• Journal of Auto-vehicle Safety Association
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• v.5 no.1
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• pp.62-68
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• 2013

This paper describes development of 4 Wheel Drive (4WD) Electric Vehicle (EV) based driving control algorithm for severe driving situation such as icy road or disturbance. The proposed control algorithm consists three parts : a supervisory controller, an upper-level controller and optimal torque vectoring controller. The supervisory controller determines desired dynamics with cornering stiffness estimator using recursive least square. The upper-level controller determines longitudinal force and yaw moment using sliding mode control. The yaw moment, particularly, is calculated by integration of a side-slip angle and yaw rate for the performance and robustness benefits. The optimal torque vectoring controller determines the optimal torques each wheel using control allocation method. The numerical simulation studies have been conducted to evaluated the proposed driving control algorithm. It has been shown from simulation studies that vehicle maneuverability and lateral stability performance can be significantly improved by the proposed driving controller in severe driving situations.

• Journal of Drive and Control
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• v.14 no.2
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• pp.16-22
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• 2017

This paper presents the algorithm of an adaptive model-free-control-based steering control for multi-axle all-terrain cranes for which the recursive least squares with forgetting are applied. To optimally control the actual system in the real world, the linear or nonlinear mathematical model of the system should be given for the determination of the optimal control inputs; however, it is difficult to derive the mathematical model due to the actual system's complexity and nonlinearity. To address this problem, the proposed adaptive model-free controller is used to control the steering angle of a multi-axle crane. The proposed model-free control algorithm uses only the input and output signals of the system to determine the optimal inputs. The recursive least-squares algorithm identifies first-order systems. The uncertainty between the identified system and the actual system was estimated based on the disturbance observer. The proposed control algorithm was used for the steering control of a multi-axle crane, where only the steering input and the desired yaw rate were employed, to track the reference path. The controller and performance evaluations were constructed and conducted in the Matlab/Simulink environment. The evaluation results show that the proposed adaptive model-free-control-based steering-control algorithm produces a sound path-tracking performance.

• Journal of Auto-vehicle Safety Association
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• v.5 no.1
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• pp.50-55
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• 2013

When it comes to commercial vehicles, their unique characteristics - center of gravity, size, weight distribution - make them particularly vulnerable to rollover. On top of that, conventional heavy vehicle brake exhibits longer actuation delays caused in part by long air lines from brake pedal to tires. This paper describes rollover prevention algorithm that copes with the characteristics of commercial vehicles. In regard of compensating for high actuating delay, predicted rollover index with short preview time has been designed. Moreover, predicted rollover index with longer preview time has been calculated by using road curvature information based on environment information. When rollover index becomes larger than specific threshold value, desired braking force is calculated in order to decrease the index. At the same time, braking force is distributed to each tire to make yaw rate track desired value.

• Journal of Auto-vehicle Safety Association
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• v.9 no.3
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• pp.19-23
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• 2017

This paper presents a lateral driver model with neuromuscular system to evaluate the performance of electric power steering (EPS). Output of most previously developed driver models is steering angle. However, in order to evaluate EPS system, driver model which results in steering torque output is needed. The proposed lateral driver model mainly consists of 2 parts: desired steering angle calculation and conversion of steering angle into steering torque. Desired steering angle calculation part results in steering angle to track desired yaw rate for path tracking. Conversion of steering angle into torque is consideration with neuromuscular system. The proposed driver model is investigated via actual driving data. Compared to other algorithms, the proposed algorithm shows similar pattern of steering angle with human driver. The proposed driver can be utilized to efficiently evaluate EPS system in simulation level.

• Transactions of the Korean Society of Automotive Engineers
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• v.8 no.6
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• pp.194-207
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• 2000

In this paper, we suggest a vision-based lane change control system, which can be applied on the straight road, without additional sensors such as a yaw rate sensor and a lateral accelerometer. In order to reduce the image processing time, we predict a reference line position during lane change using the lateral dynamics and the inverse perspective mapping. The sliding mode control algorithm with a boundary layer is adopted to overcome variations of parameters that significantly affects a vehicle`s lateral dynamics and to reduce chattering phenomenon. However, applying the sliding mode control to the system with a long sampling interval, the stability of a control system may seriously be affected by the sampling interval. Therefore, in this paper, a look ahead offset has been used instead of a lateral offset to reduce the effect of the long sampling interval due to the image processing time. The control algorithm is developed to follow the desired trajectory designed in advance. In the design of the desired trajectory, we take account of the constraints of lateral acceleration and lateral jerk for ride comfort. The performance of the suggested control system is evaluated in simulations as well as field tests.

