• Proceedings of the KIEE Conference
• /
• 2007.07a
• /
• pp.1648-1649
• /
• 2007

This paper proposes a very novel method which makes it possible that state feedback controller can be designed for unknown dynamic system with measurable states. The RLS algorithm is used for the identification of input-output relationship. A virtual state space representation is derived from the relationship and the SVM(Support Vector Machines) makes the relationship between actual states and virtual states. A state feedback controller can be designed based on the virtual system and the SVM makes the controller be with actual states. The results of this paper can give many opportunities that the state feedback control can be applied for unknown dynamic systems

• The KIPS Transactions:PartB
• /
• v.9B no.6
• /
• pp.735-744
• /
• 2002

This paper proposes learning performance improvement of support vector machine using the kernel relaxation and the dynamic momentum. The dynamic momentum is reflected to different momentum according to current state. While static momentum is equally influenced on the whole, the proposed dynamic momentum algorithm can control to the convergence rate and performance according to the change of the dynamic momentum by training. The proposed algorithm has been applied to the kernel relaxation as the new sequential learning method of support vector machine presented recently. The proposed algorithm has been applied to the SONAR data which is used to the standard classification problems for evaluating neural network. The simulation results of proposed algorithm have better the convergence rate and performance than those using kernel relaxation and static momentum, respectively.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.11 no.4
• /
• pp.2038-2057
• /
• 2017

Gaussian learning is a new technology in the computational intelligence area. However, this technology weakens the learning ability of a particle swarm and achieves a lack of diversity. Thus, this paper proposes a vector Gaussian learning strategy and presents an effective approach, named particle swarm optimization based on vector Gaussian learning. The experiments show that the algorithm is more close to the optimal solution and the better search efficiency after we use vector Gaussian learning strategy. The strategy adopts vector Gaussian learning to generate the Gaussian solution of a swarm's optimal location, increases the learning ability of the swarm's optimal location, and maintains the diversity of the swarm. The method divides the states into normal and premature states by analyzing the state threshold of the swarm. If the swarm is in the premature category, the algorithm adopts an inertia weight strategy that decreases linearly in addition to vector Gaussian learning; otherwise, it uses a fixed inertia weight strategy. Experiments are conducted on eight well-known benchmark functions to verify the performance of the new approach. The results demonstrate promising performance of the new method in terms of convergence velocity and precision, with an improved ability to escape from a local optimum.

• The Proceedings of the Korean Institute of Illuminating and Electrical Installation Engineers
• /
• v.9 no.3
• /
• pp.88-96
• /
• 1995

High speed elevator requires precise drive included in zero speed at start/stop drive for the high stability and controllability. The vector control techniques, which have been used for the precise operation of induction motor, can be divided into two classes; The indirect vector control by slip frequency and the direct vector control by field orientation. The existing direct vector control technique has a robustness against the change of motor parameter and the existing indirect vector control technique has a strength of control ability in the wide speed range comparatively. This study presents the DTIF (Direct Torque Indirect Flux) controller which has robust movement in the transition state and in about zero and low speed using the control technique in which torque is controlled by the direct vector technique and flux is controled by indirect vector technique. The proposed system is verified by simulation and experiment for driving 3 phase induction motor. The process of transition which is from about zero speed and low speed to high speed is compared and measured to specification of phase voltage, phase current and DC link current. It is verified that DTIF controller show robust and stable speed variation.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.40 no.10
• /
• pp.2080-2089
• /
• 2015

In 3D video compression, a disparity vector (DV) pointing a corresponding block position in an adjacent view is a key coding tool to exploit statistical correlation in multi-view videos. In this paper, neighboring block-based disparity vector (NBDV) is shown with detail algorithm descriptions and coding performance analysis. The proposed method derives a DV from disparity motion vector information, obtained from spatially and temporally neighboring blocks, and provides a significant coding gain about 20% BD-rate saving in a texture-video-first-coding scheme. The proposed DV derivation method is adopted into the recent 3D video coding standards such as 3D-AVC and 3D-HEVC as the state-of-the-art DV derivation method.

• 전기의세계
• /
• v.28 no.3
• /
• pp.57-64
• /
• 1979

The static state estimation are divided into two groups; estimation and detection & identification. This paper centers on detection and identification algorithm. Especially, the identification of line errors is focused on and is performed by the extended W.L.S. algorithm with line swithching states. Here, line switching states mean the discrete values of line admittance which are influenced by unexpected line switching. The numerical results are obtained from the assumption that the noise vector is independent zero mean Gaussian random variables.

• Proceedings of the KIEE Conference
• /
• 1993.07a
• /
• pp.310-312
• /
• 1993

We present the discrete event systems modeled by finite state machines in this paper using the boolean matrices and vectors. We propose a supervisor synthesis method for such boolean discrete-event systems. The proposed supervisor synthesis algorithm is practically implementable, since the size of the state vector in the product system does not increase exponentially with the number of components.

• Journal of the Korean Statistical Society
• /
• v.19 no.2
• /
• pp.182-185
• /
• 1990

Let a p-component vector y have a p-variate normal distribution $N(b\theta, \Sigma), \Sigma$ unknown, b specified, then for testing $\theta = 0$ against general $\theta$, Khatri and Rao (1987) derive a certain t test and obtain its power function. This paper presents a direct derivation of this power function in terms of the original variates unlike Khatri and Rao (1987) who resort to the canonical transformations of the original variates and the conditional distributions.

• Proceedings of the KIEE Conference
• /
• 1999.07c
• /
• pp.1049-1053
• /
• 1999

It is important to measuring and monitoring about state vectors of power system for precise operation control. All state vectors cannot be measured because it is economically disadvantageous, so that some state vectors are determined using state estimator. Determination of observability is a important precondition of power system state estimation because state estimation can be performed when given power system is observable. Recently as time-synchronization technique progress, using the PMU(Phasor Measurement Unit), state vector can be measured directly so that voltage phasor and current phasor measurements can be used for power system estimation. In this paper, observability algorithm is proposed to determinate the observability with real/reactive injection power measurements and real/reactive lineflow power measurements of existing measurement system and with phasor measurements of PMU. The jacobian matrix is newly composed for state estimation with measurements of added PMU, and state estimation is performed with least square estimatior. Comparison between state estimation result of existing measurement system and that of measurement system added PMU is presented.

• Transactions of the Korean Society of Automotive Engineers
• /
• v.5 no.4
• /
• pp.171-178
• /
• 1997

Vehicle interior noise has become increasingly important in this recent years. The noise of a vehicle is one of the important problems in a vehicle design. The interior noise is caused by various vibration sources of vehicle compartment. The booming noise of a vehicle can be significantly affected by vibrations transmitted from engine excitation forces to the vehicle body. Specially, we are interested in the state of transmission paths such as engine mounts to reduce noise in a vehicle compartment. In this paper, we have been calculated the contribution of each transmission path such as engine mounts to interior noise. To identify contribution of each input sources and transmission paths to output, the effectiveness of each input component to output is calculated. Sensitivity analysis is carried out for investigation of contribution to output due to input variations. With the simulation of magnitude and phase change of inputs using vector synthesis diagram, the trends of synthesized output vector are obtained. As a result, we suggested sensitivity analysis of vector synthesis as a technique of prediction and control for noise in a vehicle compartment.