• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.7
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• pp.615-620
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• 2001

This paper addresses the design of sliding model fuzzy-model-based controller using genetic algorithms. In general, the construction of fuzzy logic controllers has difficulties for the lack of systematic design procedure. To release this difficulties, the sliding model fuzzy-model-based controllers was presented by authors. In this proposed method, the fuzzy model, which represents the local dynamic behavior of the given nonlinear system, is utilized to construct the controller. The overall controller consists of the local compensators which compensate the local dynamic linear model and the feed-forward controller which is designed via sliding mode control theory. Although, the stability and the performance is guaranteed by the proposed method, some design parameters have to be chosen by the designer manually. This problem can be solved by using genetic algorithms. The proposed method tunes the parameters of the controller, by which the reasonable accuracy and the control effort is achieved. The validity and the efficiency of the proposed method are verified through simulations.

• Journal of Electrical Engineering and Technology
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• v.7 no.6
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• pp.845-851
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• 2012

Power system loads have a significant impact on a system. Although it is difficult to precisely describe loads in a mathematical model, accurately modeling them is important for a system analysis. The traditional load modeling method is based on the load components of a bus. Recently, the load modeling method based on measurements from a system has been introduced and developed by researchers. The two major components of a load modeling problem are determining the mathematical model for the target system and estimating the parameters of the determined model. We use the composite load model, which has both static and dynamic load characteristics. The ZIP model and the induction motor model are used for the static and dynamic load models, respectively. In this work, we propose the measurement-based parameter estimation method for the composite load model. The test system and related measurements are obtained using transient security assessment tool(TSAT) simulation program and PSS/E. The parameter estimation is then verified using these measurements. Cases are tested and verified using the sample system and its related measurements.

• Phonetics and Speech Sciences
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• v.2 no.3
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• pp.141-148
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• 2010

In this paper, voice activity detection (VAD) for dual-channel noisy speech recognition is proposed in which spatial cues are employed. In the proposed method, a probability model for speech presence/absence is constructed using spatial cues obtained from dual-channel input signal, and a speech activity interval is detected through this probability model. In particular, spatial cues are composed of interaural time differences and interaural level differences of dual-channel speech signals, and the probability model for speech presence/absence is based on a Gaussian kernel density. In order to evaluate the performance of the proposed VAD method, speech recognition is performed for speech segments that only include speech intervals detected by the proposed VAD method. The performance of the proposed method is compared with those of several methods such as an SNR-based method, a direction of arrival (DOA) based method, and a phase vector based method. It is shown from the speech recognition experiments that the proposed method outperforms conventional methods by providing relative word error rates reductions of 11.68%, 41.92%, and 10.15% compared with SNR-based, DOA-based, and phase vector based method, respectively.

• Journal of the Korea Institute of Military Science and Technology
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• v.20 no.5
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• pp.688-699
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• 2017

Model-based test, a well-known method of the black box tests, is consisted of the following four steps : model construction using requirement, test case generation from the model, execution of a SUT (software under test) and detection failures. Among models constructed in the first step, state-based models such as UML standard State Machine are commonly used to design event-based embedded systems (e.g., weapon control systems). To generate test cases from state-based models in the next step, coverage-based techniques such as state coverage and transition coverage are used. Round-trip path coverage technique using W-Method, one of coverage-based techniques, is known as more effective method than others. However it has a limitation of low failure observability because the W-Method technique terminates a testing process when arrivals meet states already visited and it is hard to decide the current state is completely same or not with the previous in the case like the GUI environment. In other words, there can exist unrevealed faults. Therefore, this study suggests a Extended W-Method. The Extended W-Method extends the round-trip path to a final state to improve failure observability. In this paper, we compare effectiveness and efficiency with requirement-item-based technique, W-Method and our Extended W-Method. The result shows that our technique can detect five and two more faults respectively and has the performance of 28 % and 42 % higher failure detection probability than the requirement-item-based and W-Method techniques, respectively.

