• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.21 no.12
• /
• pp.2081-2089
• /
• 1997

Accurate positioning of the throttle valve of a gasoline engine is required to implement various systems such as traction control system(TCS), cruise control system and drive-by-wire system. In this research, position control system has been developed for the throttle actuator system that uses one throttle actuation for small volume and DC servo motor for fast response. In order to drive the DC motor, PWM signal generator and PWM amplifier were built and interfaced to the motor and controller. Also, time delay control(TDC) law has been used as a basic control algorithm. A method of varying the reference model of the TDC according to the size of change in target throttle angle is proposed here. The simulation and experimental results show that both overshoot prevention and fast response are achieved by the TDC technique with this variable reference model.

• Journal of the Korean Society of Industry Convergence
• /
• v.23 no.4_1
• /
• pp.549-558
• /
• 2020

We describe a new approach to real-time implementation of track record and trajectory control of robotic manipulator with eight joints based on monitoring simulator. Trajectory generator uses the kinematic equations of the arm to convert the task description into a series of set points for each of the joint control loops, while the joint controllers, with simple algorithms for just one joint can move at a fast sampling rate, guaranteeing a smooth motion. The proposed control scheme is robust, fast in computation, and suitable for real-time control. Moreover, this scheme does not require any accurate parameter information, nor values of manipulator parameters and payload. Reliability of the proposed technology is veriefied by monitoring simulation and experimental of robot manipulator for the smart factory with eight degrees of freedom.

• The Transactions of the Korean Institute of Electrical Engineers A
• /
• v.50 no.5
• /
• pp.225-233
• /
• 2001

SIME(SIngle Machine Equivalent) method has been recognized as a useful tool to determine transient stability of power systems. In this paper, SIME method is used to develop the KEPCO transient stability assessment (TSA) tool. A new screening algorithm that can be implemented in SIME method is proposed. The salient feature of the proposed screening algorithm is as follows. First, critical generators are identified by a new index in the early stage of the time domain simulation. Thus, computational time required to find OMIB(One Machine Infinite Bus) can be reduced significantly. Second, clustering critical machines can be performed even in very stable cases. It enables to be avoid extra calculation of time trajectory that is needed in SIME for classifying the stable cases. Finally, using power-angle trajectory and subdividing contingency classification have improved the screening capability. This algorithm is applied to the fast TSA of the KEPCO system.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.13 no.12
• /
• pp.2525-2532
• /
• 2009

In this paper, a fast sphere decoder is proposed for the joint detection of phase-shift keying (PSK) signals in uncoded Vertical Bell Laboratories Layered Space Time (V-BLAST) systems. The proposed decoder, PSD, consists of preprocessing stage and search stage. The search stage of PSD relies on the depth-first branch-and-bound (BB) algorithm with "best-first" orders stored in lookup tables. Simulation results show that the PSD is able to provide the system with the maximum likelihood (ML) performance at low complexity.

• Journal of Korean Society for Quality Management
• /
• v.49 no.4
• /
• pp.539-550
• /
• 2021

Purpose: The purpose of this study is to propose a multivariate CUSUM control chart that can detect the out-of-control state fast while monitoring the cross- and auto- correlated multivariate time series data. Methods: We first build models to estimate the observation data and calculate the corresponding residuals. After then, a multivariate CUSUM chart is applied to monitor the residuals instead of the original raw observation data. Vector Autoregression and Artificial Neural Net are selected for the modelling, and Separated-MCUSUM chart is selected for the monitoring. The suggested methods are tested under a number of experimental settings and the performances are compared with those of other existing methods. Results: We find that Artificial Neural Net is more appropriate than Vector Autoregression for the modelling and show the combination of Separated-MCUSUM with Artificial Neural Net outperforms the other alternatives considered in this paper. Conclusion: The suggested chart has many advantages. It can monitor the complicated multivariate data with cross- and auto- correlation, and detects the out-of-control state fast. Unlike other CUSUM charts finding their control limits by trial and error simulation, the suggested chart saves lots of time and effort by approximating its control limit mathematically. We expect that the suggested chart performs not only effectively but also efficiently for monitoring the process with complicated correlations and frequently-changed parameters.

