Prof.
SHEN's Group Distributed Artificial Intelligence Laboratory, ERC-FCDE, MoE School of Mathematics, Renmin University of China |
Faculty |
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Prof.
Dong SHEN E-mail: dshen [at] ieee.org Tel: 010-82507078 Office: Rm 207, Mathematics Building Web: @DAI @RUC @ResearchGate |
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Prof. Hao JIANG Email: jiangh [at] ruc.edu.cn Office: Rm 223, Mathematics Building Web: @DAI @RUC @ResearchGate |
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Assoc. Prof. Qijiang SONG Emai: sqj [at] ruc.edu.cn Tel: 010-82500693 Office: Rm 337, Information Building Web: @DAI @RUC @ResearchGate |
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Assit. Prof. Xiuqiong CHEN Email: cxq0828 [at] ruc.edu.cn Office: Room 327, Information Building Web: @DAI @RUC |
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Ph.
D Candidate |
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HUANG Shunhao | 2020 Topic: GPR-based Learning Control M.E., Beijing University of Chemical Technology Publications: [1] Hao Jiang, Dong Shen, Shunhao Huang, Xinghuo Yu. Accelerated Learning Control for Point-to-Point Tracking Systems. IEEE Transactions on Neural Networks and Learning Systems, vol. 35, no. 1, pp. 1265-1277, 2024. [2] Shunhao Huang, Dong Shen, JinRong Wang. Point-to-Point Learning Tracking Control via Fading Communication Using Reference Update Strategy. IEEE Transactions on Cybernetics, vol. 54, no. 4, pp. 2284-2294, 2024. |
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QIAN Jiaxi | 2021 Topic: Optimization-Based ILC B.S., Jilin University Publications: [1] Jiaxi Qian, Dong Shen. A Novel Iterative Learning Control Scheme Based on Broyden-class Optimization Method. International Journal of Robust and Nonlinear Control, vol. 34, no. 1, pp. 321-340, 2024.. |
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HUO Niu | 2021 Topic: Quantized Iterative Learning Control M.E., Beijing University of Chemical Technology Awards: Selected, 2022 Funding Program for Cultivating top-notch innovative Talents of Renmin University of China Publications: [1] Niu Huo, Hao Jiang, Dong Shen, Jinrong Wang. Finite-Level Uniformly Quantized Learning Control with Random Data Dropouts. International Journal of Robust and Nonlinear Control, vol. 33, no. 7, pp. 4056-4075, 2023. [2] Dong Shen, Niu Huo, Samer S. Saab. A Probabilistically Quantized Learning Control Framework for Networked Linear Systems, IEEE Transactions on Neural Networks and Learning Systems, vol. 33, no. 12, pp. 7559-7573, 2022. [3] Niu Huo, Dong Shen, Jinrong Wang. Novel quantized iterative learning control based on spherical polar coordinates. International Journal of Robust and Nonlinear Control, vol. 34, no. 13, pp. 8945-8969, 2024. |
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HE
Xun | 2020(M) 2022(D) Topic: Learning Control for Complex Networks B.S., Qufu Normal University Awards: Selected, Graduate Scientific Research Fund Project of Renmin University of China Publications: [1] Xun He, Dong Shen. Distributed Iterative Learning Temperature Control for Large-Scale Buildings. International Journal of Robust and Nonlinear Control, vol. 33, no. 7, pp. 4210-4227, 2023. [2] Hao Jiang, Xun He, Qijiang Song, Dong Shen. Decentralized Learning Control for Large-Scale Systems With Gain Adaptation Mechanism. Information Sciences, vol. 623, pp. 539-558, 2023. |
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LIU Taojun | 2022 Topic: Learning Control with Dynamic Quantization Mechanisms B.S., Dalian University of Technology |
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CHENG
