• 전기의세계
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• v.21 no.3
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• pp.31-40
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• 1972

This study intends to investigate the optimal switching modes of a double-capacitive thermal system under different constraints on the state and the control variable, by the application of the Pontryagin's Minimum Principle. Throughout the development, the control effort is assumed to have two modes of state: M or zero and the terminal times being fixed. In the first part of this study, the Principle is discussed under various conditions for this particular problem, with different criterion functions and in the same time imposing a certain constraints; i) on the terminal states, ii) on functions of the terminal states. Depending upon the upper bound value of the control vector, possible driving modes of the states are studied from which particular optimal driving modes are extracted so as to meet the specified constraints and boundary conditions imposed in the problem. Numerical solutions are evaluated for an over0damped, double-capacitive thermal plant and the optimal solutions: the switching mode, the optimal switching time, and the control effort are compared with the analytical results, in the second part of this work, to confirm the development.

• Proceedings of the KSR Conference
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• 2011.05a
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• pp.888-894
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• 2011

This paper is a study of optimal train driving strategy to minimize the energy consumption. Optimal driving strategy can be analyzed as an optimal problem which have constraints by using Largrangian Function and Kuhn-Tucker condition. We simulate the section between Konkuk University Station and Seongsu Station which is on outer circle line of the Seoul Metro line No.2 by using MATLAB and consider the straight level track and the speed limit.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2804-2807
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• 2000

This paper suggests a method of the forward dynamic analysis for the computer simulation on the analysis of the dynamic behavior for biped walking robot. The equations f motion of the system or the simulation are constructed by using the Method of the multibody dynamics which is powerful method for modeling of the complex biped system. For the simplicity of simulation, we consider that the sole of the contacting foot is affected by the reaction forces for tree structure system topology instead of the addition or deletion of the kinematic constraints. The ground reaction forces can be modeled using the simple spring and damper model at the three contacting points on the sole of the foot. For minimizing the errors of numerical integration, the number of equations of motion is minimized by adding the driving constraints or a controller instead of the direct driving torques.

• Transactions of the Korean Society of Mechanical Engineers
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• v.11 no.2
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• pp.222-233
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• 1987

A dynamic modeling procedure for developing a control model of the driving system of a heavy industrial vehicle is presented. The dynamic model is derived by applying generalized Lagrangian equations to each component of the system and imposing kinematic relations between components as constraints. In order to obtain the control model, a few assumptions are made for the simplification of the nonlinear and complicated model, which is justified by the comparison of the simulation results of the original full nonlinear model and the simplified control model.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2003.06a
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• pp.709-712
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• 2003

The existing technical limitation makes engineer imitate nature to solve engineering problems. Recently Micro Air Vehicle(MAV) imitating the mechanism of birds or insects is being developed. Especially Ultra Flite supported by DARPA is studying hummingbird aerodynamics to relate that information to MAV. To drive MAV bender piezoelectric(PZT) actuators are used due to the convinience of control and the small size. But the displacement of the PZT actuators are very small, and the wing driving mechanism which amplifies the stroke generated by the PZT actuators has constraints in design and manufacture because of the small dimension. In this paper a wing design concept and a efficient driving mechanism are proposed. Electroactive polymers(EAPs) are used as wing mechanism actuators. Using OpenGL the mechanisms are simulated graphically. Also a prototype actuator is being developed and verified by digital Mockup with CATIA. Basic kinematics of the mechanism is studied.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.41 no.9
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• pp.869-876
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• 2017

Analysis of actuating forces and joint reaction forces are essential to determine the capacity of actuators, to control the mechanical system and to design its components. This paper presents an algorithm that calculates actuating forces(or torques), depending on the various types of driving constraints, in order to produce a given system motion in the joint coordinate space. The joint coordinates are used as the generalized coordinates of a kinematic system. System equations of motion and constraint acceleration equations are transformed from the Cartesian coordinate space to the joint coordinate space using the velocity transformation method. A numerical example is carried out to verify the algorithm proposed.

