• Journal of Institute of Control, Robotics and Systems
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• v.14 no.1
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• pp.42-48
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• 2008

This paper presents an observer design method for a special class of multi input multi output(MIMO) nonlinear systems. First, we characterize the class of MIMO nonlinear systems with a block triangular structure. Also, the observability matrices for SISO nonlinear systems are extended to MIMO systems. By using the generalized observability matrices, it is shown that under the boundedness conditions of system state and input, the proposed observer guarantees the local exponential stability of error dynamics. Finally, its application to induction motor is given to verify the proposed method.

• Journal of the Korean Institute of Telematics and Electronics
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• v.26 no.9
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• pp.1322-1331
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• 1989

This paper proposes a new adaptation algorithm with which a model reference adaptive control can give a local boundedness of the tracking error applied to a continuous-time linear time-invariant single-input single-output plant whose reduced-order model is of relative degree 1 and whose unmodeled dynamics may be represented in a sigular perturbation form. With the addition of an offset term and an extra adaptation structure, this algorithm is shown to have a robustness property in the sense that this gives zero residual tracking errors when the unmodeled dynamics are disappeared.

• International Journal of Control, Automation, and Systems
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• v.6 no.4
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• pp.544-550
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• 2008

In this paper, an efficient positioning algorithm is proposed for a local positioning system using ultrasound and RF in WSN. The proposed positioning algorithm is the modified Savarese method where measurement noise characteristics are included as a weighting. Furthermore the ill-conditioned and the singularity problem occurred when all beacons are installed at the same height are removed. And the method is applicable to 2D positioning with 2 beacons only. The experiments with implemented system show the accurate seamless positioning less than 2cm error both static and dynamic experiments while the original Savarese method can not provide positions.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.6
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• pp.477-482
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• 2016

This paper presents a simple approximation-based design approach for consensus tracking of heterogeneous second-order nonlinear systems under a directed network. All nonlinearities of followers are assumed to be unknown and non-identical. In the controller design procedure, graph-independent error surfaces are used and an unimplementable intermediate controller for each follower is designed at the first design step. Then, by adding and subtracting a graph-based term at the second step, the actual controller for each follower is designed by using one neural network employed to estimate a lumped and distributed nonlinearity. Therefore, the proposed local controller for each follower has a simpler structure than existing approximation-based consensus tracking controllers for multi-agent systems with unmatched nonlinearities.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.9
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• pp.839-845
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• 2013

A CSTR (Continuous Stirred Tank Reactor) is a highly nonlinear process with varying parameters during operation. Therefore, tuning of the controller and determining the transition policy of controller parameters are required to guarantee the best performance of the CSTR for overall operating regions. In this paper, a methodology employing the 2DOF (Two-Degree-of-Freedom) PID controller, the anti-windup technique and a fuzzy gain scheduler is presented for the temperature control of the CSTR. First, both a local model and an EA (Evolutionary Algorithm) are used to tune the optimal controller parameters at each operating region by minimizing the IAE (Integral of Absolute Error). Then, a set of controller parameters are expressed as functions of the gain scheduling variable. Those functions are implemented using a set of "if-then" fuzzy rules, which is of Sugeno's form. Simulation works for reference tracking, disturbance rejecting and noise rejecting performances show the feasibility of using the proposed method.

• Proceedings of the Korea Electromagnetic Engineering Society Conference
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• 2003.11a
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• pp.219-223
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• 2003

This paper describes an estimation of DOA(Direction Of Arrival) measurement system using DBF receiver with linear array antenna. This DBF receiver is composed of resistive FET mixer using low IF mettled. A radio frequency(RF), a local oscillator(LO) and ail intermediate frequency(IF) considered in this research are 2.09 GHz, 2.08 GHz and 10 MHz, respectively. This receiver is composed of a band-pass filter, a low-pass filter, a DC bias circuit. DOA measurement system is consist of linear array antenna, DBF receiver, AD control box and computer in the anechoic chamber. Receiving antenna is 4-array monopole antenna and DBF receiver is 4-Ch resistive FET mixer without amplifier. DOA algorithm is implemented using MUSIC algorithm with high resolution. We show that the results of DOA is $-30^{\circ},\;0^{\circ}$ and $60^{\circ}$, respectively. And we know that DOA estimation error occur by antenna radiation pattern and fabrication error of antenna array.

