Prof. Dr. Woo Young Choi
Department of Control and Instrumentation Eng., Pukyong National University, Busan, Republic of Korea
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Academic Career Length
10Years (2017-Present)
(Calculated once Scilit publication data is synced: current year − year of first publication + 1)
Representative Publications
View All Publications21 December 2021 in IEEE Transactions on Industrial Informatics
Journal Article
In this article, we present an innovative approach, i.e., horizonwise model-predictive control (H-MPC), to solve the model-predictive control (MPC) problem of a linear time-varying (LTV) system. In H-MPC, we regard the time-varying parameters as time invariant within the prediction horizon. To solve the MPC problem of the time-varying system, the decision variable is decomposed into two terms: one for linear time-invariant optimization and the other for compensating LTV uncertainties with an introduction to a uniform compensation condition. The proposed H-MPC solves the time-varying problem by removing the uncertainty due to the future parameter variations within the horizon and by updating the time-invariant MPC at each sampling time. To validate the usefulness of the proposed H-MPC, it is applied to lane tracking control for an autonomous driving vehicle. From a comparative study of the H-MPC and conventional MPCs in lane tracking control, it is confirmed that the proposed H-MPC has a competitive performance compared to LTV-MPC despite its much simpler structure.
1
17 December 2020 in International Journal of Control, Automation, and Systems
Journal Article
Woo Young ChoiCKChang Mook Kang
Chang Mook KangSLSeung-Hi Lee
Seung-Hi LeeCCChung Choo Chung
Chung Choo Chung6 November 2020 in IEEE Transactions on Industrial Informatics
Journal Article
In a dynamic lateral motion model with a look-ahead distance, curved and winding roads appear as an unmatched disturbance to a lane-tracking control system. In this article, an innovative vehicular robust lane-tracking control scheme is proposed to compensate for the problematic winding road disturbance (WRD) that always appears unless the road has zero curvature. We propose a design for a WRD compensator (WRDC) to substantially improve the lane-tracking control performance on a winding road in the presence of the WRD. The WRDC redesigns the state-space reference, rather than calculating the additional control input. We show that the proposed WRDC ensures that the projected tracking error decreases to zero. To validate the usefulness of the robust lane-tracking control, the WRDC is compared to other conventional methods. We observe that the proposed WRDC is not only robust against road curvature variation, but also outperforms the lane-tracking control performance of other popular methods.
1
1 June 2018
Conference Paper
Woo Young ChoiDKDae Jung Kim
Dae Jung Kim
CKChang Mook Kang
Chang Mook KangSLSeung-Hi Lee
Seung-Hi Lee
CCChung Choo Chung
Chung Choo Chung
20 September 2020
Conference Paper
In this paper, we propose a waypoint tracking scheme with a collision-avoidance system using the artificial potential field (APF) with speed planning. It is shown that there is little literature about the combination work of waypoint tracking and APF-based local path planner. We present a new path planning method to smoothly join the local path predicted by APF to avoid obstacles and the path given by irregular waypoints to eliminate severe yawing of the heading angle of the vehicle. The proposed speed planning combined with APF effectively prevents possible excessive tire slip angle of the vehicle driving at high speed. The simulation results show that the proposed path planning algorithm with speed planning is effective in collision avoidance with static and/or dynamic obstacles for the waypoint tracking scenario. This proposed method is validated with the vehicle dynamic lateral motion model in MATLAB/Simulink and CarSim.
17 January 2025 in IEEE Access
Journal Article
JKJin Sung Kim
Jin Sung KimYQYing Shuai Quan
Ying Shuai QuanCCChung Choo Chung
Chung Choo ChungWoo Young ChoiThis paper proposes Koopman operator-based Stochastic Model Predictive Control (K-SMPC) for enhanced lateral control of autonomous vehicles. The Koopman operator is a linear map representing the nonlinear dynamics in an infinite-dimensional space. Thus, we use the Koopman operator to represent the nonlinear dynamics of a vehicle in dynamic lane-keeping situations. The Extended Dynamic Mode Decomposition (EDMD) method is adopted to approximate the Koopman operator in a finite-dimensional space for practical implementation. We consider the modeling error of the approximated Koopman operator in the EDMD method. Then, we design K-SMPC to tackle the Koopman modeling error, where the error is handled as a probabilistic signal. The recursive feasibility of the proposed method is investigated with an explicit first-step state constraint by computing the robust control invariant set. A high-fidelity vehicle simulator, i.e., CarSim, is used to validate the proposed method with a comparative study. From the results, it is confirmed that the proposed method outperforms other methods in tracking performance. Furthermore, it is observed that the proposed method satisfies the given constraints and is recursively feasible.
About Me
Woo Young Choi received his B.S. degree in control and instrumentation engineering from Pukyong National University, Busan, Korea, in 2015, and his Ph.D. degree in electrical engineering from Hanyang University, Seoul, Korea, in 2021, where he was awarded the Best Dissertation Award for his doctoral thesis. From 2021 to 2022, he was a postdoctoral researcher with the Korea Institute of Science and Technology, in Seoul, Korea. From 2022 to 2023, he was an Assistant Professor with the Department of automotive system engineering, at Keimyung University, Daegu, South Korea. In 2023, he joined the Department of Control and instrumentation engineering, Pukyong National University, Busan, South Korea, as a Faculty Member.
His research interests include control theory, model predictive control, optimal control, estimation, uncertainty compensation, and autonomous vehicles and mobile robots. Dr. Choi is a member of IEEE Industrial Electronics Society, IEEE Intelligent Transportation Systems Society, IEEE Control Systems Society, Society of Automotive Engineers, Korean Society of Automotive Engineers, and Institute of Control, Robotics, and Systems. He received the Outstanding Young Researcher Award at the Institute of Control, Robotics, and Systems in 2023.
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