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Shuai Wang,Li Lyu,Guobao Sima, Ying Cui,Ying Cui,Baoxia Li,Xueqin Zhang,Linhuo Gan 한국화학공학회 2019 Korean Journal of Chemical Engineering Vol.36 No.7
A sulfonated lignin-derived mesoporous carbon (LDMC-SO3H) was prepared from kraft lignin (KL) using phenolation and soft-template method followed by sulfonation. LDMC-SO3H bearing a sulfonic acid density of 0.65 mmol/g possessed a well-ordered 2D hexagonal mesoporous characteristics with mesopore volume of 0.067 cm3/g and specific surface area of 262m2/g as well as mesopore size of 3.42 nm. A high 5-hydroxymethylfurfural (5-HMF) yield of 98.0% with a full fructose conversion was obtained using LDMC-SO3H as catalyst under the optimized reaction conditions of reaction temperature and time of 140 oC and 120 min, initial fructose concentration of 100 g/L, catalyst load of 0.1mg/mg in DMSO. Furthermore, there was no obvious decrease in 5-HMF yield (95.0%) within the fivecycle experiment, highlighting the superior reusability and stability of LDMC-SO3H in fructose-to-5-HMF transformation.
Q learning-based Autonomous Valet Parking System
Ying Shuai Quan(전영수),Dae Jung Kim(김대정),Seung-Hi Lee,Chung Choo Chung 한국자동차공학회 2020 한국자동차공학회 부문종합 학술대회 Vol.2020 No.7
In this paper, we propose a brand new vehicle lateral motion control algorithm for autonomous parking system utilizing Q-learning algorithm. Normally for optimal vehicle control, linearization is introduced to deal with the nonlinearity of vehicle dynamics, which reduces the optimality of the derived control laws. To solve the problem, a Q-learning based vehicle parking control algorithm is proposed. A path planning method is introduced to the design of the state vector in the Q-learning algorithm for vehicle lateral control. Feasibility of the proposed algorithm is validated by computational simulation results showing satisfactory performances on the test scenario.
Recurrent Neural Network-Based Model Predictive Control for Waypoint Tracking
Ying Shuai Quan,Woo Young Choi,Seung-Hi Lee,Chung Choo Chung 한국자동차공학회 2019 한국자동차공학회 부문종합 학술대회 Vol.2019 No.5
This paper presents an recurrent neural network-based model predictive control for an autonomous driving vehicle. Model predictive control is effective in vehicle lateral control but too computationally expensive to be applied in real-time control. To resolve this problem, we propose a recurrent neural network-based approximate model predictive control. The offline-trained neural network exhibits the ability to model the waypoint tracking system and provided the closed-loop performance. The performance of the approximate recurrent neural network-model predictive control (RNN-MPC) is validated by computational experiments of waypoints tracking control scheme.
Ying Shuai Quan,Jin Sung Kim,정정주 제어·로봇·시스템학회 2022 International Journal of Control, Automation, and Vol.20 No.7
This paper presents a robust controller using a Linear Parameter Varying (LPV) model of a lane-keeping system with parameter reduction. Both varying vehicle speed and roll motion on a curved road influence the lateral vehicle model’s parameters, such as tire cornering stiffness. Thus, we use the LPV technique to take the parameter variations into account in vehicle dynamics. However, multiple varying parameters lead to a high number of scheduling variables and cause massive computational complexity. In this paper, to reduce the computational complexity, Principal Component Analysis (PCA)-based parameter reduction is performed to obtain a reduced model with a tighter convex set. We designed the LPV robust feedback controller using the reduced model solving a set of Linear Matrix Inequality (LMI). The effectiveness of the proposed system is validated with full vehicle dynamics from CarSim on an interchange road. From the simulation, we confirmed that the proposed method largely reduces the lateral offset error, compared with other controllers based on a Linear Time-Invariant (LTI) system.
Ying Shuai Quan,Jin Sung Kim,Chung Choo Chung 제어로봇시스템학회 2021 제어로봇시스템학회 국제학술대회 논문집 Vol.2021 No.10
In this paper, we propose a Robust Model Predictive Control combined with Control Barrier Function (RMPC-CBF) for a nonholonomic robot with obstacle avoidance subject to additive input disturbances. Both Input-to-State Stability (ISS) and Input-to-State Safety (ISSf) are provided to theoretically guarantee the system’s stability and safety. CBF-based safety conditions are formulated as constraints inside a robust MPC strategy. Robust satisfaction of the constraints is ensured by tightening the state constraint set. With admissible disturbances under a certain bound, ISS and robust recursive feasibility are guaranteed by computing the terminal region and state constraint set. For obstacle avoidance, Input-to-State Safe Control Barrier Function (ISSf-CBF) is chosen to provide robust set safety for the dynamic systems under input disturbances, which always guarantees that states stay inside or close to the safe set. With the proposed method, the future state prediction is taken into consideration and optimal performance is accomplished via MPC, and the system’s safety is ensured via CBF. Numerical simulation results confirm the effectiveness and validity of the proposed approach.
