• Journal of Power System Engineering
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• v.5 no.4
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• pp.44-52
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• 2001

This paper considers a modeling and identification for the MIMO magnetic bearing system. To obtain the nominal plant transfer functions, we have experimented on the frequency response by a closed-loop identification method because the system is unstable essentially. We suggest a method of curve-fitting for obtaining the transfer function from the frequency responses by using the system's modeling structure and two controllers which are different from each other. From the frequency response results, we found the effects of coupling by opposing controllers. And using this effects and the system's modeling structure, we could obtain the transfer functions of which have the same modularized denominators.

• Smart Structures and Systems
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• v.26 no.4
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• pp.419-433
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• 2020

Investigation of structural integrity has been a critical issue in the field of civil engineering for years. Visual inspection is one of the most available methods to explore deteriorative components in structures. Still, this method is not applicable to invisible damage of structures. Alternatively, system identification methods are capable of tracking modal properties of structures over time. The deviation of these dynamic properties can serve as indicators to access structural integrity. In this study, a modal tracking technique using frequency-domain system identification from seismic responses of structures is proposed. The method first segments the measured signals into overlapped sequential portions and then establishes multiple Hankel matrices. Each Hankel matrix is then converted to the frequency domain, and a temporal-average frequency-domain Hankel matrix can be calculated. This study also proposes the frequency band selection that can divide the frequency-domain Hankel matrix into several portions in accordance with referenced natural frequencies. Once these referenced natural frequencies are unavailable, the first few right singular vectors by the singular value decomposition can offer these references. Finally, the frequency-domain stochastic subspace identification tracks the natural frequencies and mode shapes of structures through quick stabilization diagrams. To evaluate performance of the proposed method, a numerical study is carried out. Moreover, the long-term monitoring strong motion records at a specific site are exploited to assess the tracking performance. As seen in results, the proposed method is capable of tracking modal properties through seismic responses of structures.

• The Journal of Society for e-Business Studies
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• v.19 no.4
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• pp.151-168
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• 2014

UCI (Universal Content Identifier) as a national digital content identification system for identifying digital content and ICN (Integrated Copyright Number) for copyright management are operated by Korea copyright commission. However, They are not interoperable with international standard identification system such as ISRC (International Standard Recording Code), ISWC (International Standard Works Code), and ISAN (International Standard Audiovisual Number) due to lack of linkage system. Hence, extra works with international standard identification system are needed for international market entry and integrated management of statistical information including content settlement in international market is impossible. In this paper, the domestic/international identification systems are surveyed, and by metadata analysis of identification systems, linkage method with UCI/ICN is proposed. And also by developing the prototype model, research direction to UCI/ICN with international standard identification system is proposed.

• International Journal of Control, Automation, and Systems
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• v.3 no.3
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• pp.387-396
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• 2005

The Rotational/Translational Actuator (RTAC) benchmark problem considers a fourth-order dynamical system involving the nonlinear interaction of a translational oscillator and an eccentric rotational proof mass. This problem has been posed to investigate the utility of a rotational actuator for stabilizing translational motion. In order to experimentally implement any of the model-based controllers proposed in the literature, the values of model parameters are required which are generally difficult to determine rigorously. In this paper, an approach to the least-squares estimation of the parameters of a system is formulated and practically applied to the RTAC system. On the other hand, this paper shows how to model a nonlinear system as a linear uncertain system via nonparametric system identification, in order to provide the information required for linear robust $H_\infty$ control design. This method is also applied to the RTAC system, which demonstrates severe nonlinearities, due to the coupling from the rotational motion to the translational motion. Experimental results confirm that this approach can effectively condense the whole nonlinearities, uncertainties, and disturbances within the system into a favorable perturbation block.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.6
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• pp.43-52
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• 1994

A design method of rule-based fuzzy modeling is presented for the model identification of complex and nonlinear systems. The proposed rule-based fuzzy modeling implements system structure and parameter identification in the efficient form of ``IF....,THEN...', using the theories of optimization theory , linguistic fuzzy implication rules and fuzzy c-means clustering. Three kinds of method for fuzzy modeling presented in this paper include simplified inference (type I), linear inference (type 2), and modified linear inference (type 3). In order to identify premise structure and parameter of fuzzy implication rules, fuzzy c- means clustering and modified complex method are used respectively and the least sequare method is utilized for the identification of optimum consequence parameters. Time series data for gas furance and those for sewage treatment process are used to evaluate the performance of the proposed rule-based fuzzy modeling. Comparison shows that the proposed method can produce the fuzzy model with higher accuracy than previous other studies.

