• 제어로봇시스템학회:학술대회논문집
• /
• 1994.10a
• /
• pp.277-282
• /
• 1994

Convergence of the state error e to zero in adaptive systems is shown using the uniqueness of solutions and the existence of a Lyapunov function in which the adaptation laws are constructed. Results in the paper are general, and therefore applicable to any adaptive control of a linear/nonlinear, time-varying or distributed-parameter system. Since the approach taken in the paper does not require the boundedness of the derivative of the state error e for all t .geq. 0, it is particularly useful in the adaptive control of infinite dimensional systems.

• The Transactions of the Korean Institute of Electrical Engineers
• /
• v.40 no.2
• /
• pp.144-153
• /
• 1991

This paper presents an algorithm to improve accuracy and reliability in the state estimation of contaminated bad data. The conventional algorithms for detection of bad data have the problems of excessive memory requirements and long computation time. In order to overcome these problems, a measurement compensation approach is proposed to reduce computation time, and the partitioned measurement error model has the advantage of remarkable reduction in computation time and memory requirements in estimated error computation. The proposed algorithm has been tested for IEEE sample systems, which shows its applicability to on-line power systems.

• 제어로봇시스템학회:학술대회논문집
• /
• 1993.10a
• /
• pp.34-39
• /
• 1993

Presented in this paper is a complete error covariance analysis for strapdown inertial navigation system(SDINS). We have found that in SDINS the cross-coupling terms in gyrocompass alignment errors can significantly influence the SDINS error propagation. Initial heading error has a close correlation with the east component of gyro bias erro, while initial level tilt errors are closely related to accelerometer bias errors. In addition, pseudo-state variables are introduced in covariance analysis for SDINS utilizing the characteristics of gyrocompass alignment errors. This approach simplifies the covariance analysis because it makes the initial error covariance matrix to a diagonal form. Thus a real implementation becomes easier. The approach is conformed by comparing the results for a simplified case with the covariance analysis obtained from the conventional SDINS error model.

• The Transactions of the Korean Institute of Electrical Engineers
• /
• v.45 no.3
• /
• pp.399-406
• /
• 1996

This paper presents a method of hierarchical state estimation of the time-varying linear systems via Block-pulse function(BPF). When we estimate the state of the systems where noise is considered, it is very difficult to obtain the solutions because minimum error variance matrix having a form of matrix nonlinear differential equations is included in the filter gain calculation. Therefore, hierarchical approach is adapted to transpose matrix nonlinear differential equations to a sum of low order state space equation from and Block-pulse functions are used for solving each low order state space equation in the form of simple and recursive algebraic equation. We believe that presented methods are very attractive nd proper for state estimation of time-varying linear systems on account of its simplicity and computational convenience. (author). 13 refs., 10 figs.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2023.05a
• /
• pp.25-25
• /
• 2023

The ensemble optimal interpolation (EnOI) scheme is a sub-optimal alternative to the ensemble Kalman filter (EnKF) with a reduced computational demand making it potentially more suitable for operational applications. Since only one model is integrated forward instead of an ensemble of model realizations, online estimation of the background error covariance matrix is not possible in the EnOI scheme. In this study, we investigate two Gaussian noise based ensemble generation strategies to produce dynamic covariance matrices for assimilation of water level observations into a distributed hydrological model. In the first approach, spatially correlated noise, sampled from a normal distribution with a fixed fractional error parameter (which controls its standard deviation), is added to the model forecast state vector to prepare the ensembles. In the second method, we use an adaptive error estimation technique based on the innovation diagnostics to estimate this error parameter within the assimilation framework. The results from a real and a set of synthetic experiments indicate that the EnOI scheme can provide better results when an optimal EnKF is not identified, but performs worse than the ensemble filter when the true error characteristics are known. Furthermore, while the adaptive approach is able to reduce the sensitivity to the fractional error parameter affecting the first (non-adaptive) approach, results are usually worse at ungauged locations with the former.