Xiang | 2020(M) 2023(D) Topic: Variable Gain Design in ILC B.S., University of Science and Technology Beijing Awards: 2022 China National Scholarship Publications: [1] Xiang Cheng, Hao Jiang, Dong Shen, Xinghuo Yu. A Novel Adaptive Gain Strategy for Stochastic Learning Control. IEEE Transactions on Cybernetics, vol. 53, no. 8, pp. 5264-5275, 2023. [2] Xiang Cheng, Hao Jiang, Dong Shen. A Novel Accelerated Multi-Stage Learning Control Mechanism via Virtual Performance Reduction. IEEE Transactions on Neural Networks and Learning Systems, vol. 35, no. 5, pp. 6338-6352, 2024. [3] Xiang Cheng, Hao Jiang, Dong Shen, Xinghuo Yu. An accelerated adaptive gain design in stochastic learning control. IEEE Transactions on Cybernetics, accepted. |
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ZHANG Zeyi | 2020(M) 2023(D) Topic: New Design Techniques in ILC B.S., Qingdao University Awards: 2022 China National Scholarship 2024 SCIS-CCC The Honorable Mention of Poster Paper Award 2022 IEEE 11th DDCLS Best Paper Award Finalist Publications: [1] Zeyi Zhang, Dong Shen. Randomized Kaczmarz Algorithm with Averaging and Block Projection. BIT Numerical Mathematics, vol. 64, Article number: 1, 2024. [2] Zeyi Zhang, Hao Jiang, Dong Shen, Samer S. Saab. Data-driven learning control algorithms meeting unachievable tracking problems.IEEE/CAA Journal of Automatica Sinica, vol. 11, no. 1, pp. 205-218, 2024. |
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LI Zihan | 2021(M) 2024(D) Topic: Fractional-power Learning Control Rules B.S., Hunan University Awards: 2023 China National Scholarship Publications: [1] Zihan Li, Dong Shen. Filter-Free Parameter Estimation Method for Continuous-Time Systems. IEEE Transactions on Automation Science and Engineering, accepted for publication. [2] Zihan Li, Dong Shen, Xinghuo Yu. Enhancing Iterative Learning Control With Fractional Power Update Law. IEEE/CAA Journal of Automatica Sinica, vol. 10, no. 5, pp. 1137-1149, 2023. [3] Zihan Li, Dong Shen, Xinghuo Yu. A multistage update rule framework for iterative learning control systems. IEEE Transactions on Automation Science and Engineering, accepted for publication. |
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GAO Shuai | 2021(M) 2024(D) Topic: Learning Control for High-Speed Trains B.S., Shaanxi Normal University Awards: 2023 China National Scholarship Publications: [1] Shuai Gao, Qijiang Song, Dong Shen. Distributed Learning Control for High-Speed Trains With Operation Safety Constraints. IEEE Transactions on Cybernetics, vol. 54, no. 3, pp. 1794-1805, 2024. [2] Shuai Gao, Qijiang Song, Hao Jiang, Dong Shen. History Makes Future: Iterative Learning Control for High-Speed Trains. IEEE Intelligent Transportation Systems Magazine, vol. 16, no. 1, pp. 6-21, 2024. |
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Master Candidate | |
ZHANG Zhenfa | 2022 Topic: Multi-objective Learning Control B.S., Shandong University |
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HUANG Dunsheng | 2022 Topic: Wavelet-based Learning Approximation B.S., Beijing Jiaotong University Awards: 2024 IEEE 13th DDCLS Best Poster Paper Award |
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DU Bowen | 2022 Topic: Learning Control for HSTs B.S., Shandong University |
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WANG Chi | 2022 Topic: Bioinformatics B.S., Huazhong University of Science and Technology |
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ZHOU Zimo | 2022 Topic: Bioinformatics B.S., Harbin Institute of Technology, Shenzhen |
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CHANG Junji | 2022 Topic: Learning Control Under Noise Correlation B.S., Liaoning Technical University |
HE Yunqi | 2023 Topic: Federated Learning and Applications B.S., Sichuan University |
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TONG Bosong | 2023 Topic: ILC Based on Two-Dimensional Systems B.S., Beijing University of Technology |
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ZHOU Chengtao | 2023 Topic: Bioinformatics B.S., Zhongnan University of Economics and Law |