• Journal of Electrical Engineering and information Science
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• v.3 no.2
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• pp.211-221
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• 1998

It is becoming apparent that stereo matching algorithms need much information from high level cognitive processes. Otherwise, conventional algorithms based on bottom-up control alone are susceptible to local minima. We introduce a system that consists of two levels. A lower level, using a usual matching method, is based upon the local neighborhood and a second level, that can integrate the partial information, is aimed at contextual matching. Conceptually, the introduction of bottom-up and top-down feedback loop to the usual matching algorithm improves the overall performance. For this purpose, we model the image attributes using a Markov random field (MRF) and thereupon derive a maximum a posteriori (MAP) estimate. The energy equation, corresponding to the estimate, efficiently represents the natural constraints such as occlusion and the partial informations from the other levels. In addition to recognition, we derive a training method that can determine the system informations from the other levels. In addition to recognition, we derive a training method that can determine the system parameters automatically. As an experiment, we test the algorithms using random dot stereograms (RDS) as well as natural scenes. It is proven that the overall recognition error is drastically reduced by the introduction of contextual matching.

• Bulletin of the Korean Chemical Society
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• v.28 no.3
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• pp.397-402
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• 2007

Restenosis after percutaneous coronary intervention (PCI) continues to be a serious problem in clinical cardiology. To solve this problem, drug eluting stents (DES) with antiproliferative agents have been developed. Variable local drug delivery systems in the context of stenting require the development of stent manufacture, drug pharmacology and coating technology. We have worked on a system that integrates electrophoretic deposition (EPD) technology with the polymeric nanoparticles in DES for local drug delivery and a controlled release system. The surface morphology and drug loading amount of DES by EPD have been investigated under different operational conditions, such as operation time, voltage and the composition of media. We prepared poly-D,L-lactide-co-glycolic acid (PLGA) nanoparticles embedded with curcumin, which was done by a modified spontaneous emulsification method and used polyacrylic acid (PAA) as a surfactant because its carboxylic group contribute negative charge to the surface of CPNPs (?53.5 ± 5.8 mV). In the process of ‘trial and error' endeavors, we found that it is easy to control the drug loading amount deposited onto the stent while keeping uniform surface morphology. Accordingly, stent coating by EPD has a wide application to the modification of DES using various kinds of nanoparticles and drugs.

• Journal of Institute of Control, Robotics and Systems
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• v.3 no.2
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• pp.179-186
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• 1997

In this paper we suggest a development of surface defect inspection algorithms for cold mill strip. The defects which exist in a surface of cold mill strip have a scattering or singular distribution. This paper consists of preprocessing, feature extraction and defect classification. By preprocessing, the binarized defect image is achieved. In this procedure, Top-hit transform, adaptive thresholding, thinning and noise rejection are used. Especially, Top-hit transform using local min/max operation diminishes the effect of bad lighting. In feature extraction, geometric, moment and co-occurrence matrix features are calculated. For the defect classification, multilayer neural network is used. The proposed algorithm showed 15% error rate.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.1
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• pp.200-206
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• 2016

It is necessary to develop a real-time monitoring system for electric facilities, operating and managing system for the accident prevention of electrical demand facilities anytime, anywhere. In this paper, we propose the implementation of distributing board monitoring system based on Internet of Things(IoT). The proposed system is installed in existing distributing board that it can transmit status information of distributing board and control information through the cloud server and the wireless local area network. The distributing board monitoring system can monitor and control the condition of distributing board by system administrator. The results show that the margin of error was ${\pm}5%$ in performance evaluation.