• ETRI Journal
• /
• v.31 no.1
• /
• pp.42-50
• /
• 2009

A new method for simulating voltage and current distributions in transmission lines is described. It gives the time domain solution of the terminal voltage and current as well as their line distributions. This is achieved by treating voltage and current distributions as distributed state variables (DSVs) and turning the transmission line equation into an ordinary differential equation. Thus the transmission line is treated like other lumped dynamic components, such as capacitors. Using backward differentiation formulae for time discretization, the DSV transmission line component is converted to a simple time domain companion model, from which its local truncation error can be derived. As the voltage and current distributions get more complicated with time, a new piecewise exponential with controllable accuracy is invented. A segmentation algorithm is also devised so that the line is dynamically bisected to guarantee that the total piecewise exponential error is a small fraction of the local truncation error. Using this approach, the user can see the line voltage and current at any point and time freely without explicitly segmenting the line before starting the simulation.

• Proceedings of the IEEK Conference
• /
• 2002.06b
• /
• pp.369-372
• /
• 2002

This paper presents a family of continuous conduction mode with constant-switching pulse width modulator controllers. Unified implementation of quasi steady state approach for various DC-DC converters topoiogies is illustrated. The property and control low for quasi-state approach will be discussed in this paper. The different procedures will be discussed in details with different results for five commonly used DC-DC converters. Both trailing and leading edge pulse width modulation are used. Leading edge modulation can some times lead to simpler control circuitry as will be demonstrated in some circuits. These controllers do not require the multiplier in the voltage feed back loop, error amplifier in the current loop and rectified line voltage sensor, which are needed by traditional control methods. Controller examples and design arc analyzed.

• Journal of applied mathematics & informatics
• /
• v.7 no.2
• /
• pp.409-438
• /
• 2000

In this paper we develop a new procedure to control stepsize for Runge- Kutta methods applied to both ordinary differential equations and semi-explicit index 1 differential-algebraic equation In contrast to the standard approach, the error control mechanism presented here is based on monitoring and controlling both the local and global errors of Runge- Kutta formulas. As a result, Runge-Kutta methods with the local-global stepsize control solve differential of differential-algebraic equations with any prescribe accuracy (up to round-off errors)

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 2006.11a
• /
• pp.293-296
• /
• 2006

This paper presents new sufficient conditions to an intelligent digital redesign (IDR). The purpose of the IDR is to effectively convert an existing continuous-time fuzzy controller to an equivalent sampled-data fuzzy controller in the sense of the state-matching. The state-matching error between the closed-loop trajectories is carefully analyzed using the integral quadratic functional approach. The problem of designing the sampled-data fuzzy controller to minimize the state-matching error as well as to guarantee the stability is formulated and solved as the convex optimization problem with linear matrix inequality (LMI) constraints.

• Journal of Power System Engineering
• /
• v.12 no.6
• /
• pp.42-49
• /
• 2008

The most important job in the container terminal area is to handle the cargo effectively in the limited time. To achieve this object, many strategies have been introduced and applied to. If we consider the automated container terminal, it is necessary that the cargo handling equipments are equipped with more intelligent control systems. From the middle of the 1990's, an automated rail-mounted gantry crane(RMGC) and rubber-tired gantry crane(RTG) have been developed and widely used to handle containers in the yards. Recently, in these cranes, the many equipments like CCD cameras and sensors are mounted to cope with the automated terminal environment. In this paper, we try to support the development of more intelligent automated cranes which make the cargo handling be performed effectively in the yards. For this plant, the modelling, tracking control, anti-sway system design, skew motion suppressing and complicated motion control and suppressing problems must be considered. Especially, in this paper, the system modelling and tracking control approach are discussed. And, we design the tracking control system incorporating an observer based on the 2DOF servo system design approach to obtain the desired state informations. In the case of observer design, a weighted $H_{\infty}$ error bound approach for a state estimator is considered. Based on an algebraic Riccati equation(inequality) approach, a necessary and sufficient condition for the existence of a full-order estimator which satisfies the weighted $H_{\infty}$ error bound is introduced. Where, the condition for existence of the estimator is denoted by a Linear Matrix Inequality(LMI) which gives an optimized solution and observer gain. Based on this result, we apply it to the tracking control system design for the transfer crane.