• Communications for Statistical Applications and Methods
• /
• 제5권2호
• /
• pp.539-557
• /
• 1998

This article is concerned with the problem of estimating the mean of a one-parameter exponential family through sequential sampling in three stages under quadratic error loss. This more general framework differs from those considered by Hall (1981) and others. The differences are : (i) the estimator and the final stage sample size are dependent; and (ii) second order approximation of a continuously differentiable function of the final stage sample size permits evaluation of the asymptotic regret through higher order moments. In particular, the asymptotic regret can be expressed as a function of both the skewness $\rho$ and the kurtosis $\beta$ of the underlying distribution. The conditions on $\rho$ and $\beta$ for which negative regret is expected are discussed. Further results concerning the stopping variable N are also presented. We also supplement our theoretical findings wish simulation results to provide a feel for the triple sampling procedure presented in this study.

• 대한전기학회:학술대회논문집
• /
• 대한전기학회 2000년도 하계학술대회 논문집 B
• /
• pp.1056-1058
• /
• 2000

Deadbeat technique has been proposed as a digital controller for an UPS inverter to achieve the fast response to a load variation and to conserve a very low THD under a nonlinear load condition. This scheme contains a fatal drawback, sensitivity against parameter variation and calculation time delay. This paper proposes a second order deadbeat current controller, which fundamentally solves the calculation time delay problem and certainly guarantees the robustness of the parameter's variation. This is shown theoretically and practically through simulation and experiment.

• Korean Journal of Chemical Engineering
• /
• 제36권3호
• /
• pp.356-367
• /
• 2019

This work presents an advanced and systematic approach to analytically design the optimal parameters of a two parameter second-order internal model control (IMC) filter that satisfies operational constraints on the output process, the manipulated variable as well as rate of change of the manipulated variable, for a first-order plus dead time (FOPDT) process. The IMC parameters are designed to minimize a control objective function composed of the weighted sum of the error between the process variable and the set point, and the rate of change of the manipulated variable, and to satisfy the desired constraints. The feasible region of the constrained IMC control parameters was graphically analyzed, as the process parameters and the constraints varied. The resulting constrained IMC control parameters were also used to find the corresponding industrial proportional-integral controller parameters of a Smith predictor structure.

• Journal of Electrical Engineering and Technology
• /
• 제8권5호
• /
• pp.975-983
• /
• 2013

This study proposes a low order dynamic model of a building system in order to predict thermal behavior within a building and its energy consumption. The building system includes a thermally well-insulated room and an electric heater. It is modeled by a second order lumped RC thermal network based on the thermal-electrical analogy. In order to identify unknown parameters of the model, an experimental procedure is firstly detailed. Then, the different linear parametric models (ARMA, ARX, ARMAX, BJ, and OE models) are recalled. The parameters of the parametric models are obtained by the least square approach. The obtained parameters are interpreted to the parameters of the physically based model in accordance with their relationship. Afterwards, the obtained models are implemented in Matlab/Simulink(R) and are evaluated by the mean of the sum of absolute error (MAE) and the mean of the sum of square error (MSE) with the variable of indoor temperature of the room. Quantities of electrical energy and converted thermal energy are also compared. This study will permit a further study on Model Predictive Control adapting to the proposed model in order to reduce energy consumption of the building.

• 대한의용생체공학회:학술대회논문집
• /
• 대한의용생체공학회 1990년도 추계학술대회
• /
• pp.25-28
• /
• 1990

We tested the ability of two-dimensional echocardiograms of complete heart cycle in closed-chest human to discriminate between normal and infarcted myocardium using fixed window, Inter- and Intra-frame analysis. The results show that statistical parameter, MEAN, second order gray level statistics parameter, ASM and proposed parameter, HGE, I.T, can quantitatively distinguish between normal and Infarcted regions. The manner in which these parameters vary over the cardiac cycle is also a good indicator of the state of myocardium. The infarcted areas yield regions of higher Intensity throughout the cardiac cycle. Whereas, normal tissue demonstrates greater variability throughout the cardiac cycle.

