• Proceedings of the KIEE Conference
• /
• 1999.07a
• /
• pp.486-488
• /
• 1999

This paper shows the form of the optimal solution and how to minimize energy of train driving control using SA(simulated annealing). In this paper, we consider the case where a train is to be driven by automatic operation mode along a non-constant gradient, curve and with speed limits. Using the combinational optimal technique, SA, we constructed optimal train driving strategy.

• Journal of Auto-vehicle Safety Association
• /
• v.11 no.3
• /
• pp.30-36
• /
• 2019

This paper suggests a car-following algorithm for urban environment, with multiple target candidates. Until now, advanced driver assistant systems (ADASs) and self-driving technologies have been researched to cope with diverse possible scenarios. Among them, car-following driving has been formed the groundwork of autonomous vehicle for its integrity and flexibility to other modes such as smart cruise system (SCC) and platooning. Although the field has a rich history, most researches has been focused on the shape of target trajectory, such as the order of interpolated polynomial, in simple single-lane situation. However, to introduce the car-following mode in urban environment, realistic situation should be reflected: multi-lane road, target's unstable driving tendency, obstacles. Therefore, the suggested car-following system includes both in-lane preceding vehicle and other factors such as side-lane targets. The algorithm is comprised of three parts: path candidate generation and optimal trajectory selection. In the first part, initial guesses of desired paths are calculated as polynomial function connecting host vehicle's state and vicinal vehicle's predicted future states. In the second part, final target trajectory is selected using quadratic cost function reflecting safeness, control input efficiency, and initial objective such as velocity. Finally, adjusted path and control input are calculated using model predictive control (MPC). The suggested algorithm's performance is verified using off-line simulation using Matlab; the results shows reasonable car-following motion planning.

• The Transactions of the Korean Institute of Electrical Engineers D
• /
• v.54 no.1
• /
• pp.48-55
• /
• 2005

Mobility of an indoor wheeled robot is affected by adhesion force that is related to various floor conditions. When the adhesion force between driving wheels and floor decreases suddenly, the robot begins slip. In order to overcome this slip problem, optimal slip velocity must be decided for stable movement of wheeled robot. First of all, this paper shows that conventional PI control can not be applied to a wheeled robot of the light weight. Secondly, proposed fuzzy logic is applied to the Takagi-Sugeno model for the configuration of fuzzy sets. For the design of Takagi-Sugeno model and fuzzy rule, proposed algorithm uses FCM(Fuzzy c-mean clustering method) algorithm. In additionally, this algorithm adjusts the driving torque for restraining re-slip. The proposed fuzzy logic controller(FLC) is pretty useful with prevention of the slip phenomena for the controller performance in the re-adhesion control strategy, These procedures are implemented using a Pioneer 2-DXE wheeled robot parameter.

• Transactions of the Korean Society of Automotive Engineers
• /
• v.20 no.2
• /
• pp.30-37
• /
• 2012

Pneumatic Active Engine Mount(PAEM) with open-loop control system has been developed to reduce the transmission of the idle-shake vibration induced by engine effectively and economically. A solenoid valve installed between PAEM and vacuum tank is on-off switched by the Pulse Width Modulate(PWM) control signal to decrease the dynamic stiffness of the engine mount. This paper presents the methodology to identify the optimal values of control parameters of a PAEM, i.e, turn-on timing and duty ratio of PWM signal for 6 different idle driving conditions. A scanning algorithm was first applied to the vehicle test to obtain the approximate optimal control parameters minimizing the vibration at front seat rail and at steering wheel. Then the PAEM system identification was fulfilled to find accurate optimal control parameters by using multi-layer neural networks of Levenberg-Marquardt algorithm with vehicle test data.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2009.05a
• /
• pp.627-630
• /
• 2009

The combination of the marine use various multi sensor surveillance system technology with the development of servo motion control algorithm and gyro sensor in six freedom motion is implemented to analyze the movement response. The stabilization of the motion control is developed and Nano driving Precision Pan-Tilt/Gimbal system is obtained from the security positioning cameras with ultra high speed device is used to carry out the exact behavior of the device. The exact behavior will be used to make a essential equipment. Finally the development of the Nano Driving Multi Sensor, Nano of Surveillance System Driving Precision Pan-Tilt/Gimbal optimal design and production, 3-aix Gyro Sensor based with Servo Motion Control algorithm development, Image trace video software and hardware tracking the development is organized and discuss in details. The development of the equipment and the system integration are fully experimented and verified.

