• Journal of the Korea Society for Simulation
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• v.22 no.1
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• pp.21-30
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• 2013

A hybrid system is a combination of sub systems which have different types of state and time: a typical example is a combination of discrete event and continuous systems. A HDEVS(Hybrid DEVS) formalism was proposed for modeling and analyzing a hybrid system. The HDEVS formalism allows modelers to construct a hierarchical and modular model based on the mathematical set theory. Because the HDEVS formalism was applied to the distributed and interoperated simulators, modelers should make several heterogenous models dividing a target system. Hence, this paper proposes an extended hybrid coupled model of HDEVS formalism and an integrated hybrid modeling methodology in contrast to the existing simulation framework on interoperable simulators. By applying the proposed modeling method, a target system can be translated to a hybrid model in a similar form as the target system. This paper also contains a simulation engine design for the proposed modeling methodlogy and a case study which simulates water tank control systems.

• Journal of Electrical Engineering and Technology
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• v.12 no.2
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• pp.790-802
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• 2017

This paper proposes the modeling and control strategy to track the MPPs of hybrid PV and Wind power systems, using a new dual input boost converter. The dual input power conditioning system with an independent MPPT control scheme is introduced with minimum number of circuit elements in order to reduce the switching loss, size and cost of the system. Since the operating conditions for the PV and Wind power systems are very distinct from each other, an efficient and superior control system is required to track the MPPs of both renewable sources with the use of a simply-structured single-ended single-inductor converter. The design of Power-Conditioning System (PCS) and detail control strategy are presented in this paper. To provide independent tracking of MPPs, a variable duty-cycle control strategy is employed for the wind system and a variable frequency strategy is employed for the PV system. Finally, the proposed dual-input converter for hybrid power conditioning system is implemented and the hardware test results are presented. From the hardware experiment, it is concluded that the proposed system successfully tracks the MPPs of both of the renewable power systems independently.

• Proceedings of the KIEE Conference
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• 2008.10c
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• pp.223-225
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• 2008

In order to apply SFCLs into electric power systems, the urgent issues to be settled are as follows, such as initial installation price, operation and maintenance cost due to ac loss of superconductor and the life of cryostat, and high voltage and high current problems. We designed novel hybrid SFCLs which combine superconductor and conventional electric equipments including a vacuum interrupter, an electro-magnetic contactor and a current limiting reactor. The main purpose of the hybrid SFCL is to drastically reduce total usage of superconductor by adopting current commutation method by use of the superconductor and the fast switch. According to protective coordination and performance, we investigated two concepts of Hybrid SFCLs. First is a half cycle fault current limitation type and second is a non-half cycle fault current limitation type. We concluded that the non-half cycle fault current limitation type is batter than the other.

• Smart Structures and Systems
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• v.16 no.6
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• pp.1107-1132
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• 2015

A damage detection algorithm based on neuro fuzzy hybrid system is presented in this study for location and severity predictions of cracks in beam-like structures. A combination of eigenfrequencies and rotation deviation curves are utilized as input to the soft computing technique. Both single and multiple damage cases are considered. Theoretical expressions leading to modal properties of damaged beam elements are provided. The beam formulation is based on Euler-Bernoulli theory. The cracked section of beam is simulated employing discrete spring model whose compliance is computed from stress intensity factors of fracture mechanics. A hybrid neuro fuzzy technique is utilized to solve the inverse problem of crack identification. Two different neuro fuzzy systems including grid partitioning (GP) and subtractive clustering (SC) are investigated for the highlighted problem. Several error metrics are utilized for evaluating the accuracy of the hybrid algorithms. The study is the first in terms of 1) using the two models of neuro fuzzy systems in crack detection and 2) considering multiple damages in beam elements employing the fused neuro fuzzy procedures. At the end of the study, the developed hybrid models are tested by utilizing the noise-contaminated data. Considering the robustness of the models, they can be employed as damage identification algorithms in health monitoring of beam-like structures.

• Smart Structures and Systems
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• v.4 no.5
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• pp.667-684
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• 2008

Numerous devices exist for reducing or eliminating seismic damage to structures. These include passive dampers, semi-active dampers, and active control devices. The performance of structural systems with these devices has often been evaluated using numerical simulations. Experiments on structural systems with these devices, particularly at large-scale, are lacking. This paper describes a real-time hybrid testing facility that has been developed at the Lehigh University NEES Equipment Site. The facility enables real-time large-scale experiments to be performed on structural systems with rate-dependent devices, thereby permitting a more complete evaluation of the seismic performance of the devices and their effectiveness in seismic hazard reduction. The hardware and integrated control architecture for hybrid testing developed at the facility are presented. An application involving the use of passive elastomeric dampers in a three story moment resisting frame subjected to earthquake ground motions is presented. The experiment focused on a test structure consisting of the damper and diagonal bracing, which was coupled to a nonlinear analytical model of the remaining part of the structure (i.e., the moment resisting frame). A tracking indictor is used to track the actuator ability to achieve the command displacement during a test, enabling the quality of the test results to be assessed. An extension of the testbed to the real-time hybrid testing of smart structures with semi-active dampers is described.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2004.10a
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• pp.211-216
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• 2004

