• Journal of Drive and Control
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• v.21 no.3
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• pp.46-55
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• 2024

In the agricultural machinery field, load analysis is mostly done through field tests. However, field tests are time-consuming and costly. There are also limitations in test conditions due to weather conditions. To overcome these environmental limitations, research on load analysis through simulation in a virtual environment is actively being conducted. This study aimed to select the most appropriate soil particle size for modeling by analyzing the effect of soil particle size on the prediction of draft force of the implement using simulation and soil particle modeling in a virtual environment with the discrete element method (DEM) software. The accuracy was verified by simulating the draft force for the same moving speed by soil particle size. For soil particle modeling, DEM soil modeling was performed by designing soil property measurement procedure. Soil particle correction was performed with a virtual vane shear test. Average DEM simulation results showed an error of 27.39% (19.43~40.66%) compared to actual measured data. The possibility of improvement was confirmed through additional research. Results of this study provide useful information for selecting soil particle size in soil modeling using DEM from the perspective of agricultural machinery research.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.12
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• pp.3227-3234
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• 1996

This paper proposes a new absorbing boundary condition(ABC) for the FDTD simulation of waveguide problems. It is based on the exact analytic expression for the time domain EM wave propatation in the waveguide. The ABC derived from the expression has a convolution form whose kernel (the discrete Green's function) has a simple, closed form formula. Also, it is applicable to the wide variety of waveguide types with conducting boundaries and complex cross-sectional shapes.

• ETRI Journal
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• v.37 no.1
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• pp.175-185
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• 2015

This paper presents a system-of-systems (SoS) approach to the formal modeling of a cyber-physical system (CPS) for simulation-based analysis. The approach is based on a convergence technology for modeling and simulation of a highly complex system in which SoS modeling methodology, hybrid systems modeling theory, and simulation interoperation technology are merged. The methodology maps each constituent system of a CPS to a disparate model of either continuous or discrete types. The theory employs two formalisms for modeling of the two model types with formal specification of interfaces between them. Finally, the technology adapts a simulation bus called DEVS BUS whose protocol synchronizes time and exchange messages between subsystems simulation. Benefits of the approach include reusability of simulation models and environments, and simulation-based analysis of subsystems of a CPS in an inter-relational manner.

• Geomechanics and Engineering
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• v.28 no.4
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• pp.421-435
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• 2022

The necessity of estimating the time and cost required for tunnel construction has led to extensive research in this regard. Since geological conditions are significant factors in terms of time and cost of road tunnels, considering these conditions is crucial. Uncertainties about the geological conditions of a tunnel alignment cause difficulties in planning ahead of the required construction time and costs. In this paper, the continuous-space, discrete-state Markov process has been used to predict geological conditions. The Monte-Carlo (MC) simulation (MCS) method is employed to estimate the construction time and costs of a road tunnel project using the input data obtained from six tunneling expert questionnaires. In the first case, the input data obtained from each expert are individually considered and in the second case, they are simultaneously considered. Finally, a comparison of these two modes based on the technique presented in this article suggests considering views of several experts simultaneously to reduce uncertainties and ensure the results obtained for geological conditions and the construction time and costs.

• Proceedings of the KIEE Conference
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• 1996.07a
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• pp.309-311
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• 1996

In this paper, we propose two types of novel discrete time current control methods of modified fixed band hysteresis control and optimal control for Parallel Resonant DC Link Inverters(PRDCLI). Because zero bus voltage intervals are generated on the DC link of PRDCLI, we can obtain the information of counter electromotive force(emf) by a simple estimation strategy. The proposed current controllers predict the currents of the next resonant cycle using the obstained information of counter emf and the average values of DC link voltages. The computer simulation results for a simple equivalent circuit of induction motor show that the proposed control methods are more effective than conventional methods.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.12
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• pp.1133-1145
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• 2000

In this paper a model following flight control system design using the discrete time quasi-sliding mode control method is described. The quasi-sliding mode is represented as the sliding mode band, not as the sliding surface. The quasi-sliding mode control is composed of the equivalent control for the nominal system without uncertainties and disturbances and the additive control compensating the uncertainties and disturbances. The linearized plant on the equilibrium point is used in designing a flight control system and the stability conditions are proposed for the model uncertainties. Pseudo-state feedback control which uses the model variables for the unmeasured states is proposed. The proposed method is applied to the design of the roll attitude and pitch load factor control of a bank-to-turn missile. The performance is verified through the nonlinear six degrees of freedom flight simulation.

• Proceedings of the KIEE Conference
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• 1994.07a
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• pp.468-471
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• 1994

This paper presents the digital implementation of an optimal and robust VSS controller with sliding observer. Firstly, a discrete-time VSS control law which enables the system state to move into a sliding sector where the closed-loop system is stable is designed. Then optimal control theory is used to design an optimal sliding sector. Secondly, a sliding observer which provide robust state estimation against model-plant mismatches due to parameter uncertainties is designed for the sampled-data multivariable systems. Finally, modified sliding observer which effectively reduce chattering of state variables in state estimation was proposed. The proposed scheme was applied 10 a two degree of freedom inverted pendulum with passive joint to verify robust motion control. Computer simulation results confirm the viability of the proposed observer-based controller.

• Wind and Structures
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• v.5 no.2_3_4
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• pp.257-266
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• 2002

In the recent years flow around bridges are investigated using computer modeling. Selvam (1998), Selvam and Bosch (1999), Frandsen and McRobie (1999) used finite element procedures. Larsen and Walther (1997) used discrete vorticity procedure. The aeroelastic instability is a major criterion to be checked for long span bridges. If the wind speed experienced by a bridge is greater than the critical wind speed for flutter, then the bridge fails due to aeroelastic instability. Larsen and Walther (1997) computed the critical velocity for flutter using discrete vortex method similar to wind tunnel procedures. In this work, the critical velocity for flutter will be calculated directly (free oscillation procedure) similar to the approaches reported by Selvam et al. (1998). It is expected that the computational time required to compute the critical velocity using this approach may be much shorter than the traditional approach. The computed critical flutter velocity of 69 m/s is in reasonable comparison with wind tunnel measurement. The no flutter and flutter conditions are illustrated using the bridge response in time.

• 제어로봇시스템학회:학술대회논문집
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• 1994.10a
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• pp.753-757
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• 1994

In control system design, whether the various subsystems are in discrete time or continuous time, the state space is usually regarded as a continuum. However, when the system is implemented, some subsystems may have a state space which is a subset of finite computer arithmetic. This is an important concern if a subsystem has chaotic behaviour, because it is theoretically possible for rich and varied motions in a continuum to collapse to trivial and degenerate behaviour in a finite and discrete state space [5]. This paper discusses new ways to describe these effects and reports on computer experiments which document and illustrate such collapsing behaviour.

• Proceedings of the KIEE Conference
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• 1999.07b
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• pp.933-935
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• 1999

In this paper, we present model predictive control scheme based on neural network to control discrete-time chaotic systems. We use a feedforward neural network as nonlinear prediction model. The training algorithm used is an adaptive backpropagation algorithm that tunes the connection weights. And control signal is obtained by using gradient descent (GD), some kind of LMS method. We identify that the system identification results through model prediction control have a great effect on control performance. Finally, simulation results show that the proposed control algorithm performs much better than the conventional controller.