Mechanical Performance of Prefabricated External Wall Panel under Horizontal Displacement
Ying Xu,Shuai-Ying Wang,Lei Chai,Cong-Cong Luo 대한토목학회 2018 KSCE JOURNAL OF CIVIL ENGINEERING Vol.22 No.11
In this paper, experiment and Finite Element Method (FEM) approaches are employed to study the mechanical performance of prefabricated external wall panel under lateral displacement. Tensile bond strength test and Z-shaped specimen direct shear test of the bonding interface of mortar to ceramsite concrete are performed, the normal and shear mechanical property of the interface is studied respectively. Scaled model test of prefabricated external wall panel under lateral displacement is then performed to obtain loaddisplacement curve, and mechanical behavior of prefabricated external wall panel in different stages is studied. Moreover, ABAQUS finite element analysis model for scaled model test panel is established based on previous study about bond interface and the results from experiment and FEM analysis are relatively consistent with each other. It is found that with the gradual increase in tangential contact stiffness of joint interfaces, the overall lateral stiffness of wall panels will approach complete joint consolidation conditions before the peak load. However, when the tangential contact stiffness of joint interfaces increases to a certain extent, there will be little change in initial lateral stiffness.
Robust MPC-CBF를 이용한 논홀로노믹 로봇의 장애물 회피
전영수(Ying Shuai Quan),홍정훈(Jeong Hun Hong),김진성(Jin Sung Kim),정정주(Chung Choo Chung) 대한전기학회 2021 대한전기학회 학술대회 논문집 Vol.2021 No.10
본 논문에서는 additive input disturbance가 존재하는 상황에서 논홀로노믹 로봇의 장애물 회피를 위한 Robust Model Predictive Control combined with Control Barrier Function (RMPC-CBF)를 제안한다. CBF는 로봇의 safety 조건을 만족하기 위해 사용되고, 이를 위해 Robust MPC의 constraint로 반영된다. 제안하는 방법은 CBF의 safety 조건을 만족하는 RMPC를 통해 예측된 모델의 상태가 최적화 된다. 또한, 본 논문에서는 제안하는 알고리즘의 stability를 보장하기 위해 Input-to-State Stability(ISS)의 이론을 통해 증명한다. 알고리즘의 유효성을 검증하기 위해 MATLAB을 이용하여 시뮬레이션을 수행하였고, 이를 통해 제안하는 알고리즘의 장애물 회피를 확인하였다.
( Shuai Liu ),( Xiao Yu ),( Qiankun Wang ),( Zhepeng Liu ),( Qiaoqiao Xiao ),( Panpan Hou ),( Ying Hu ),( Wei Hou ),( Zhanqiu Yang ),( Deyin Guo ),( Shuliang Chen ) 한국미생물생명공학회(구 한국산업미생물학회) 2017 Journal of microbiology and biotechnology Vol.27 No.10
The synergistic activation mediator (SAM) system can robustly activate endogenous gene expression by a single-guide RNA. This transcriptional modulation has been shown to enhance gene promoter activity and leads to epigenetic changes. Human interferon-γ is a common natural glycoprotein involved in antiviral effects and inhibition of cancer cell growth. Large quantities of high-purity interferon-γ are important for medical research and clinical therapy. To investigate the possibility of employing the SAM system to enhance endogenous human interferon-γ with normal function in innate immunity, we designed 10 single-guide RNAs that target 200 bp upstream of the transcription start sites of the interferon-γ genome, which could significantly activate the interferon-γ promoter reporter. We confirmed that the system can effectively and highly activate interferon-γ expression in several humanized cell lines. Moreover, we found that the interferon-γ induced by the SAM system could inhibit tumorigenesis. Taken together, our results reveal that the SAM system can modulate epigenetic traits of non-immune cells through activating interferon-γ expression and triggering JAK-STAT signaling pathways. Thus, this strategy could offer a novel approach to inhibit tumorigenesis without using exogenous interferon-γ.
Ying-Xiao Fu,Jian-Hong Gu,Yi-Ran Zhang,Xi-Shuai Tong,Hong-Yan Zhao,Yan Yuan,Xue-Zhong Liu,Jian-Chun Bian,Zong-Ping Liu 대한수의학회 2013 Journal of Veterinary Science Vol.14 No.4
The purpose of this study was to determine whether osteoprotegerin (OPG) could affect osteoclat differentiation and activation under serum-free conditions. Both duck embryo bone marrow cells and RAW264.7 cells were incubated with macrophage colony stimulatory factor (M-CSF) and receptor activator for nuclear factor κB ligand (RANKL) in serum-free medium to promote osteoclastogenesis. During cultivation, 0,10, 20, 50, and 100 ng/mL OPG were added to various groups of cells. Osteoclast differentiation and activation were monitored via tartrate-resistant acid phosphatase (TRAP) staining,filamentous-actin rings analysis, and a bone resorption assay. Furthermore, the expression osteoclast-related genes, such as TRAP and receptor activator for nuclear factor κB (RANK),that was influenced by OPG in RAW264.7 cells was examined using real-time polymerase chain reaction. In summary,findings from the present study suggested that M-CSF with RANKL can promote osteoclast differentiation and activation,and enhance the expression of TRAP and RANK mRNA in osteoclasts. In contrast, OPG inhibited these activities under serum-free conditions.