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MU Weimeng | 2023 Topic: Bioinformatics B.S., Xiamen University |
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CAI Yujin | 2024 Topic: Pending B.S., Xiamen University |
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CHEN Kunhong | 2024 Topic: Pending B.S., Fuzhou University |
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MA Yenan | 2024 Topic: Pending B.S., Northeastern University |
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YAN Yujing | 2024 Topic: Pending B.S., Hebei University of Technology |
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DU Ruobing | 2024 Topic: Pending B.S., Shandong University |
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LIU Zihan | 2024 Topic: Pending B.S., Shandong University |
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JIANG Yunxi | 2024 Topic: Pending B.S., Beijing Normal University |
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Welcom to join us. Email me. |
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Undergraduates |
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Recruiting |
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Visiting
Students |
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Recruiting
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ZHAO Xingying | Ph.D. Graduated 2024.06 Topic: Federated Learning and Its Applications Publications: [1] Xing-Ying Zhao, Hao Jiang, Dong Shen. EOGFACE: Deep Face Recognition Via Extensional Logits. 2022 IEEE International Conference on Image Processing. 2022 IEEE International Conference on Image Processing, Bordeaux, France, 16-19 October, 2022, pp. 311-315. [2] Xingying Zhao, Dong Shen. FedLoss: Logits Replacement of Softmax for Federated Learning Face Recognition. Submitted. [3] Xingying Zhao, Dong Shen. FedDFS: Data Filtering for Stable Federated Learning. Submitted. [4] Xingying Zhao, Dong Shen. FedSW: Federated learning with adaptive sample weights. Information Sciences, vol. 654, Article 119873, 2024. |
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LUO Qiaoqiao | M.S. Graduated 2024.06 Topic: Learning Control under Network Attacks |
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WANG Yingchao | M.S. Graduated 2024.06 Topic: Event-triggered Learning Control |
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ZHOU Yujian | M.S. Graduated 2024.06 Topic: Machine Learning and Its Applications |
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ZHAN Senwen | M.S. Graduated 2024.06 Topic: Machine learning and Its Applications Publications: [1] Senwen Zhan, Hao Jiang, Dong Shen. Co-regularized Optimal High-Order Graph Embedding for Multi-View Clustering. Pattern Recognition, accepted. |
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HUANG yixiang|M.S. Graduated 2024.06 Topic: Machine Learning in Bioinformatics |
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AI Yutong | M.S. Graduated 2023.06 Topic:Graph Neural Networks and its applications |
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WANG Mengjie | M.S. Graduated 2023.06 Topic: Machine learning on Bioinfomatics |
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ZENG
Kun | M.E. Graduated 2023.06 Topic: Iterative Learning Containment Control for Multi-Agent Systems Book Chapter: [1] Kun Zeng. Iterative Learning Control for FinTech. Proceedings of the First International Forum on Financial Mathematics and Financial Technology, Chapter 15. Springer, 2021. |
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DOU Yiyao | M.S. Graduated 2022.06 Topic: Bioinformatics |
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FENG Yifan | M.S. Graduated 2022.06 Topic: Bioinformatics |
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QU