• 대기
• /
• 제30권4호
• /
• pp.335-346
• /
• 2020

Three free parameters included in a cumulus parameterization are optimized by using micro-genetic algorithm for three precipitation cases occurred in the Korea Peninsula during the summer season in order to reduce biases in a regional model associated with the uncertainties of the parameters and thus to improve the predictability of precipitation. The first parameter is the one that determines the threshold in convective trigger condition. The second parameter is the one that determines boundary layer forcing in convective closure. Finally, the third parameter is the one used in calculating conversion parameter determining the fraction of condensate converted to convective precipitation. Optimized parameters reduce the occurrence of convections by suppressing the trigger of convection. The reduced convection occurrence decreases light precipitation but increases heavy precipitation. The sensitivity experiments are conducted to examine the effects of the optimized parameters on the predictability of precipitation. The predictability of precipitation is the best when the three optimized parameters are applied to the parameterization at the same time. The first parameter most dominantly affects the predictability of precipitation. Short-range forecasts for July 2018 are also conducted to statistically assess the precipitation predictability. It is found that the predictability of precipitation is consistently improved with the optimized parameters.

• 로봇학회논문지
• /
• 제6권2호
• /
• pp.130-140
• /
• 2011

This paper proposes an optimal posture for the task-oriented movement of dual arm manipulator. A stability criterion function which consists of three kinds of feature-representative parameters has been utilized to define the optimal posture. The first parameter is the force which is applied to the object. The torque of each joint and position of arm are attained from the current sensor and encoder, respectively. From these two data, the applied force to an object is estimated using sum of vectors of the joint torques estimated from the measured current. In order to investigate the robustness of each posture, the variation of the end-effector from the encoder information has been utilized as the second parameter. And for the last parameter for the optimality, the total energy consumption has been used. The total consuming energy of each posture can be computed from the current information and the battery voltage. The proposed robot structure consists of a mobile inverted pendulum and dual manipulators. In order to define the optimal posture for the each object, external disturbances are applied to the mobile inverted pendulum robot and the first and second parameters are investigated to find the optimal posture among the pre-selected most representative postures. Finally, the proposed optimal posture has been verified by the proposed stability criterion function which consists of total force to the object, the fluctuation of the end-effector position, and total energy consumption. The effectiveness of the proposed algorithms has been verified and demonstrated through the practical simulations and real experiments.

• 제어로봇시스템학회논문지
• /
• 제4권5호
• /
• pp.608-615
• /
• 1998

In this paper a second-order iterative learning control algorithm with feedback is proposed for the trajectory-tracking control of nonlinear dynamic systems with unidentified parameters. In contrast to other known methods, the proposed teaming control scheme utilize more than one past error history contained in the trajectories generated at prior iterations, and a feedback term is added in the learning control scheme for the enhancement of convergence speed and robustness to disturbances or system parameter variations. The convergence proof of the proposed algorithm is given in detail, and the sufficient condition for the convergence of the algorithm is provided. We also discuss the convergence performance of the algorithm when the initial condition at the beginning of each iteration differs from the previous value of the initial condition. The effectiveness of the proposed algorithm is shown by computer simulation result. It is shown that, by adding a feedback term in teaming control algorithm, convergence speed, robustness to disturbances and robustness to unmatched initial conditions can be improved.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
• /
• pp.369-369
• /
• 2000

Control system by means of fuzzy theory has demonstrated its robustness in applying to the high-order and nonlinear dynamic system in that it can utilizes the human expert knowledges in system design. In this paper, first, the design methodology of HFC combined PID controller with fuzzy controller by membership function of weighting coefficient is proposed. Second, Second, an auto-tuning algorithms utilizing the simplified reasoning method and genetic algorithms is presented to improve the performance of hybrid fuzzy controller. Especially, in order to obtain the optimal scaling factors and PID parameters of HFC using GA based on advanced initial individual, three kinds of estimation modes such as basic, contraction, and expansion mode are effectively utilized. The proposed HFC is evaluated and discussed in ITAE, overshoot and rising time to show applicability and superiority with simulation results.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
• /
• pp.346-346
• /
• 2000

We proposed a method of second-order iterative learning control with feedback, which shows an enhancement of convergence speed and robustness to the disturbances in our previous study. In this paper, we show that the proposed second-order iterative learning control algorithm with feedback is more effective and has better convergence performance than the algorithm without feedback in the case of the existence of initial condition errors. And the convergence woof of the proposed algorithm in the case of the existence of initial condition error is given in detail, and the effectiveness of the Proposed algorithm is shown by simulation results.