In this thesis, we present the Takagi-Sugeno-Kang (TSK) fuzzy model based adaptive controller and adaptive identification for a general class of uncertain nonlinear dynamic systems. We use an estimated model for the unknown plant model and use this model for designing the controller. The hybrid adaptive control combined direct and indirect adaptive control based on TSK fuzzy model is constructed. The direct adaptive law can be showed by ignoring the identification errors and fails to achieve parameter convergence. Thus, we propose an TSK fuzzy model based hybrid adaptive (HA) law combined of the tracking error and the model ins error to adjust the parameters. Using a Lyapunov synthesis approach, the proposed hybrid adaptive control is proved. The hybrid adaptive law (HA) is better than the direct adaptive (DA) method without identifying the model ins error in terms of faster and improved tracking and parameter convergence. In order to show the applicability of the proposed method, it is applied to the inverted pendulum system and the performance is verified by some simulation results.

• ETRI Journal
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• v.43 no.2
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• pp.357-370
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• 2021

The evolution of blockchain-based systems has enabled researchers to develop nextgeneration e-voting systems. However, the classical consensus method of blockchain, that is, Proof-of-Work, as implemented in Bitcoin, has a significant impact on energy consumption and compromises the scalability, efficiency, and latency of the system. In this paper, we propose a hybrid consensus model (PSC-Bchain) composed of Proof of Credibility and Proof of Stake that work mutually to address the aforementioned problems to secure e-voting systems. Smart contracts are used to provide a trustworthy public bulletin board and a secure computing environment to ensure the accuracy of the ballot outcome. We combine a sharding mechanism with the PSC-Bchain hybrid approach to emphasize security, thus enhancing the scalability and performance of the blockchain-based e-voting system. Furthermore, we compare and discuss the execution of attacks on the classical blockchain and our proposed hybrid blockchain, and analyze the security. Our experiments yielded new observations on the overall security, performance, and scalability of blockchain-based e-voting systems.

• 제어로봇시스템학회:학술대회논문집
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• 1998.10a
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• pp.244-249
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• 1998

In this paper, the hybrid state space self-tuning control technique Is studied within the framework of fuzzy systems and dual-rate sampling control theory. We show that fuzzy modeling techniques can be used to formulate chaotic dynamical systems. Then, we develop the hybrid state space self-tuning fuzzy control techniques with dual-rate sampling for digital control of chaotic systems. An equivalent fast-rate discrete-time state-space model of the continuous-time system is constructed by using fuzzy inference systems. To obtain the continuous-time optimal state feedback gains, the constructed discrete-time fuzzy system is converted into a continuous-time system. The developed optimal continuous-time control law is then convened into an equivalent slow-rate digital control law using the proposed digital redesign method. The proposed technique enables us to systematically and effective]y carry out framework for modeling and control of chaotic systems. The proposed method has been successfully applied for controlling the chaotic trajectories of Chua's circuit.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2006.05a
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• pp.381-384
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• 2006

Self Organizing Map(SOM) is a powerful neural network model for unsupervised loaming. In many clustering works with exploratory data analysis, it has been popularly used. But it has a weakness which is the poorly theoretical base. A lot more researches for settling the problem have been published. Also, our paper proposes a method to overcome the drawback of SOM. As compared with the presented researches, our method has a different approach to solve the problem. So, a hybrid SOM is proposed in this paper. Using Monte Carlo computing, a hybrid SOM improves the performance of clustering. We verify the improved performance of a hybrid SOM according to the experimental results using UCI machine loaming repository. In addition to, the number of clusters is determined by our hybrid SOM.

• Smart Structures and Systems
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• v.10 no.3
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• pp.193-207
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• 2012

New insights into our previously proposed hybrid-type method for vibration control are highlighted in terms of energy analysis, such as the assessment of energy efficiency and system stability. The hybrid method improves the bang-bang active method by combining it with an energy-recycling approach. Its simple configuration and low energy-consumption property are quite suitable especially for isolated structures whose energy sources are strictly limited. The harmful influence of the external voltage is assessed, as well as its beneficial performance. We show a new chattering prevention approach that both harvests electrical energy from piezoelectric actuators and eliminates the displacement-offset of the equilibrium point of structures. The amount of energy consumption of the hybrid system is assessed qualitatively and is compared with other control systems. Experiments and numerical simulations conducted on a 10-bay truss can provide a thorough energy-efficiency evaluation of the hybrid suppression system having our energy-harvesting system.