Ganggui | M.E. Graduated 2021.06 Thesis: Iterative Learning Control Over Fading Channel Following Position: Engineer in a company Awards: 2019 China National Scholarship Journal Papers: [1] Ganggui Qu, Dong Shen. Stochastic Iterative Learning Control With Faded Signals. IEEE/CAA Journal of Automatica Sinica, vol. 6, no. 5, pp. 1196-1208, 2019. [2] Dong Shen, Ganggui Qu, Qijiang Song. Learning Control for Networked Stochastic Systems With Fading Communication. IEEE Transactions on Systems, Man, and Cybernetics-Systems, accepted for publication. [3] Dong Shen, Ganggui Qu. Learning Tracking Systems Over Fading Channels with Multiplicative and Additive Randomness. IEEE Transactions on Neural Networks and Learning Systems, vol. 31, no. 4, pp. 1196-1210, 2020. [4] Dong Shen, Ganggui Qu, Xinghuo Yu. Averaging Techniques for Balancing Learning and Tracking Abilities Over Fading Channels. IEEE Transactions on Automatic Control, accepted for publication. [5] Ganggui Qu, Dong Shen, Qijiang Song, Xinghuo Yu. Point-to-Point Learning and Tracking for Networked Stochastic Systems With Fading Communications. Submitted for publication. [6] Ganggui Qu, Dong Shen, Xinghuo Yu. Batch-Based Learning Consensus of Multi-Agent Systems With Faded Neighborhood Information. IEEE Transactions on Neural Networks and Learning Systems. accepted. |
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HUO Niu | M.E. Graduated 2021.06 Thesis: Research on Quantized Iterative Learning Control Following Position: PhD candidate, Renmin University of China Awards: 2019 China National Scholarship Journal Papers: [1] Niu Huo, Dong Shen. Finite-level Quantized Iterative Learning Control with Encoding and Decoding Mechanism with Random Data Dropouts. IEEE Transactions on Automation Science and Engineering, vol. 17, no. 3, pp. 1343-1360, 2020. [2] Niu Huo, Dong Shen. Improving Boundary Level Calculation in Quantized Iterative Learning Control with Encoding and Decoding Mechanism. IEEE Access, vol. 7, no. 1, pp. 66623-66632, 2019. [3] Niu Huo, Dong Shen, Jinrong Wang. Finite-Level Uniformly Quantized Learning Control with Random Data Dropouts. Submitted for publication. [4] Dong Shen, Niu Huo, Samer S. Saab. A Probabilistically Quantized Learning Control Framework for Networked Linear Systems, IEEE Transactions on Neural Networks and Learning Systems. |
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LIU Yanze | B.E. Graduated 2021.06 Bachelor Thesis: Iterative Learning Control in Network Environments Journal Papers: [1] Yanze Liu, Dong Shen. An Efficient Algorithm for Collaborative Learning Model Predictive Control of Nonlinear System. ISA Transactions, accepted for publication. |
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LIU
Chen | M.E. Graduated 2020.06 Co-supervised by Shuming Tang Thesis: Consensus Tracking Iterative Learning Control for Multi-Agent Systems Following Position: PhD candidate, Xi'an Jiaotong University Awards: 2019 China National Scholarship Journal Papers: [1] Chen Liu, Dong Shen, JinRong Wang. Iterative Learning Control of Multi-Agent Systems under Communication Noises and Measurement Range Limitations. International Journal of Systems Science, vol. 50, no. 7, pp. 1465-1482, 2019. [2] Chen Liu, Dong Shen, JinRong Wang. A Two-Dimensional Approach to Iterative Learning Control with Randomly Varying Trial Lengths. Journal of Systems Science and Complexity, vol. 33, no. 3, pp. 685-705, 2020. [3] Chen Liu, Dong Shen, JinRong Wang. Adaptive learning control for general nonlinear systems with nonuniform trial lengths, initial state deviation, and unknown control direction. International Journal of Robust and Nonlinear Control, vol. 29, no. 17, pp. 6227-6243, 2019. [4] Dong Shen, Chen Liu, Lanjing Wang, Xinghuo Yu. Iterative Learning Tracking for Multi-Sensor Systems: A Weighted Optimization Approach. IEEE Transactions on Cybernetics, accepted for publication. [5] Tianbo Zhang, Dong Shen, Chen Liu, Hongze Xu. A Novel Iterative Learning Control Approach Based on Steady-state Kalman Filtering. IEEE Access, vol. 7, no. 1, pp. 99371-99380, 2019. |
