Seunghwan Baek

Application of a sliding mode control to anti-lock brake system

This paper presents application method of a sliding mode wheel slip controller for ABS that improves the vehicle response and increases the safety on slippery road. Sliding mode wheel slip controller receives wheel slip ratio, vehicle velocity, longitudinal acceleration, and tire forces from vehicle model to generate braking pressures. In general, two solenoid valves, so called normal open and normal close valves, have been used to generate the hydraulic pressure necessary to generate proper braking force. In this paper, the valve operating method is proposed to implement the sliding mode control output in hydraulic unit of the ABS. The control performance is verified by using a HILS System that has a vehicle braking system controlled with On/Off solenoid valves.

A study on the welding seam tracking by using Laser Vision Sensor

This paper suggests one of the pre-measurement methods to trace a welding path. The welding path is measured by the LVS (Laser Vision Sensor). A line laser is projected on the weldment and a vision sensor captures images. Center points of the welding path are detected through image processing. Measured image coordinates are transformed to robot coordinates by coordinate transformations. The experimental structure is composed by 1-axis robot, cylinder, LVS. The rolling cylinder that is carved V-groove generates the continuous welding path and the 1-Axis robot follows the V-groove. The tracking algorithm is applied to generate the welding path that is obtained by the correlation of a set of groove center points. It is important that the robot traces the welding path accurately in the margin of error. Thus, the process of error data distinction and modification is implemented through the estimation algorithm.

A Method for Rear-side Vehicle Detection and Tracking with Vision System

This paper contributes to development of a new method for detecting rear -side vehicle s and estimat ing the position s for blind spot region or providing the lane change information by using vision systems . Because the real image acquired during car driving has a lot of information including the target vehicle and background image as well as the noises such as lighting and shading, it is hard to extract only the target vehicle agains t the background image with satisfied robustness. In this paper, the target vehicle has been detected by repetitive image processing such as sobel and morphological operations and a Kalman filter has been also designed to cancel the background image and pr event the misreading of the target image. The proposed method can get faster image processing and more robustness rather than the previous researches. Various experiments were performed on the highway driving situations to evaluate the performance of the p roposed algorithm.

Comparison of model reference and map based control method for vehicle stability enhancement

A map based controller method to improve a vehicle lateral stability is proposed in this study and compared with the conventional method, a model referenced controller. A model referenced controller to determine compensated yaw moment uses the sliding mode method, but the proposed map based controller uses compensated yaw moment map acquired by vehicle stability analysis. Vehicle stability region is calculated by topological method based on trajectory reversal method. A two degree-of-freedom vehicle model and Pacejkas tire model used to evaluate the proposed map based controller. The control performance of two methods are compared under various road conditions and driving inputs. Model referenced control method needs control input to satisfies linear reference model, and then generates unnecessary tire lateral forces, it may lead to worse performance than uncontrolled vehicle with step steer input in low friction road. As the results of simulation, map based controller seems to be better than model referenced in the viewpoint of stability.

Control Performance Comparison of Model-referenced and Map-based Control Method for Vehicle Lateral Stability Enhancement

This study proposes a map-based control method to improve a vehicle’s lateral stability, and the performance of the proposed method is compared with that of the conventional model-referenced control method. Model-referenced control uses the sliding mode method to determine the compensated yaw moment; in contrast, the proposed map-based control uses the compensated yaw moment map acquired by vehicle stability analysis. The vehicle stability region is calculated by a topological method based on the trajectory reversal method. The performances of modelreferenced control and map-based control are compared under various road conditions and driving inputs. Model-referenced control uses a control input to satisfy the linear reference model, and it generates unnecessary tire lateral forces that may lead to worse performance than an uncontrolled vehicle with step steering input on a road with low friction coefficient. The simulation results show that map-based control provides better stability than model-referenced control.