• Proceedings of the KSPS conference
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• 2003.10a
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• pp.185-188
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• 2003

In this paper, we construct phonetic GMM for text-independent speaker identification system. The basic idea is to combine of the advantages of baseline GMM and HMM. GMM is more proper for text-independent speaker identification system. In text-dependent system, HMM do work better. Phonetic GMM represents more sophistgate text-dependent speaker model based on text-independent speaker model. In speaker identification system, phonetic GMM using HMM-based speaker-independent phoneme recognition results in better performance than baseline GMM. In addition to the method, N-best recognition algorithm used to decrease the computation complexity and to be applicable to new speakers.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.6
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• pp.789-799
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• 1999

In this paper, the optimization of fuzzy inference systems is proposed for fuzzy model of nonlinear systems. A fuzzy model needs to be identified and optimized by means of the definite and systematic methods, because a fuzzy model is primarily acquired by expert's experience. The proposed rule-based fuzzy model implements system structure and parameter identification using the HCM(Hard C-mean) clustering method, genetic algorithms and fuzzy inference method. Two types of inference methods of a fuzzy model are the simplified inference and linear inference. in this paper, nonlinear systems are expressed using the identification of structure such as input variables and the division of fuzzy input subspaces, and the identification of parameters of a fuzzy model. To identify premise parameters of fuzzy model, the genetic algorithms is used and the standard least square method with the gaussian elimination method is utilized for the identification of optimum consequence parameters of fuzzy model. Also, the performance index with weighting factor is proposed to achieve a balance between the performance results of fuzzy model produced for the training and testing data set, and it leads to enhance approximation and predictive performance of fuzzy system. Time series data for gas furnace and sewage treatment process are used to evaluate the performance of the proposed model.

• International Journal of Computer Science & Network Security
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• v.22 no.11
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• pp.241-247
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• 2022

Ad hoc network is self-organized network powered by battery. The reliability of virtual user identification and channel security are reduced when SNR is low due to limited user energy. In order to solve this problem, a joint virtual user identification and channel security en/decoding method is proposed in this paper. Transmitter-receiver-based virtual user identification code is generated by executing XOR operation between orthogonal address code of transmitter and pseudo random address code of receiver and encrypted by channel security code to acquire orthogonal random security sequence so as to improve channel security. In order to spread spectrum as well as improve transmission efficiency, data packet is divided into 6-bit symbols, each symbol is mapped with an orthogonal random security sequence. Subspace-based method is adopted by receiver to process received signal firstly, and then a judgment model is established to identify virtual users according to the previous processing results. Simulation results indicate that the proposed method obtains 1.6dB E_b/N₀ gains compared with reference methods when miss alarm rate reaches 10^-3.

• International Journal of Computer Science & Network Security
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• v.22 no.12
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• pp.212-216
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• 2022

Space based constellation network is a kind of ad hoc network in which users are self-organized without center node. In space based constellation network, users are allowed to enter or leave the network at any given time. Thus, the number of active users is an unknown and time-varying parameter, and the performance of the network depends on how accurately this parameter is estimated. The so-called problem of active user identification, which consists of determining the number and identities of users transmitting in space based constellation network is discussed and a novel active user identification method is proposed in this paper. Active user identification code generated by transmitter address code and receiver address code is used to spread spectrum. Subspace-based method is used to process received signal and judgment model is established to identify active users according to the processing results. The proposed method is simulated under AWGN channel, Rician channel and Rayleigh channel respectively. Numerical results indicate that the proposed method obtains at least 1.16dB E_b/N₀ gains compared with reference methods when miss alarm rate reaches 10^-3.

• Transactions of the Korean Society of Automotive Engineers
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• v.10 no.5
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• pp.29-34
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• 2002

This study presents the process of the continuous-time system identification for unknown nonlinear systems. The Radial Basis Function(RBF) error filtering identification model is introduced at first. This identification scheme includes RBF network to approximate unknown function of nonlinear system which is structured by affine form. The neural network is trained by the adaptive law based on Lyapunov synthesis method. The identification scheme is applied to engine and the performance of RBF error filtering Identification model is verified by the simulation with a three-state engine model. The simulation results have revealed that the values of the estimated function show favorable agreement with the real values of the engine model. The introduced identification scheme can be effectively applied to model-based nonlinear control.