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ZENG Chun | M.E. Graduated 2019.06 Thesis: Iterative Learning Control with Iteration-Varying Lengths Based on CEF Following Position: China Electronics Technology Group Corporation (Institute 32) Awards: [1] 2018 China National Scholarship [2] 2019 Excellent Master Thesis of BUCT Journal Papers: [1] Chun Zeng, Dong Shen, JinRong Wang. Adaptive Learning Tracking for Uncertain Systems with Partial Structure Information and Varying Trial Lengths. Journal of the Franklin Institute, vol. 355, no. 15, pp. 7027-7055, 2018. [2] Chun Zeng, Dong Shen, JinRong Wang. Adaptive Learning Tracking for Robot Manipulators with Varying Trial Lengths. Journal of the Franklin Institute, vol. 356, no. 12, pp. 5993-6014, 2019. |
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ZHANG Chao | M.E. Graduated 2018.12 ahead of schedule Thesis: Quantized Iterative Learning Control Based on Encoding and Decoding Mechanism Following Position: CheetahMobile Awards [1] 2018 IEEE 7th DDCLS Best Paper Award Finalist [2] 2017 China National Scholarship [3] 2016 Top Scholarship of BUCT Journal Papers: [1] Dong Shen, Chao Zhang, Yun Xu. Two Compensation Schemes of Iterative Learning Control for Networked Control Systems with Random Data Dropouts. Information Sciences, vol. 381, pp. 352-370, 2017. [2] Dong Shen, Chao Zhang. Learning Control for Discrete-Time Nonlinear Systems With Sensor Saturation and Measurement Noise. International Journal of Systems Sciences, vol. 48, no. 13, pp. 2764-2778, 2017. [3] Dong Shen, Chao Zhang, Yun Xu. Intermittent and Successive ILC for Stochastic Nonlinear Systems with Random Data Dropouts. Asian Journal of Control, vol. 20, no. 3, pp. 1102-1114, 2018. [4] Dong Shen, Chao Zhang, Jian-Xin Xu. Distributed Neural Networks Based Learning Consensus Control for Heterogeneous Nonlinear Multi-Agent Systems. International Journal of Robust and Nonlinear Control, vol. 29, no. 13, pp. 4328-4347, 2019. [5] Chao Zhang, Dong Shen. Zero-Error Convergence of Iterative Learning Control Based on Uniform Quantization with Encoding and Decoding Mechanism. IET Control Theory & Application, vol. 12, no. 14, pp. 1907-1915, 2018. [6] Chao Zhang, Dong Shen. Zero-Error Learning Tracking Based on Quantized Data via Encoding-Decoding Mechanism at Both Measurement and Actuator Sides. IEEE Transactions on Cybernetics. |
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WANG Lanjing | M.E. Graduated 2018.06 Thesis: Iterative Learning Control for Continuous-time Nonlinear Systems with Iteration Varying Lengths Followin position: Sichuan Agricultural University Awards: [1] 2018 Excellent Master Thesis of BUCT Journal Papers: [1] Lanjing Wang, Xuefang Li, Dong Shen. Sampled-data-based Iterative Learning Control for Continuous-time Nonlinear Systems with Iteration-Varying Lengths. International Journal of Robust and Nonlinear Control, vol. 28, no. 8, pp. 3073-3091, 2018. [2] Dong Shen, Chen Liu, Lanjing Wang, Xinghuo Yu. Iterative Learning Tracking for Multi-Sensor Systems: A Weighted Optimization Approach. IEEE Transactions on Cybernetics, accepted for publication. |
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ZHANG Fanshou | M.E. Graduated 2018.06 Thesis: Design and Analysis the Algorithms of Smart Car in Environmental Perception and Interaction Co-supervised with Prof. Shuming Tang from Institute of Automation, CAS Following position: Umetrip |