• Journal of Mechanical Science and Technology
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• v.20 no.7
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• pp.981-992
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• 2006

In this paper, a lateral vehicle control using the concept of control configured vehicle (CCV) is presented. The control objectives for the lateral dynamics of a vehicle include the ability to follow a chosen variable without significant motion change in other specified variables. The analysis techniques for decoupling of the aircraft motions are utilized to develop vehicle lateral control with advanced mode. Vehicle lateral dynamic is determined to have the steering input and control torque input. The additional vehicle modes are also defined to using CCV concept. We use right eigenstructure assignment techniques and command generator tracker to design a control law for an lateral vehicle dynamics. The desired eigenvectors are chosen to achieve the desired decoupling (i.e., lateral direction speed and yaw rate). The command generator tracker is used to ensure steady-state tracking of the driver's command. Finally, the developed design is utilized by using the lateral vehicle dynamic with four wheel.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.10
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• pp.1002-1011
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• 2006

In this paper, a lateral vehicle control using the concept of control configured vehicle(CCV) is presented. The control objectives for the lateral dynamics of a vehicle include the ability to commend a chosen variable without significant motion change in other specified variables. The analysis techniques fur decoupling of the aircraft motions are utilized to develop vehicle lateral control with advanced mode. Vehicle lateral dynamic is determined to have the steering input and control torque input. The additional vehicle modes are also defined to using CCV concept. We use right eigenstructure assignment techniques and command generator tracker to design a control law for an lateral vehicle dynamics. The desired eigenvectors are chosen to achieve the desired decoupling(i.e., lateral direction speed and yaw rate). The command generator tracker is used to ensure steady-state tracking of the driver's command. Finally, the developed design is utilized by using the lateral vehicle dynamic with four wheel.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.26 no.12
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• pp.2519-2526
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• 2002

A disturbance observer-based vehicle stability controller is proposed in this paper. The lumped disturbance to the vehicle yaw rate dynamics caused by the uncertain factors such as uncertain tire forces and parameters is estimated by the disturbance observer, which is utilized by the robust controller to stabilize the lateral dynamics of the vehicle. The dynamics of the hydraulic actuator is incorporated in the vehicle stability controller design using the model reduction technique. Modular control design methodology is adopted to effectively deal with the mismatched uncertainty. Simulation results indicate that the proposed disturbance observer-based vehicle stability controller can achieve the desired reference tracking performance as well as sufficient level of robustness.

• Aerospace Engineering and Technology
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• v.6 no.2
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• pp.1-7
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• 2007

The control design for attitude and yaw rate of 40 % scaled SMART UA Vhas been performed. Analytic selection method for a control gain is proposed to meet the design specification of desired time response considering stability margin. The sliding mode attitude controller is also proposed and compared with the simulation results of a linear controller. Additionally, a velocity and height tracking controller is devised to prepar for the flight test.

• Journal of the Society of Naval Architects of Korea
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• v.60 no.3
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• pp.165-174
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• 2023

Unmanned Surface Vehicle (USV)'s berthing and unberthing is the most difficult maneuvering tasks and have the highest risk of accidents. In this paper, we designed a berthing/unberthing control algorithm given human joystick command for an USV equipped with a waterjet and a bow thruster. The berthing and unberthing maneuvers are performed remotely by a joystick operator at the Ground Control Center (GCC) where the status of USV and environmental situation can be monitored. We interpret the human joystick commands into USV's desired speed, yaw rate, and heading angle commands. next, we developed a control algorithm for the desired target values of MIMO actuators (engine speed, bucket step, nozzle angle, and bow thruster state) to follow the interpreted commands. The validity of the control algorithm is confirmed through simulations and sea trials at Gwang Am port.