• Journal of Institute of Control, Robotics and Systems
• /
• v.19 no.7
• /
• pp.599-604
• /
• 2013

Path planning of mobile robots has a purpose to design an optimal path from an initial position to a target point. Minimum driving time, minimum driving distance and minimum driving error might be considered in choosing the optimal path and are correlated to each other. In this paper, an efficient driving trajectory is planned in a real situation where a mobile robot follows a moving object. Position and distance of the moving object are obtained using a web camera, and the rotation angular and linear velocities are estimated using Kalman filters to predict the trajectory of the moving object. Finally, the mobile robot follows the moving object using a single curvature trajectory by estimating the trajectory of the moving object. Using the estimation by Kalman filters and the single curvature in the trajectory planning, the total tracking distance and time saved amounts to about 7%. The effectiveness of the proposed algorithm has been verified through real tracking experiments.

• The Transactions of the Korean Institute of Electrical Engineers
• /
• v.45 no.1
• /
• pp.74-80
• /
• 1996

This paper describes current controlled PWM technique of PM synchronous motors for a wide variety of speed control applications. They are however limited in their ability to operate in the power limited regime where the available torque is reduced as the speed is increased above its base value. This paper reviews the operation of the PMSM drives when they are constrained to be within the permissible envelope of maximum inverter voltage and current to produce the rated power and to provide this with the highest attainable rotor speed. The optimal field-weakening control algorithm is the use of phase current and d-axis current feedback to reduce of error between the d-axis current command and real current and to improve the torque characteristics. The improved torque characteristics of speed control strategy with optimal field weakening control algorithm is analyzed and the performance is investigated by the computer simulation and experimental results. (author). refs., figs.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.37 no.5
• /
• pp.609-617
• /
• 2013

This paper presents a near-minimum time path planning algorithm for autonomous driving. The problem of near-minimum time path planning is an optimization problem in which it is necessary to take into account not only the geometry of the circuit but also the dynamics of the vehicle. The path planning algorithm consists of a candidate path generation and a velocity optimization algorithm. The candidate path generation algorithm calculates the compromises between the shortest path and the path that allows the highest speeds to be achieved. The velocity optimization algorithm calculates the lap time of each candidate considering the vehicle driving performance and tire friction limit. By using the calculated path and velocity of each candidate, we calculate the lap times and search for a near-minimum time path. The proposed algorithm was evaluated via computer simulation using CarSim and Matlab/Simulink.

• Transactions on Control, Automation and Systems Engineering
• /
• v.3 no.3
• /
• pp.176-180
• /
• 2001

In this papers, we derive a simple kinematic and dynamic formulation of an unmanned electric bicycle. We also check the controllability of the stabilization problem of bicycle. We propose a new control algorithm for the self stabilization of unmanned bicycle with bounded wheel speed and steering angle by using nonlinear control based on the sliding patch and stuck phenomena which was introduced by W. Ham. We also propose a sort of optimal control strategy for steering angle and driving wheel speed that make the length of bicycle\`s path be the shortest. From the computer simulation results, we prove the validity of the proposed control algorithm.

• The Transactions of the Korean Institute of Power Electronics
• /
• v.26 no.6
• /
• pp.397-403
• /
• 2021

In this paper, phase shedding algorithm that measuring to converter's input and output parameter during real-time to control the number of driving converters is proposed. The proposed phase-shedding algorithm drives the DVR power supply with the optimal converter's combination without the loss calculation curve and the lookup table in which the efficiency is measured in advance. The proposed algorithm was implemented through a digital controller and verified in a two-modular LLC converter with a single rated power of 60 Win a 120 W DVR power supply system. Experimental results are presented to prove the validity of the proposed algorithm.