and using the usual robot controllers that are decentralized, treating each link as if it is independent of any coupling with other links. The resultof the paper is to show that stability of the indirect learning controllers for all subsystems when the coupling between subsystems is turned off, assures convergence to zero tracking error of the decentralized indirect learning control of the coupled system, provided that the sample tie in the digital learning controller is sufficiently short.

• Journal of the Korean Chemical Society
• /
• v.41 no.10
• /
• pp.524-534
• /
• 1997

Analysis of additives in cured rubber is often a difficult task for analytical chemists because of a wide variety of complex components. Conventional analyses of additives and rubbers have been done in multistep, off-line processes with large sample size and extensive sample preparations. The coumarone-indene resin, resorcinol-formaldehyde resin, and prevulcanization inhibitor have been characterized by their pyrolysis pathways and mass spectra of characteristic pyrolyzates. Pyrolysis Gas Chromatography/Mass Spectrometry (Py-GC/MS) was used in the identification of additives without any sample pretreatment. This result shows that several organic additives in cured rubber can be directly analyzed.

• Korean Journal of Environmental Agriculture
• /
• v.25 no.4
• /
• pp.371-381
• /
• 2006

New proteomic techniques have been pioneered extensively in recent years, enabling the high-throughput and systematic analyses of cellular proteins in combination with bioinformatic tools. Furthermore, the development of such novel proteomic techniques facilitates the elucidation of the functions of proteins under stress or disease conditions, resulting in the discovery of biomarkers for responses to environmental stimuli. The ultimate objective of proteomics is targeted toward the entire proteome of life, subcellular localization biochemical activities, and the regulation thereof. Comprehensive analysis strategies of proteomics can be classified into three categories: (i) protein separation via 2-dimensional gel electrophoresis (2-DE) or liquid chromatography (LC), (ii) protein identification via either Edman sequencing or mass spectrometry (MS), and (iii) proteome quantitation. Currently, MS-based proteomics techniques have shifted from qualitative proteome analysis via 2-DE or 2D-LC coupled with off-line matrix assisted laser desorption ionization (MALDI) and on-line electrospray ionization (ESI) MS, respectively, toward quantitative proteome analysis. In vitro quantitative proteomic techniques include differential gel electrophoresis with fluorescence dyes. protein-labeling tagging with isotope-coded affinity tags, and peptide-labeling tagging with isobaric tags for relative and absolute quantitation. In addition, stable isotope-labeled amino acids can be in vivo labeled into live culture cells via metabolic incorporation. MS-based proteomics techniques extend to the detection of the phosphopeptide mapping of biologically crucial proteins, which ale associated with post-translational modification. These complementary proteomic techniques contribute to our current understanding of the manner in which life responds to differing environment.

• Journal of Plant Biotechnology
• /
• v.37 no.2
• /
• pp.196-204
• /
• 2010

With the completion of genome sequencing of several organisms, attention has been focused to determine the function and functional network of proteins by proteome analysis. The recent techniques of proteomics have been advanced quickly so that the high-throughput and systematic analyses of cellular proteins are enabled in combination with bioinformatics tools. Furthermore, the development of proteomic techniques helps to elucidate the functions of proteins under stress or diseased condition, resulting in the discovery of biomarkers responsible for the biological stimuli. Ultimate goal of proteomics orients toward the entire proteome of life, subcellular localization, biochemical activities, and their regulation. Comprehensive analysis strategies of proteomics can be classified as three categories: (i) protein separation by 2-dimensional gel electrophoresis (2-DE) or liquid chromatography (LC), (ii) protein identification by either Edman sequencing or mass spectrometry (MS), and (iii) quanitation of proteome. Currently MS-based proteomics turns shiftly from qualitative proteome analysis by 2-DE or 2D-LC coupled with off-line matrix assisted laser desorption ionization (MALDI) and on-line electrospray ionization (ESI) MS, respectively, to quantitative proteome analysis. Some new techniques which include top-down mass spectrometry and tandem affinity purification have emerged. The in vitro quantitative proteomic techniques include differential gel electrophoresis with fluorescence dyes, protein-labeling tagging with isotope-coded affinity tag, and peptide-labeling tagging with isobaric tags for relative and absolute quantitation. In addition, stable isotope labeled amino acid can be in vivo labeled into live culture cells through metabolic incorporation. MS-based proteomics extends to detect the phosphopeptide mapping of biologically crucial protein known as one of post-translational modification. These complementary proteomic techniques contribute to not only the understanding of basic biological function but also the application to the applied sciences for industry.

