• Communications for Statistical Applications and Methods
• /
• v.8 no.1
• /
• pp.29-37
• /
• 2001

In this paper, we consider the second order probability matching criterion for the ratio of the variance components under the one-way random effect model. It turns out that among all of the reference priors given in Ye(1994), the only one reference prior satisfies the second order matching criterion. Similar results are also obtained for the intraclass correlation as well.

• ETRI Journal
• /
• v.34 no.2
• /
• pp.184-189
• /
• 2012

In this paper, we propose a novel approach to statistical model-based voice activity detection (VAD) that incorporates a second-order conditional maximum a posteriori (CMAP) criterion. As a technical improvement for the first-order CMAP criterion in [1], we consider both the current observation and the voice activity decision in the previous two frames to take full consideration of the interframe correlation of voice activity. This is clearly different from the previous approach [1] in that we employ the voice activity decisions in the second-order (previous two frames) CMAP, which has quadruple thresholds with an additional degree of freedom, rather than the first-order (previous single frame). Also, a soft-decision scheme is incorporated, resulting in time-varying thresholds for further performance improvement. Experimental results show that the proposed algorithm outperforms the conventional CMAP-based VAD technique under various experimental conditions.

• Management Science and Financial Engineering
• /
• v.21 no.2
• /
• pp.25-30
• /
• 2015

This short article compares different solution methods for a basic RBC model (Hansen, 1985). We solve and simulate the model using two main algorithms: the methods of perturbation and projection, respectively. One novelty is that we offer a type of the hybrid method: we compute easily a second-order approximation to decision rules and use that approximation as an initial guess for finding Chebyshev polynomials. We also find that the second-order perturbation method is most competitive in terms of accuracy for standard RBC model.

• Journal of Advanced Marine Engineering and Technology
• /
• v.31 no.3
• /
• pp.293-300
• /
• 2007

The aim of this paper is to design a speed controller of a DC motor by selection of a PID parameters using genetic algorithm. The model of a DC motor is considered as a typical non-oscillatory, second-order system, And this paper compares three kinds of tuning methods of parameter for PID controller. One is the controller design by the genetic algorithm. second is the controller design by the model matching method third is the controller design by Ziegler and Nichols method. It was found that the proposed PID parameters adjustment by the genetic algorithm is better than the Ziegler & Nickels' method. And also found that the results of the method by the genetic algorithm is nearly same as the model matching method which is analytical method. The proposed method could be applied to the higher order system which is not easy to use the model matching method.

• Proceedings of the KIEE Conference
• /
• summer
• /
• pp.345-347
• /
• 2004

In small signal stability analysis of power systems, eigenvalue analysis is the most useful method and the detailed modeling of generator has an important effect to the eigenvalues. Generator full model is used for precise dynamic analysis of generators and controllers while two-axis model is used for multi-machine systems because of the reduced order of the state matrix. Also, the eigenvalue sensitivity coefficients are used for optimizing controller parameters to improve system stability. This paper compare the first and second order eigenvalue sensitivity coefficients of controllers using generator full model with those of two-axis model. As a result of an example, the estimated eigenvalues using the first and the second eigenvalue sensitivity coefficients using generator full model is very close to those of state matrix. Also the error ratios throughout a wide range of controller parameters is less than $1\%$.

• Nuclear Engineering and Technology
• /
• v.52 no.3
• /
• pp.552-559
• /
• 2020

This paper presents an observer-based chattering free robust optimal control scheme to regulate the total power of a nuclear reactor. The non-linear model of nuclear reactor is linearized around a steady state operating point to obtain a linear model for which an optimal second order integral sliding mode controller is designed. A second order integral sliding mode observer is also designed to estimate the unmeasurable states. In order to avoid the chattering effect, the discontinuous input of both observer and controller are designed using the super-twisting algorithm. The proposed controller is realized by combining an optimal linear tracking controller with a second order integral sliding mode controller to ensure minimum control effort and robustness of the closed-loop system in the presence of uncertainties. The condition for the selection of gains of discontinuous control based on the super-twisting algorithm is derived using a strict Lyapunov function. Performance of the proposed observer based control scheme is demonstrated through non-linear simulation studies.

• Nuclear Engineering and Technology
• /
• v.47 no.1
• /
• pp.94-101
• /
• 2015

This paper presents findings on the second-order sliding-mode controller for a nuclear research reactor. Sliding-mode controllers for nuclear reactors have been used for some time, but higher-order sliding-mode controllers have the added advantage of reduced chattering. The nonlinear model of Pakistan Research Reactor-1 has been used for higherorder sliding-mode controller design and performance evaluation. The reactor core is simulated based on point kinetics equations and one delayed neutron groups. The model assumes feedback from lumped fuel and coolant temperatures. The effect of xenon concentration is also considered. The employed method is easy to implement in practical applications, and the second-order sliding-mode control exhibits the desired dynamic properties during the entire output-tracking process. Simulation results are presented to demonstrate the effectiveness of the proposed controller in terms of performance, robustness, and stability.

• Korean journal of communication and information
• /
• v.74
• /
• pp.72-108
• /
• 2015

The more mobile technology evolves, the more users are trapped in mobile technology by being encouraging the replacement with state-of-the-art technology. However, the use of device is not entirely determined by technology's attributes itself. The meaning of smartness can be varied by 'how users accept and perceive immediate spatial perception from reality to mobile space' without recognizing the boundaries between them. This study focuses on the analysis of 'smart usage' for smartphone and this is verified the concept of 'smart usage' by the second-order measurement model. The result show that the concept organization of 'smart usage' had been differentiated and elicited by the six factors - 'multifunctional use readiness', 'administrative efficiency', 'embedded media', 'device connectivity', 'user-friendly optimization', and 'external connectivity(being connected). According to the conceptual factors, 'smart usage' can be explained in an individual's autonomous ability to control a mobile interface and to utilize a wide range of applications of smartphones.

• 제어로봇시스템학회:학술대회논문집
• /
• 1988.10b
• /
• pp.1018-1021
• /
• 1988

This study is concerned with modeling an elastomer constitutive relation by utilizing the truncated Volterra series. Actual experimental data from the Instron Tester are obtained for combined input, i.e. constant strain rate followed by a constant strain input. These data are then estimated for step inputs and utilized for the truncated Volterra series models. One second order and one third order truncated Volterra series models have been employed to estimated the force-displacement relation which is one of the prominent properities to characterize the viscoelastic material. The third order Volterra series model has better results, compared with those of the second order Volterra series model.

• Computational Structural Engineering : An International Journal
• /
• v.3 no.1
• /
• pp.1-7
• /
• 2003

For system identification of large structures, it is not practical to identify the entire structure due to the prohibitive computational time and difficulty in numerical convergence. This paper explores the possibility of performing system identification at substructure level, taking advantage of reduction in both the number of unknowns and the number of degrees of freedom involved. Another advantage is that different portions (substructures) of a structural system can be identified independently and even concurrently with parallel computing. Two substructural identification methods are formulated on the basis whether substructural approach is used to obtain first-order or second-order model. For substructural first-order model, identification at the substructure level will be performed by means of the Observer/Kalman filter Identification (OKID) and the Eigensystem Realization Algorithm (ERA) whereas identification at the global level will be performed to obtain second-order model in order to evaluate the system's stiffness and mass parameters. In the case of substructural second-order model, identification will be performed at the substructure level throughout the identification process. The efficiency of the proposed technique is shown by numerical examples for multi-storey shear buildings subjected to random forces, taking into consideration the effects of noisy measurement data. The results indicate that both the proposed methods are effective and efficient for damage identification of large structures.