• Journal of Institute of Control, Robotics and Systems
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• v.3 no.5
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• pp.526-531
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• 1997

To control nonlinear chemical processes, a new neural linearizing control scheme is proposed. This is a hybrid of a radial basis function(RBF) network and a linear controller, thus the control action applied to the process is the sum of both control actions. Firstly, to train the RBF newtork a linear reference model is determined by analyzing the past operating data of the process. Then, the training of the RBF newtork is iteratively performed to minimize the difference between outputs of the process and the linear reference model. As a result, the apparent dynamics of the process added by the RBF newtork becomes similar to that of the linear reference model. After training, the original nonlinear control problem changes to a linear one, and the closed-loop control performance is improved by using the optimum tuning parameters of the linear controller for the linear dynamics. The proposed control scheme performs control and training simultaneously, and shows a good control performance for nonlinear chemical processes.

• ETRI Journal
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• v.39 no.1
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• pp.62-68
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• 2017

In this paper, we present the design and characterization analysis of a cascode GaN field-effect transistor (FET) for switching power conversion systems. To enable normally-off operation, a cascode GaN FET employs a low breakdown voltage (BV) enhancement-mode Si metal-oxide-semiconductor FET and a high-BV depletion-mode (D-mode) GaN FET. This paper demonstrates a normally-on D-mode GaN FET with high power density and high switching frequency, and presents a theoretical analysis of a hybrid cascode GaN FET design. A TO-254 packaged FET provides a drain current of 6.04 A at a drain voltage of 2 V, a BV of 520 V at a drain leakage current of $250{\mu}A$, and an on-resistance of $331m{\Omega}$. Finally, a boost converter is used to evaluate the performance of the cascode GaN FET in power conversion applications.

• Journal of Korean Institute of Industrial Engineers
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• v.33 no.2
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• pp.201-212
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• 2007

Genetic algorithms (GAs) are very useful methods for global search and have been applied to various optimization problems. They have two kinds of important search mechanisms, crossover and mutation. Because the performance of GAs depends on these operators, a large number of operators have been developed for improving the performance of GAs. Especially, many researchers have been more interested in a crossover operator than a mutation operator. The reason is that a crossover operator is a main search operator in GAs and it has a more effect on the search performance. So, we also focus on a crossover operator. In this paper we first investigate the drawback of various crossovers, especially subtour-based crossovers and then introduce a new crossover operator to avoid such drawback and to increase efficiency. Also we compare it with several crossover operators for symmetric traveling salesman problem (STSP) for showing the performance of the proposed crossover. Finally, we introduce an efficient simple hybrid genetic algorithm using the proposed operator and then the quality and efficiency of the obtained results are discussed.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38A no.3
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• pp.289-293
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• 2013

In the noncoherent methods for UWB-IR (ultra-wideband impulse radio), block coded modulation (BCM) is better than the transmitted reference (TR) systems in terms of the energy efficiency and data rate. However, even BCM suffers from the performance degradation in the presence of strong inter-frame interference and inter symbol interference. We propose the transmitted reference based on the BCM (TR-BCM) which is the hybrid system of TR and BCM. Performance evaluation shows that the performance of TR-BCM is better than that of BCM in the high SNR range.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.372-372
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• 2000

In this paper, we propose Neuro Fuzzy Polynomial Networks(NFPN) based on Polynomial Neural Network(PNN) and Neuro-Fuzzy(NF) for model identification of complex and nonlinear systems. The proposed NFPN is generated from the mutually combined structure of both NF and PNN. The one and the other are considered as the premise part and consequence part of NFPN structure respectively. As the premise part of NFPN, NF uses both the simplified fuzzy inference as fuzzy inference method and error back-propagation algorithm as learning rule. The parameters such as parameters of membership functions, learning rates and momentum coefficients are adjusted using genetic algorithms. As the consequence part of NFPN, PNN is based on Group Method of Data Handling(GMDH) method and its structure is similar to Neural Networks. But the structure of PNN is not fixed like in conventional Neural Networks and self-organizing networks that can be generated. NFPN is available effectively for multi-input variables and high-order polynomial according to the combination of NF with PNN. Accordingly it is possible to consider the nonlinearity characteristics of process and to get better output performance with superb predictive ability. In order to evaluate the performance of proposed models, we use the nonlinear function. The results show that the proposed FPNN can produce the model with higher accuracy and more robustness than any other method presented previously.

