Hyung-Chul Lee
Hanyang University · 工学
研究室紹介
Professor Hyung-Chul Lee's research lab specializes in advanced control systems for intelligent transportation and automotive applications, focusing on robust and adaptive control strategies for nonlinear and uncertain dynamic systems. The lab develops innovative control methodologies—such as adaptive fuzzy logic control, sliding mode control, and robust backstepping techniques—to enhance vehicle stability, traction control, and autonomy in complex, real-world environments. Key research directions include integrated longitudinal and lateral vehicle control, sensor fusion for state estimation, and vehicle-in-the-loop (VIL) simulation for validating advanced driver assistance systems (ADAS). The lab emphasizes practical implementation and reliability under model uncertainties and parameter variations.
Research Overview
Research Output Trend
Figures are computed from collected data and may differ slightly.
Selected Papers
15This paper deals with the robust adaptive control of a class of nonlinear systems in the presence of parametric uncertainties and dominant uncertain nonlinearities. The proposed controller utilizes the robust adaptive control to guarantee uniform boundedness and convergence of tracking errors. In addition, an adaptive fuzzy logic system is used as a universal approximator to reduce the model uncertainties coming from uncertain nonlinearities and to improve tracking performance. The approach does
This paper presents a robust adaptive control method for a class of multi-input–multi-output (MIMO) nonlinear systems that are transformable to a parametric-strict-feedback form which has couplings among input channels and the appearance of parametric uncertainties in the input matrices. The proposed approach effectively combines the design techniques of robust adaptive control by backstepping and adaptive fuzzy-logic control in order to remove the matching-condition requirement and to provide b
This paper is concerned with robust longitudinal control of vehicles in intelligent vehicle highway systems by adaptive vehicle traction force control. Two different traction force controllers, adaptive fuzzy logic control and adaptive sliding-mode control, are proposed and applied to the fastest stable acceleration/deceleration and robust vehicle platooning problems. The motivation for investigating adaptive techniques arises from the unknown time-varying nature of the tire/road surface interac
Most vehicle controllers are developed and verified with V-model. There are several traditional methods in the automotive industry called “X-in-the-Loop (XIL)”. However, the validation of advanced driver assistance system (ADAS) controllers is more complicated and needs more environmental resources because the controller interacts with the external environment of the vehicle. Vehicle-in-the-Loop (VIL) is a recently being developed approach for simulating ADAS vehicles that ensures the safety of
This paper presents a systematic design of the combined control of vehicle longitudinal and lateral motions for the Intelligent Vehicle Highway Systems (IVHS). A fully coordinated control of the steering and the accelerating/braking actions is presented to maximize the ability of distributing the traction forces in a desired way. This control method covers a broad range of driving condition by removing several conventional simplification on vehicle dynamics, such as the linearized lateral tracti
Reliability indexed sensor fusion (RISF) is a new estimation techique which uses process and measurement noise covariances as the reliability index in an adaptive Kalman filter framework. In RISF, noise covariances are assumed to be highly uncertain and determined by engineering knowledge. The uniform boundedness of the RISF with incorrect noise covariances is proved in the sense that the error covariance is bounded if specified conditions are satisfied. The RISF technique is then applied to the
An integrated fault-diagnosis algorithm for a motor sensor of in-wheel independent drive electric vehicles is presented. This paper proposes a method that integrates the high- and low-level fault diagnoses to improve the robustness and performance of the system. For the high-level fault diagnosis of vehicle dynamics, a planar two-track non-linear model is first selected, and the longitudinal and lateral forces are calculated. To ensure redundancy of the system, correlation between the sensor and
Vehicle control systems such as ESC (electronic stability control), MDPS (motor-driven power steering), and ECS (electronically controlled suspension) improve vehicle stability, driver comfort, and safety. Vehicle control systems such as ACC (adaptive cruise control), LKA (lane-keeping assistance), and AEB (autonomous emergency braking) have also been actively studied in recent years as functions that assist drivers to a higher level. These DASs (driver assistance systems) are implemented using
This report presents two different control algorithms for adaptive vehicle traction control, which includes wheel slip control, optimal time control, anti-spin acceleration and anti-skid control, and longitudinal platoon control. The two control algorithms are respectively based on adaptive fuzzy logic control and sliding mode control with on-line road condition estimation. Simulations of the two control methods are conducted using a complex nonlinear vehicle model as well as a simple linear veh
This paper presents an analytical sensor fault-detection and isolation algorithm for the vertical accelerometers of a continuous damping control (CDC) system, which are essential but vulnerable components in the CDC system. Because the sensor configuration of the target CDC system does not provide sufficient redundancy for fault diagnosis, two different vehicle suspension models, a modified full car model and a roll-and-pitch plane model, are derived and combined to establish analytical redundan
Transmission mounted electric drive type hybrid electric vehicles (HEVs) engage/disengage an engine clutch when EV↔HEV mode transitions occur. If this engine clutch is not adequately engaged or disengaged, driving power is not transmitted correctly. Therefore, it is required to verify whether engine clutch engagement/disengagement operates normally in the vehicle development process. This paper studied machine learning-based methods for detecting anomalies in the engine clutch engagement/disenga
In this paper, a new estimation technique, reliability indexed sensor fusion (RISF), is proposed. The proposed RISF technique uses noise covariances as the reliability index in an adaptive Kalman filter framework. The uniform boundedness of the RISF is proved and the RISF technique is applied to the vehicle longitudinal and lateral velocity estimation. Multiple sensors, such as the wheel speed sensors, the accelerometers, the yaw rate sensor, and the steering angle sensor, are used for the veloc
We present a theoretical analysis of the temperature behavior of pellicles in extreme ultra-violet (EUV) lithography. Using modified heat transfer equations and accounting for the cooling mechanism during exposure, we calculate the temperature of the pellicle due to EUV beam absorption as a function of the incident EUV power. We find the temperature rise to be less than 620 K for a 10 ms incident EUV beam with a power of 100 W. The recovery time after EUV beam exposure is also calculated to be l
This paper presents a control system design procedure for a four-wheel drive (4WD) system that uses a clutchless centre limited slip differential (CC-LSD) as the torque biasing device between the front and rear driveshafts. The paper describes mathematical analysis and modelling of the CC-LSD. It also presents a new analytical 4WD control method based on the vehicle dynamics by introducing several breakthrough control techniques, such as the control map with three different control modes, the ve