• Proceedings of the Korean Society of Precision Engineering Conference
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• 1992.10a
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• pp.161-165
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• 1992

The important properties of industrial scale or weighing machine operated in production lines are quickness and precision. This paper presents an algorithm which meets the importance. The algorithm of Recursive Least Squares Regression is described for the weighing system simulated as a dynamic model of the second order. Using the model and the algorithm, model parameters and then the mass being weighed can be determined from the step input. The performance of the algorithm is illustrated in digital simulation. Discussions have been extended to the development of fast converging algorithm. It turns out that the algorithm shows several desirable features suitable for microcomputer assisted realtime signal processing.

• Proceedings of the KIPE Conference
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• 1998.07a
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• pp.239-244
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• 1998

We propose a nonlinear feedback controller that can control the induction motors with high dynamic performance by means of decoupling of motor speed and rotor flux. A new recursive adaptation algorithm for rotor resistance which can be applied to our nonlinear feedback controller is also presented in this paper. Some simulation results show that the adaptation algorithm for rotor resistance is robust against the variation of stator resistance and mutual inductance. In addition, it is computationally simple and has small estimation errors.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.2719-2724
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• 2003

In this paper, we deal with the kinematic and dynamic modeling of hybrid robotic systems that are constructed by combination of parallel and serial modules or series of parallel modules. Previously, open-tree structure has been employed for dynamic modeling of hybrid robotic systems. Though this method is generally used, however, it requires expensive computation as the size of the system increases. Therefore, we propose an efficient dynamic modeling methodology for hybrid robotic systems. Initially, the dynamic model for the proximal module is obtained with respect to the independent joint coordinates. Then, in order to represent the operational dynamics of the proximal module, we model virtual joints attached at the top platform of the proximal module. The dynamic motion of the next module exerts dynamic forces to the virtual joints, which in fact is equivalent to the reaction forces exerted on the platform of the lower module by the dynamics of the upper module. Then, the dynamic forces at the virtual joints are distributed to the independent joints of the proximal module. For multiple modules, this scheme can be constructed as a recursive dynamic formulation, which results in reduction of the complexness of the open-tree structure method for modeling of hybrid robotic systems. Simulation for inverse dynamics is performed to validate the proposed modeling algorithm.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.408-413
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• 2005

A new methodology for discrete non-Gaussian probability density estimation is investigated in this paper based on a dynamic Bayesian network (DBN) and kernel functions. The estimator consists of a DBN in which the transition distribution is represented with kernel functions. The estimator parameters are determined through a recursive learning algorithm according to the maximum likelihood (ML) scheme. A discrete-type Poisson distribution is generated in a simulation experiment to evaluate the proposed method. In addition, an unknown probability density generated by nonlinear transformation of a Poisson random variable is simulated. Computer simulations numerically demonstrate that the method successfully estimates the unknown probability distribution function (PDF).

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.8
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• pp.1492-1501
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• 2011

A wide-area protection intelligent technique has been used to improve a reliability in power systems and to prevent a blackout. Nowadays, voltage and current phasor estimation has been executed by GPS-based synchronized PMU, which has become an important way of wide-area blackout protection for the prevention of expending faults in power systems. As this technique has the difficulties in collecting and sharing of information, there have been used a FNET method for the wide-area intelligent protection. This technique is very useful for the prediction of the inception fault and for the prevention of fault propagation with accurate monitoring frequency and frequency deviation. It consists of FDRs and IMS. It is well known that FNET can detect the dynamic behavior of system and obtain the real-time frequency information. Therefore, FDRs must adopt a optimal frequency estimation method that is robust to noise and fault. In this paper, we present comparative studies for the frequency estimation method using IRDWT(improved recursive discrete wavelet transform), for the frequency estimation method using FRDWT(fast recursive discrete wavelet transform). we used the Republic of Korea 345kV power system modeling data by EMTP-RV. The user-defined arbitrary waveforms were used in order to evaluate the performance of the proposed two kinds of RDWT. Also, the frequency variation data in various range, both large range and small range, were used for simulation. The simulation results showed that the proposed frequency estimation technique using FRDWT can be the optimal frequency measurement method applied to FDRs.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.25 no.5
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• pp.455-463
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• 2012