• Computers and Concrete
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• v.12 no.2
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• pp.229-241
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• 2013

The objective of this study is to reveal the sufficiency of neural networks (NN) as a securer, quicker, more robust and reliable method to be used in seismic assessment of existing reinforced concrete buildings. The NN based approach is applied as an alternative method to determine the seismic performance of each existing RC buildings, in terms of damage level. In the application of the NN, a multilayer perceptron (MLP) with a back-propagation (BP) algorithm is employed using a scaled conjugate gradient. NN based model wasd eveloped, trained and tested through a based MATLAB program. The database of this model was developed by using a statistical procedure called P25 method. The NN based model was also proved by verification set constituting of real existing RC buildings exposed to 2003 Bingol earthquake. It is demonstrated that the NN based approach is highly successful and can be used as an alternative method to determine the seismic performance of each existing RC buildings.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2005.11b
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• pp.140-143
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• 2005

The hybrid CAE/CAT methods are widely applied to product development in various fields because this method can predict the response of the whole system when a part of the system is changed. Especially, the hybrid CAE/CAT method is very useful to predict tile vehicle NVH characteristics after changing some parts of the vehicle. Target parts can be established on the basis of test models and FE models of the prototype constructed in the planning stage of car development. In this study, the topic was focused on the proper test-based FBS application process to predict vehicle NVH characteristic. First, the test-based FBS method was apply to vehicle substructure and car-body. And then the test-based model was replaced with FE model to apply hybrid CAE/CAT method. The replaced FE model was modified through the optimization process. The interior noise in vehicle during the drive was predicted with Modified FE model, then the predicted results were verified by experimenting with actual modified model.

• Smart Structures and Systems
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• v.15 no.3
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• pp.645-663
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• 2015

Recently, an indirect displacement estimation method using data fusion of acceleration and strain (i.e., acceleration-strain-based method) has been developed. Though the method showed good performance on beam-like structures, it has inherent limitation in applying to more general types of bridges that may have complex shapes, because it uses assumed analytical (sinusoidal) mode shapes to map the measured strain into displacement. This paper proposes an improved displacement estimation method that can be applied to more general types of bridges by building the mapping using the finite element model of the structure rather than using the assumed sinusoidal mode shapes. The performance of the proposed method is evaluated by numerical simulations on a deck arch bridge model and a three-span truss bridge model whose mode shapes are difficult to express as analytical functions. The displacements are estimated by acceleration-based method, strain-based method, acceleration-strain-based method, and the improved method. Then the results are compared with the exact displacement. An experimental validation is also carried out on a prestressed concrete girder bridge. The proposed method is found to provide the best estimate for dynamic displacements in the comparison, showing good agreement with the measurements as well.

• Management Science and Financial Engineering
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• v.19 no.2
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• pp.37-42
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• 2013

This paper suggests a numerical method for valuation of European and American options under the two L$\acute{e}$vy Processes, Normal Inverse Gaussian Model and the Variance Gamma model. The method is based on approximation of underlying asset price using a finite-state, time-homogeneous Markov chain. We examine the effectiveness of the proposed method with simulation results, which are compared with those from the existing numerical method, the lattice-based method.

• Proceedings of the KSME Conference
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• 2008.11a
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• pp.678-683
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• 2008

Moment-based reliability analysis is the method to calculate reliability using Pearson System with first-four raw moments obtained from simulation model. But it is too expensive to calculate first four moments from complicate simulation model. To overcome this drawback the MD(multiplicative decomposition) method which approximates simulation model to kriging metamodel and calculates first four raw moments explicitly with multiplicative decomposition techniques. In general, kriging metamodel is an interpolation model that is decomposed of global model and local model. The global model, in general, can be used as the constant global model, the 1st order global model, or the 2nd order global model. In this paper, the influences of global models on the accuracy and robustness of raw moments are examined and compared. Finally, we suggest the best global model which can provide exact and robust raw moments using MD method.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.1 no.1
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• pp.113-118
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• 2001

In this paper, we develop an optimal intelligent digital redesign method for a class of fuzzy-model-based controllers, effective for stabilization of continuous-time complex nonlinear systems. Takagi-Sugeno (TS) fuzzy model is used to extend the results of the classical digital redesign technique to complex nonlinear systems. Unlike the conventional intelligent digital redesign technique reported in the literature, the proposed method utilized the recently developed LMI optimization technique to obtain a digitally redesigned fuzzy-model-based controller. Precisely speaking, the intelligent digital redesign problem is converted to an equivalent optimization problem, and the LMI optimization method is used to find the digitally redesigned fuzzy-model-based controller. A numerical example is provided to evaluate the feasibility of the proposed approach.