• 제어로봇시스템학회:학술대회논문집
• /
• 2003.10a
• /
• pp.1480-1484
• /
• 2003

This paper presents the design and development of network for housing estate security system. The system can cover up to 961 houses which can be up to 1,200 meters long transfer rate of 9,600 bps. This system uses checking and warning the abnormal situation. More over this system has ability to control switch on/off the electrical equipment in the house via AC line control system. The system consists of 4 parts. The first part is a security system of each house using MCS-51 microcontroller as a central processing unit scan 32 sensors and control 8 appliances and send alarm. The MCS-51 microcontroller received control signal via telephone used DTMF circuit. The second part is distributed two levels master/slave network implementing after RS-485 serial communication standard. The protocol its base on the OSI (Open Systems Interconnection) 7 layers protocol model design focus on speed, reliability and security of data that is transferred. The network security using encrypt by DES algorithm, message sequence, time stamp checking and authentication system when user to access and when connect new device to this system. Flow control in system is Poll/Select and Stop-and-Wait method. The third part is central server that using microcomputer which its main function are storing event data into database and can check history event. The final part is internet system which users can access their own homes via the Internet. This web service is based on a combination of SOAP, HTTP and TCP/IP protocols. Messages are exchanged using XML format [6]. In order to save the number of IP address, the system uses 1 IP address for the whole village in which all homes and appliance in this village are addressed using internal identification numbers. This proposed system gives the data transfer accuracy over 99.8% and maximum polling time is 1,120 ms.

• Korean Chemical Engineering Research
• /
• v.46 no.6
• /
• pp.1043-1051
• /
• 2008

In polyolefin processes melt index (MI) is the most important controlled variable indicating product quality. Because of the difficulty in the on-line measurement of MI, a lot of MI estimation and correlation methods have been proposed. In this work a new dynamic MI estimation scheme is developed based on system identification techniques. The empirical MI estimation equation proposed in the present study is derived from the $1^{st}$-order dynamic models. Effectiveness of the present estimation scheme was illustrated by numerical simulations based on plant operation data including grade change operations in high density polyethylene (HDPE) processes. From the comparisons with other estimation methods it was found that the proposed estimation scheme showed better performance in MI predictions. Using the model predictive control method based on the present dynamic MI estimation model, MI values are estimated and compared with those of MI setpoints. From the numerical simulation of the proposed control system, it was found that significant reduction of transition time and the amount of off-spec during grade changes were achieved.

• Journal of the Institute of Convergence Signal Processing
• /
• v.2 no.1
• /
• pp.44-52
• /
• 2001

This paper describes an off-line method for recognizing totally unconstrained handwritten digits using modified chaotic neural networks(MCNN). The chaotic neural networks(CNN) is modified to be a useful network for solving complex pattern problems by enforcing dynamic characteristics and learning process. Since the MCNN has the characteristics of highly nonlinear dynamics in structure and neuron itself, it can be an appropriate network for the robust classification of complex handwritten digits. Digit identification starts with extraction of features from the raw digit images and then recognizes digits using the MCNN based classifier. The performance of the MCNN classifier is evaluated on the numeral database of Concordia University, Montreal, Canada. For the relative comparison of recognition performance, the MCNN classifier is compared with the recurrent neural networks(RNN) classifier. Experimental results show that the classification rate is 98.0%. It indicates that the MCNN classifier outperforms the RNN classifier as well as other classifiers that have been reported on the same database.