In this study, we calculate dynamic constrained force of tower top and blade root of a floating offshore wind turbine. The floating offshore wind turbine is multibody system which consists of a floating platform, a tower, a nacelle, and a hub and three blades. All of these parts are regarded as a rigid body with six degree-of-freedom(DOF). The platform and the tower are connected with fixed joint, and the tower, the nacelle, and the hub are successively connected with revolute joint. The hub and three blades are connected with fixed joint. The recursive formulation is adopted for constructing the equations of motion for the floating wind turbine. The non-linear hydrostatic force, the linear hydrodynamic force, the aerodynamic force, the mooring force, and gravitational forces are considered as external forces. The dynamic load at the tower top, rotor shaft, and blade root of the floating wind turbine are simulated in time domain by solving the equations of motion numerically. From the simulation results, the mutual effects of the dynamic response between the each part of the floating wind turbine are discussed and can be used as input data for the structural analysis of the floating offshore wind turbine.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.26 no.4
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• pp.247-254
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• 2013

In this paper, dynamic response analysis of a heave compensation system is performed for offshore drilling operations based on multibody dynamics. With this simulation, the efficiency of the heave compensation system can be virtually confirmed before it is applied to drilling operations. The heave compensation system installed on a semi-submersible platform consists of a passive and an active heave compensator. The passive and active heave compensator are composed of several bodies that are connected to each other with various types of joints. Therefore, to carry out the dynamic response analysis, the dynamics kernel was developed based on mutibody dynamics. To construct the equations of motion of the multibody system and to determine the unknown accelerations and constraint forces, the recursive Newton-Euler formulation was adapted. Functions of the developed dynamics kernel were verified by comparing them with other commercial dynamics kernels. The hydrostatic force with nonlinear effects, the linearized hydrodynamic force, and the pneumatic and hydraulic control forces were considered as the external forces that act on the platform of the semi-submersible rig and the heave compensation system. The dynamic simulation of the heave compensation system of the semi-submersible rig, which is available for drilling operations with a 3,600m water depth, was carried out. From the results of the simulation, the efficiency of the heave compensation system were evaluated before they were applied to the offshore drilling operations. Moreover, the calculated constraint forces could serve as reference data for the design of the mechanical system.

• Journal of the Korean Society of Safety
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• v.9 no.4
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• pp.125-131
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• 1994

This paper proposes a dynamic recursive model with the effect analysis of machine state considering human factor(human skillfulness) In a single lot man-machine production system. This model obtained using Kalman Filtering Algorithm Is based on input state, output state, machine state. For sensitivity analysis, this model constructed is examined according to the impact of human skillfulness with computer simulation. The model studied in this paper has a great advance from the point of view a combination of three factors( human engineering, dynamic control theory, quality control ) and can also be extended in several applications.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2002.05a
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• pp.1093-1098
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• 2002

Dynamic behaviors of the Korean High-speed Train(KHST) have been analyzed to investigate the performance on the stability, the safety and the ride comfort. Multi-body dynamics analysis program using Recursive method, called RecurDyn, have been employed in the numerical simulation. To model the wheel-rail contact, the RecurDyn uses its built-in module which uses the square root creep law. The accuracy of the rail module in RecurDyn. however, decreases in the analysis of flange contact because it linearizes the shape of the wheel and rail. To solve this problem, a nonlinear contact theory have been developed that considers the profiles of the wheel and rail. The results show that the KHST still needs more stability. The problem should be solved by the examinations of module and modeling.

• Communications for Statistical Applications and Methods
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• v.25 no.1
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• pp.29-42
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• 2018

We combine the integer-valued GARCH(1, 1) model with a generalized regime-switching model to propose a dynamic count time series model. Our model adopts Markov-chains with time-varying dependent transition probabilities to model dynamic count time series called the generalized regime-switching integer-valued GARCH(1, 1) (GRS-INGARCH(1, 1)) models. We derive a recursive formula of the conditional probability of the regime in the Markov-chain given the past information, in terms of transition probabilities of the Markov-chain and the Poisson parameters of the INGARCH(1, 1) process. In addition, we also study the forecasting of the Poisson parameter as well as the cumulative impulse response function of the model, which is a measure for the persistence of volatility. A Monte-Carlo simulation is conducted to see the performances of volatility forecasting and behaviors of cumulative impulse response coefficients as well as conditional maximum likelihood estimation; consequently, a real data application is given.