• 산업경영시스템학회지
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• 제32권3호
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• pp.135-141
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• 2009

A variety of statistical methods are applied to model and optimize responses, related to product or system's quality, in terms of control and noise factors at design and manufacturing stages. Most of them assume continuous response variables but, assessing the performance of a product or system often involves categorical observations, such as ratings and scores. Although most previous works to deal with the categorical data provide sorhisticated response models and ensure unbiased outcomes, they require heavy computation to estimate the model parameters, as well as enough replications. In this study, we present some practical approaches for optimal parameter design with ordered categorical response when only a few or no replication is available. Two real-life examples are given to illustrate the presented methods.

• Transactions on Control, Automation and Systems Engineering
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• 제2권3호
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• pp.175-181
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• 2000

This paper investigates the robust nonlinear H$_{\infty}$ filter with FIR(Finite Impulse Response) structure for nonlinear discrete time-varying uncertain systems represented by the state-space model having parameter uncertainty. Firstly, when there is no parameter uncertainty in the system, the discrete-time nominal nonlinear H$_{\infty}$ FIR filter is derived by using the equivalence relationship between the FIR filter and the recursive filter, which corresponds to the standard nonlinear H$_{\infty}$ filter. Secondly, when the system has the parameter uncertainty, the robust nonlinear H$_{\infty}$ FIR filter is proposed for the discrete-time nonlinear uncertain systems.

• Transactions on Control, Automation and Systems Engineering
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• 제4권4호
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• pp.289-295
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• 2002

In this paper, a linear matrix inequality(LMI)-based robust control method, which combines model predictive control(MPC) with the feedback linearization(FL), is presented for constrained nonlinear systems with parameter uncertainty. The design procedures consist of the following 3 steps: Polytopic description of nonlinear system with a parameter uncertainty via FL, Mapping of actual input constraint by FL into constraint on new input of linearized system, Optimization of the constrained MPC problem based on LMI. To verify the performance and usefulness of the control method proposed in this paper, some simulations with application to a flexible single link manipulator are performed.

• 제어로봇시스템학회논문지
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• 제3권3호
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• pp.244-251
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• 1997

In this paper, we propose a fault diagnosis algorithm to detect and isolate multiple faults in a system. The proposed fault diagnosis algorithm is based on a multiple fault classifier which consists of two ART2 NN(adaptive resonance theory2 neural network) modules and the algorithm is composed of three main parts - parameter estimation, fault detection and isolation. When a change in the system occurs, estimated parameters go through a transition zone in which residuals between the system output and the estimated output cross the threshold, and in this zone, estimated parameters are transferred to the multiple faults classifier for fault isolation. From the computer simulation results, it is verified that when the proposed diagnosis algorithm is performed successfully, it detects and isolates faults in the position control system of a DC motor.

• Bulletin of the Korean Chemical Society
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• 제24권3호
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• pp.279-284
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• 2003

The One Pass Method (OPM) previously presented for the identification of single input single output systems is used to estimate the parameters of a Decentralized Control System (DCS). The OPM is a linear and therefore a simple estimation method. All of the calculations are performed in one pass, and no initial parameter guess, iteration, or powerful search methods are required. These features are of interest especially when the parameters of multi input-output model are estimated. The benefits of the OPM are revealed by comparing its results against those of two recently published methods based on pulse testing. The comparison is performed using two databases from the literature. These databases include single and multi input-output process transfer functions and relevant disturbances. The closed loop responses of these processes are roughly captured by the previous methods, whereas the OPM gives much more accurate results. If the parameters of a DCS are estimated, the OPM yields the same results in multi or single structure implementation. This is a novel feature, which indicates that the OPM is a convenient and practice method for the parameter estimation of multivariable DCSs.

• Journal of Electrical Engineering and Technology
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• 제8권3호
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• pp.464-471
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• 2013

This paper proposes a hybrid searching algorithm based on parameter identification for power system load models. Hybrid searching was performed by the combination of particle swarm optimization (PSO) and a complex method, which enhances the convergence of solutions closer to minima and takes advantage of global searching with PSO. In this paper, the load model of interest is composed of a ZIP model and a third-order model for induction motors for stability analysis, and parameter sets are obtained that best-fit the output measurement data using the hybrid search. The origin of the hybrid method is to further apply the complex method as a local search for finding better solutions using the selected particles from the performed PSO procedure.

• Bulletin of the Korean Chemical Society
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• 제22권11호
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• pp.1255-1260
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• 2001

The expansion of two different kinds of hydrodynamic size of polymethyl methacrylate (PMMA Mw: 1.56- 2.04 ${\times}$ 106 g/mol) has been measured by dynamic light scattering and viscometry above the Flory $\theta$ temperature of the variou s solvents such as n-butyl chloride, 3-heptanone, and 4-heptanone. The expansion of PMMA chains was analyzed in terms of universal temperature parameters and also compared with previous results of polystyrene (PS) system. First it was found that simple $\tau/{\tau}c$ parameter no longer had its universality for the expansion behavior of hydrodynamic size in the chemically different linear polymer chains. However after modifying ${\tau}/{\tau}c$ parameter into $(Mw/Ro2)3}2(\tau/\tauc)$, we observed a much better universality for both PMMA and PS systems. Here Mw, Ro, $\tau[=(T-{\theta}$)/${\theta}$]$, and ${\tau}c[=({\theta}-Tc)/Tc]$ are defined as the weight average molecular weight, the unperturbed end-to-end distance, the reduced temperature and the reduced critical temperature, respectively.

• 로봇학회논문지
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• 제17권3호
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• pp.347-352
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• 2022

The paper presents how to update impedance control parameters for dual-arm manipulators using EMG signals and motions of the operator. Since the hand motions of the dual-arm are modeled to be the mass-spring-damper system in this paper, the impedance parameter update method is an important issue to reflect the operator's force. However, task space inertia to be used as the mass parameter goes to infinity if the manipulator approaches a kinematic singularity. To alleviate this issue, the impedance (stiffness and damping) parameters are divided with a diagonal element of the task space inertia. Also, the stiffness and damping matrices are updated using the normalized EMG signals captured from the operator's forearm. Through this process, the motion of the dual-arm manipulator is more stabilized even though it approaches the kinematic singularity.

• International Journal of Control, Automation, and Systems
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• 제3권spc2호
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• pp.355-362
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• 2005

Deregulations and market practices in power industry have brought great challenges to the system planning area. In particular, they introduce a variety of uncertainties to system planning. New techniques are required to cope with such uncertainties. As a promising approach, probabilistic methods are attracting more and more attentions by system planners. In small signal stability analysis, generation control parameters play an important role in determining the stability margin. The objective of this paper is to investigate power system state matrix sensitivity characteristics with respect to system parameter uncertainties with analytical and numerical approaches and to identify those parameters have great impact on system eigenvalues, therefore, the system stability properties. Those identified parameter variations need to be investigated with priority. The results can be used to help Regional Transmission Organizations (RTOs) and Independent System Operators (ISOs) perform planning studies under the open access environment.

• 한국군사과학기술학회지
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• 제3권1호
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• pp.13-25
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• 2000

A simulation model is developed to analyze the large-structure driving system and its integrated behavior in the whole weapon system. It models every component in the driving system such as mechanical and electrical characteristics, and it is programmed by simulation language in a way which strongly reflects the system's real time dynamics and reduces computation time as well. A useful parameter identification method is proposed, and it is tuned on the given physical system. The model is validated through comparing to real test, and it is applied to analysis and prediction of integrated system functions relating to the fire control system.