• Proceedings of the KSME Conference
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• 2000.11a
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• pp.659-664
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• 2000

Fuel-consumption and catalyst-out emissions of a parallel hybrid electric vehicle are affected by operating region of an engine. In many researches, It is generally known that it is profitable in fuel- consumption to operate engine in OOL(Optimal Operating Line). We established the mathematical model of a parallel hybrid electric vehicle, which is linear time-invariant. To operate an engine in OOL, we applied RHC(Receding Horizon Control) to the driving control of a parallel hybrid electric vehicle. And it is known that the RHC has advantages such as good tracking performance under state and control constraints. This RHC is obtained by using linear matrix inequality (LMI) optimization. In this paper, there are three main topics. First, without state and control constraints, the optimal tracking of OOL was simulated. Second, with state and control constraints by engine and motor performances, the optimal tracking of OOL was simulated. In the last, we studied on the optimal gear ratio. That is to say, we combined the RHC and the iterative simulation to extract the optimal gear ratio. In this simulation, the vehicle is commanded to track the reference vehicle trajectory and the engine is operated in the optimal operating region which is made by the state constraints.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.3
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• pp.199-209
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• 2015

This paper presents a model predictive control (MPC) approach to control the steering angle in an autonomous vehicle. In designing a highly automated driving control algorithm, one of the research issues is to cope with probable risky situations for enhancement of safety. While human drivers maneuver the vehicle, they determine the appropriate steering angle and acceleration based on the predictable trajectories of surrounding vehicles. Likewise, it is required that the automated driving control algorithm should determine the desired steering angle and acceleration with the consideration of not only the current states of surrounding vehicles but also their predictable behaviors. Then, in order to guarantee safety to the possible change of traffic situation surrounding the subject vehicle during a finite time-horizon, we define a safe driving envelope with the consideration of probable risky behaviors among the predicted probable behaviors of surrounding vehicles over a finite prediction horizon. For the control of the vehicle while satisfying the safe driving envelope and system constraints over a finite prediction horizon, a MPC approach is used in this research. At each time step, MPC based controller computes the desired steering angle to keep the subject vehicle in the safe driving envelope over a finite prediction horizon. Simulation and experimental tests show the effectiveness of the proposed algorithm.

• KIPS Transactions on Computer and Communication Systems
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• v.12 no.3
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• pp.93-102
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• 2023

Data processing through the cloud causes many problems, such as latency and increased communication costs in the communication process. Therefore, many researchers study edge computing in the IoT, and autonomous driving is a representative application. In indoor self-driving, unlike outdoor, GPS and traffic information cannot be used, so the surrounding environment must be recognized using sensors. An efficient autonomous driving system is required because it is a mobile environment with resource constraints. This paper proposes a machine-learning method using neural networks for autonomous driving in an indoor environment. The neural network model predicts the most appropriate driving command for the current location based on the distance data measured by the LiDAR sensor. We designed six learning models to evaluate according to the number of input data of the proposed neural networks. In addition, we made an autonomous vehicle based on Raspberry Pi for driving and learning and an indoor driving track produced for collecting data and evaluation. Finally, we compared six neural network models in terms of accuracy, response time, and battery consumption, and the effect of the number of input data on performance was confirmed.

• Transactions of the Korean Society of Automotive Engineers
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• v.5 no.5
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• pp.73-85
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• 1997

An automatic transmission is an important element of automotive power systems that allows a driving convenience. Compared to a manual transmission, however, it has a few problems in efficiency, shift feel, and maintenance. To improve these, it is imperative to understand the dynamics of automatic transmissions. This paper develops a dynamically-correct model of an automatic transmission, using the bond graph method. The bond graph method is ideally suited for modeling power systems, because the method is based on generalized power variables. The bond graph method is capable of providing correct dynamic constraints and kinematic constraints, as well as the governing differential equations of motion. The bond graph method is applied to 1-4 in-gear ranges, as well as various upshifts and downshifts of an automatic transmission, which allows an accurate simulation of an automatic transmission. Conventional automatic transmission models have no dynamic constraint, which do not allow correct simulation studies.