Computer Science
Paper Review Records
All Paper Review Records
18 valid samples · Newest publication first
Review days = acceptance date − received date. PDF, DOI, and publisher-page sources are retained.
Incipient fault isolation for dynamic processes with the aid of extracted fault direction knowledge
AuthorsHongquan Ji; Yingxuan Shao
AffiliationsCollege of Electrical Engineering and Automation, Shandong University of Science and Technology, Qingdao 266590, PR China
CL-EALTD: Environment-aware latent temporal-difference contrastive learning for process series anomaly detection
AuthorsYunpeng Guo; Jianqi An; Qifu Chen; Min Wu; Jinhua She
AffiliationsSchool of Artificial Intelligence and Automation, China University of Geosciences, Wuhan, 430074, China; Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems, Wuhan, 430074, China; Engineering Research Center of Intelligent Technology for Geo-Exploration, Ministry of Education, Wuhan, 430074, China; School of Future Technology, China University of Geosciences, Wuhan, 430074, China; School of Engineering, Tokyo University of Technology, Hachioji, Tokyo, 192-0982, Japan
MS2-DAMoE: Multiscale multi-source domain alignment with adaptive mixture-of-experts for industrial time-series prediction
AuthorsXue Xu; Kaifang Li; Yuanjian Fu; Chaomin Luo; Chengyi Xia
AffiliationsSchool of Artificial Intelligence, Tiangong University, Tianjin 300387, China; Tianjin Key Laboratory of Intelligent Control of Electrical Equipment, Tiangong University, Tianjin 300387, China; School of Control Science and Engineering, Tiangong University, Tianjin 300387, China; Department of Electrical and Computer Engineering, Mississippi State University, Starkville, MS 39762, USA
Neural-Network Assisted MPC for flow reactors including reactions
AuthorsS. Knoll; K. Silber; A.C. Hone; C.O. Kappe; M. Steinberger; M. Horn
AffiliationsInstitute of Automation and Control, Graz University of Technology, Inffeldgasse 21b, 8010 Graz, Austria; Center for Continuous Synthesis and Processing (CCFLOW), Research Center Pharmaceutical Engineering GmbH (RCPE), Inffeldgasse 13, 8010 Graz, Austria; Institute of Chemistry, University of Graz, NAWI Graz, Heinrichstrasse 28, 8010 Graz, Austria
Few-shot class-incremental fault diagnosis via orthogonal prototypes and fuzzy uncertainty modeling
AuthorsBing Song; Yunpeng Li; Lijia Cao; Hongbo Shi; Yang Tao
AffiliationsKey Laboratory of Smart Manufacturing in Energy Chemical Process of the Ministry of Education, East China University of Science and Technology, Shanghai 200237, China; Sichuan University of Science & Engineering, Sichuan 618500, China
Learning reachable sets for efficient and approximate zonotopic robust nonlinear model predictive control
AuthorsMoritz Heinlein; Sergio Lucia
AffiliationsChair of Process Automation Systems, TU Dortmund University, Emil-Figge-Strasse 70, Dortmund, 44227, North Rhine Westphalia, Germany
Joint prediction and classification within a single multitask architecture for early fault diagnosis in chemical processes
AuthorsDjogap F. Chrysler J.; Moncef Chioua
AffiliationsDepartment of Chemical Engineering, Polytechnique Montréal, 2500 Chem. de Polytechnique, Montréal, H3T 0A3, QC, Canada
Disturbance observer-based model-free adaptive iterative learning control for nonlinear batch processes with non-repetitive disturbance
AuthorsFei Shi; Hongfeng Tao; Zhihe Zhuang; Tao Liu; Wojciech Paszke
AffiliationsKey Laboratory of Advanced Process Control for Light Industry of Ministry of Education, Jiangnan University, Wuxi, 214000, PR China; Institute of Advanced Measurement and Control Technology, Dalian University of Technology, Dalian, 116024, PR China; Institute of Automation, Electronic and Electrical Engineering, University of Zielona Gora, ul. Szafrana 2, 65-246 Zielona Gora, Poland
A multi-priority NMPC framework with adaptive convergence rate tuning strategy
AuthorsRuiyu Qiu; Yitao Yan; Zhijiang Shao; Jie Bao
AffiliationsCollege of Control Science and Engineering, Zhejiang University, Hangzhou, China; School of Chemical Engineering, The University of New South Wales, Sydney, Australia; Huzhou Institute of Industrial Control Technology, Huzhou, China
Sparse identification of physically plausible aggregation kernels for wet granulation processes
AuthorsStefan R. Tölle; Lorenz Dörschel; Stefan Klinken-Uth; Alana Delvos; Jörg Breitkreutz; Heike Vallery; Sebastian Stemmler
AffiliationsInstitute of Automatic Control, RWTH Aachen University, Aachen, Germany; Institute of Pharmaceutics and Biopharmaceutics, Heinrich Heine University, Düsseldorf, Germany; Department of Biomechanical Engineering, Delft University of Technology, Delft, The Netherlands
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