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XU Yun | M.E. Graduated 2017.06 Thesis: Iterative Learning Control under Active Incomplete Data Following position: State Administration of Taxation, PRC Awards: [1] 2017 Excellent Master Thesis of BUCT [2] 2016 China National Scholarship [3] 2015 Top Scholarship of BUCT [4] 2014 Top Scholarship of BUCT Journal Papers: [1] Dong Shen, Yanqiong Jin, Yun Xu. Learning Control for Linear Systems under General Data Dropouts at Both Measurement and Actuator Sides: A Markov Chain Approach. Journal of the Franklin Institute, vol. 354, no. 13, pp. 5091-5109, 2017. [2] Yun Xu, Dong Shen, Xuhui Bu. Zero-Error Convergence of Iterative Learning Control Using Quantized Information. IMA Journal of Mathematical Control and Information, vol. 34, no. 3, pp. 1061-1077, 2017. [3] Yun Xu, Dong Shen, Xiao-Dong Zhang. Stochastic Point-to-Point Iterative Learning Control Based on Stochastic Approximation. Asian Journal of Control, vol. 19, no. 5, pp. 1748-1755, 2017. [4] Dong Shen, Chao Zhang, Yun Xu. Intermittent and Successive ILC for Stochastic Nonlinear Systems with Random Data Dropouts. Asian Journal of Control, vol. 20, no. 3, pp. 1102-1114, 2018. [5] Yun Xu, Dong Shen, Youqing Wang. On Interval Tracking Performance Evaluation and Practical Varying Sampling ILC. International Journal of Systems Science, vol. 48, no. 8, pp. 1624-1634, 2017. [6] Dong Shen, Chao Zhang, Yun Xu. Two Compensation Schemes of Iterative Learning Control for Networked Control Systems with Random Data Dropouts. Information Sciences, vol. 381, pp. 352-370, 2017. [7] Dong Shen, Yun Xu. Iterative Learning Control for Discrete-time Stochastic Systems with Quantized Information. IEEE/CAA Journal of Automatica Sinica, vol. 3, no. 1, pp. 59-67, 2016. |
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JIN
Yanqiong | B.Eng. Graduated 2017.06 Bachelor Thesis: Iterative Learning Control with Data Dropouts at Both Sides Following position: M.E. Candidate, Beihang University Journal Papers: [1] Yanqiong Jin, Dong Shen. Iterative Learning Control for Nonlinear Systems with Data Dropouts at Both Measurement and Actuator Sides. Asian Journal of Control, vol. 20, no. 4, pp. 1624-1636, 2018. [2] Dong Shen, Yanqiong Jin, Yun Xu. Learning Control for Linear Systems under General Data Dropouts at Both Measurement and Actuator Sides: A Markov Chain Approach. Journal of the Franklin Institute, vol. 354, no. 13, pp. 5091-5109, 2017. |
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HAN Jian | M.E. Graduated 2016.06 Thesis: Neural Networks Based Point-to-Point Iterative Learning Control Following position: Ph.D Candidate, University of Amsterdam, The Netherlands Journal Papers: [1] Jian Han, Dong Shen, Chiang-Ju Chien. Terminal Iterative Learning Control for Discrete-Time Nonlinear System Based on Neural Networks. Journal of the Franklin Institute, vol. 355, no. 8, pp. 3641-3658, 2018. [2] Dong Shen, Jian Han, Youqing Wang. Stochastic Point-to-Point Iterative Learning Tracking With Unknown System Matrices. IEEE Transactions on Automation Science and Engineering, vol. 14, no. 1, pp. 376-382, 2017. [3] Dong Shen, Jian Han, Youqing Wang. Convergence Analysis of ILC Input Sequence for Underdetermined Linear Systems. SCIENCE CHINA Information Sciences, vol. 60, ID: 099201, 2017. |
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ZHANG Wei | M.E. Graduated 2016.06 Thesis: Iterative Learning Control for Discrete-time Systems with Randomly Iteration-Varying Lengths Following position: State Grid Corporation of China Journal Papers: [1] Dong Shen, Wei Zhang, Jian-Xin Xu. Iterative Learning Control for Discrete Nonlinear Systems with Randomly Iteration Varying Lengths. Systems & Control Letters, vol. 96, pp. 81-87, 2016. [2] Dong Shen, Wei Zhang, Youqing Wang, Chiang-Ju Chien. On Almost Sure and Mean Square Convergence of P-type ILC Under Randomly Varying Iteration Lengths. Automatica, vol. 63, no. 1, pp. 359-365, 2016. |
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