• Journal of Information Technology Applications and Management
• /
• v.26 no.1
• /
• pp.53-64
• /
• 2019

The purpose of this study is to find out the fast delivery route that several drones return a truck again after departing from it for delivery locations at each cluster while the truck goes through the cluster composed of several delivery locations. The main issue is to reduce the total delivery time composed of the delivery time by relatively slow trucks via clusters and the sum of maximum delivery times by relatively fast drones in each cluster. To solve this problem, we use a three-step heuristic approach. First, we cluster the nearby delivery locations with minimal number of clusters satisfying a constraint of drone flight distance to set delivery paths for drones in each cluster. Second, we set an optimal delivery route for a truck through centers of the clusters using the TSP model. Finally, we find out the moved centers of clusters while maintaining the delivery paths for the truck and drones and satisfying the constraint of drone flight. distance in the two-dimensional region to reduce the total delivery time. In order to analyze the effect of this study model according to the change of the number of delivery locations, we developed a R-based simulation prototype and compared the relative efficiency, and performed paired t-test between TSP model and the cluster-based models. This study showed its excellence through this experimentation.

• The Transactions of the Korean Institute of Electrical Engineers D
• /
• v.53 no.12
• /
• pp.793-798
• /
• 2004

In this paper, the problem of adaptively identifying time-varying nonlinear systems is considered. For that purpose, the discrete time-varying Volterra series is employed as a system model, and the filtered weighted least squares (FWLS) algorithm, developed for adaptive identification of linear time-varying systems, is utilized for the adaptive identification of time-varying quadratic Volterra systems. To demonstrate the performance of the proposed approach, some simulation results are provided. Note that the FWLS algorithm, decomposing the conventional weighted basis function (WBF) algorithm into a cascade of two (i.e., estimation and filtering) procedures, leads to fast parameter tracking with low computational burden, and the proposed approach can be easily extended to the adaptive identification of time-varying higher-order Volterra systems.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
• /
• 2001.11b
• /
• pp.46-51
• /
• 2001

For Fast Real-time Recognition of Nonlinear Error Data, a new Neural Network algorithm which recognized the map in real time is proposed. The proposed neural network technique is the real time computation method through the inter-node diffusion, In the network, a node corresponds to a state in the quantized input space. Each node is composed of a processing unit and fixed weights from its neighbor nodes as well as its input terminal. The most reliable algorithm derived for real time recognition of map, is a dynamic programming based algorithm based on sequence matching techniques that would process the data as it arrives and could therefore provide continuously updated neighbor information estimates. Through several simulation experiments, real time reconstruction of the nonlinear map information is processed,

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
• /
• 2001.11a
• /
• pp.46-51
• /
• 2001

For Fast Real-time Recognition of Nonlinear Error Data, a new Neural Network algorithm which recognized the map in real time is proposed. The proposed neural network technique is the real time computation method through the inter-node diffusion. In the network, a node corresponds to a state in the quantized input space. Each node is composed of a processing unit and fixed weights from its neighbor nodes as well as its input terminal. The most reliable algorithm derived for real time recognition of map, is a dynamic programming based algorithm based on sequence matching techniques that would process the data as it arrives and could therefore provide continuously updated neighbor information estimates. Through several simulation experiments, real time reconstruction of the nonlinear map information is processed.

• Journal of the Korean Society of Visualization
• /
• v.2 no.2
• /
• pp.8-15
• /
• 2004

With all the recent progresses in computer hardware and software technology, the animation of fluids in real-time is still among the most challenging issues of computer graphics. The fluid animation is carried out in two steps - the physical simulation of fluids immediately followed by the visual rendering. The physical simulation is usually accomplished by numerical methods utilizing the particle dynamics equations as well as the fluid mechanics based on the Navier-Stokes equations. Particle dynamics method is usually fast in calculation, but the resulting fluid motion is conditionally unrealistic. The methods using Navier-Stokes equation, on the contrary, yield lifelike fluid motion when properly conditioned, yet the complexity of calculation restrains this method from being used in real-time applications. This article presents a rapid fluid animation method by using the continuum-based fluid mechanics and the enhanced particle dynamics equations. For real-time rendering, pre-integrated volume rendering technique was employed. The proposed method can create realistic fluid effects that can interact with the viewer in action, to be used in computer games, performances, installation arts, virtual reality and many similar multimedia applications.