• Journal of the Korean Society of Visualization
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• v.11 no.1
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• pp.41-47
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• 2013

Turbulence properties of a cylinder wake (d=10 mm) have been investigated with a new volume PTV algorithm. The measurement system consists of two-high-cameras(1 $k{\times}1$ k), a Nd-Yag laser and a host computer. A fitness function representing three-dimensional coherency has been adopted to sort out spurious vectors. A hybrid fitness function representing the relations between the fitness and the three-dimensional shortest distances constructed by the two collinears of the two cameras has been also adopted. The constructed algorithm has been employed for the measurements of the cylinder wakes. The Reynolds numbers tested in this paper are 360, 540, 720, 900, 1080 and 1260. More than 10,000 instantaneous 3D vectors have been obtained by the constructed system. The volumetric distributions of the turbulence intensities (for u', v', w') indicate that clearly different patterns for all Reynolds numbers and imply that a regular pattern (like a similarity rule) for the turbulent properties exists.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.7
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• pp.3192-3212
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• 2016

With the advent and popularity of e-commerce, an increasing number of consumers prefer to order tourism products online. A recommender system can help these users contend with information overload; however, such a system is affected by the cold start problem. Online tourism destination searching is a more difficult task than others on account of its more restrictive factors. In this paper, we therefore propose a tourism destination recommender system that employs opinion-mining technology to refine user preferences and item opinion reputations. These elements are then fused into a hybrid collaborative filtering method by combining user- and item-based collaborative filtering approaches. Meanwhile, we embed an artificial interactive module in our recommender system to alleviate the cold start problem. Compared with several well-known cold start recommendation approaches, our method provides improved recommendation accuracy and quality. A series of experimental evaluations using a publicly available dataset demonstrate that the proposed recommender system outperforms existing recommender systems in addressing the cold start problem.

• Journal of Communications and Networks
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• v.14 no.6
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• pp.629-639
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• 2012

A challenge faced by smart grid systems is providing highly reliable transmissions to better serve different types of electrical applications and improve the energy efficiency of the system. Although wireless networking technologies can provide high-speed and cost-effective solutions, their performance may be impaired by various factors that affect the reliability of smart grid networks. Here, we first suggest the use of IEEE 802.11s-based wireless LAN mesh networks as high-speed wireless backbone networks for smart grid infrastructure to provide high scalability and flexibility while ensuring low installation and management costs. Thereafter, we analyze some vital problems of the IEEE 802.11s default routing protocol (named hybrid wireless mesh protocol; HWMP) from the perspective of transfer reliability, and propose appropriate solutions with a new routing method called HWMP-reliability enhancement to improve the routing reliability of 802.11s-based smart grid mesh networking. A simulation study using ns-3 was conducted to demonstrate the superiority of the proposed schemes.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.26 no.5
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• pp.212-217
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• 2014

Recently, the use of renewable energy has been increased due to growing concern on the energy-saving at buildings and the reduction of $CO_2$ emission. In the field of architecture, to reduce the energy consumption of heating, cooling and hot water supply, heat pump systems with renewable energy has been developed and used in various applications. However, there have been many of researches on the large-scale commercial heat pump systems, but the research and the field application of a compact heat pump system is rare. Therefore, in order to develop the compact heat pump for the small-scale residential building, this study conducted the performance test and feasibility study for a hybrid heat pump using the heat source of air, solar and ground. In the results of experiments through a trial product, the average COP of cooling mode with ground heat source was 4.75, and it of heating mode was 4.03. Furthermore, the average COP of cooling mode with air heat source was 2.60, and it of heating mode was 2.92. Finally, payback period of the system was calculated as 9.2 years.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.2
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• pp.141-147
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• 2008

In this paper, we present one approach to achieve safe navigation in indoor dynamic environment. So far, there have been various useful collision avoidance algorithms and path planning schemes. However, those algorithms have a fundamental limitation that the robot can avoid only "visible" obstacles. In real environment, it is not possible to detect all the dynamic obstacles around the robot. There exist a lot of "occluded" regions due to the limitation of field of view. In order to avoid possible collisions, it is desirable to consider visibility information. Then, a robot can reduce the speed or modify a path. This paper proposes a safe navigation scheme to reduce the risk of collision due to unexpected dynamic obstacles. The robot's motion is controlled according to a hybrid control scheme. The possibility of collision is dually reflected to a path planning and a speed control. The proposed scheme clearly indicates the structural procedure on how to model and to exploit the risk of navigation. The proposed scheme is experimentally tested in a real office building. The presented result shows that the robot moves along the safe path to obtain sufficient field of view, while appropriate speed control is carried out.