Jia Shi 师佳Associate Professor 副教授


    Main Research Interests/Areas研究领域及兴趣

    主要的研究兴趣是以人的智能行为为导向,探索各类复杂工业过程中的信息处理技术、系统建模技术以及智能控制理论与方法，并以此为基础，进一步研发过程系统仿真平台、先进的自动控制装置和控制系统设计方案。目前主要的研究活动集中在基于数据驱动的过程系统建模、仿真与监测方法，以及面向复杂批次/重复/周期过程的智能控制理论及相关技术。

    Inspired by many intelligent behaviors of human being, my research interesting is covering all the intelligent technologies for the information processing, the process modeling and the intelligent control theories and methods for all kinds of complex industrial processes. On the basis of these technologies and theories, the process simulation platform, the advanced control devices and the automatic control systems will be further developed and designed. My current research areas are mainly focused on the data-driven based process modeling, simulation and monitoring, and the intelligent control theory and technologies for the complex repetitive/batch/periodic processes.


    Learning-based control methods and applications
    基于学习的控制技术与方法研究

    “授人以鱼，不如授人以渔”，在面对越来越复杂的工业系统和生产过程的时候，我们希望教给机器的不是简单的控制方法，而是自己学会控制系统的方法。这就跟我们课题组培养研究生的目标一样，不是简单地传授给他们知识，更重要的是要教给他们高效学习知识的方法。对此我们需要在理解各类人工智能和机器学习算法的基础上，深入研究人类学习的各种范式，进而研究各种高效的智能学习控制算法，并努力将其应用于各类实际系统与工程。
    There is a saying that “it is better to teach one fishing than to give one a fish”. In the face of more and more complex industrial systems and processes, we hope to design an automation that not can control the system, but can learn to control the system by itself. This is the same with the training objective for the graduate students in our group, which is not simply to teach them knowledge, but the more important is to teach them efficient learning methods. We need to learn from various learning methods of human and explore various efficient intelligent learning algorithms on the basis of various artificial intelligence and machine learning algorithms, and then strive to apply them to various practical systems and engineering.


    Current Research Activities目前的主要研究工作

    科学研究上，主要从事面向复杂批次/重复/周期过程的建模、过程信息分析与特征提取以及先进自动控制理论与技术研究，包括：迭代学习辨识、迭代学习控制、模型预测控制、自适应控制、过程统计分析与建模等。

    工程研究上，主要针对复杂批次／重复／周期过程或系统进行控制算法和控制装置研发，主要包括注射成型过程、间歇精馏过程、高精密3维打印机、单分子电导扫描仪等。

    In academic research, my current work is mainly focused on the process modeling, process information analysis, feature detection, and advanced control theories and technologies for the complex batch/repetitive/periodic processes, including: learning based identification, multi-time dimensional iterative learning control, model predictive control, adaptive control, statistical process analysis and modeling.

    In engineering research, my current work is mainly focused on the development of the advanced control algorithms and control devices for the batch/repetitive/periodic processes or systems, such as injection molding machine, batch distillation, 3D printers, single-molecule conductance scanner, etc.

    Education 教育背景

    • PhD. of Engineering, Control Science and Engineering, 06.2001-06.2006. College of Control Science and Engineering, Zhejiang University, P. R. China

    • Master of Science, Operation Research and Cybernetics, 06.1994-06.1997. Department of System Science，Xiamen University, P. R. China

    • Bachelor of Science, Control Science, 06.1990-06.1994. Department of Computer and System Science, Xiamen University, P. R. China

    Research Experience 研究经历

    • 2008-             Associate Professor, Department of Chemical and Biochemical Engineering, Xiamen University, P. R. China

    • 2003-2006   Research Assistant, Department of Chemical and Biomolecular Engineering, The Hong Kong University of Science and Technology, Hong Kong, P. R. China

    • 1999-2007    Assistant Professor, Department of Automation, Xiamen University, P. R. China

    Selected Publications 代表性论文

    1. Yang Y, Cao W, Cao Z, Zhou H, Gao F, Shi J*. “An Integrated Design Method of a Cascade Iterative Learning Control for the Cascaded Batch/Repetitive Processes”. Industrial & Engineering Chemistry Research. (2016), 55 (6): 1598–1608.

    2. Shi J, Yang B, Cao Z, Zhou H, Yang Y. “Two-dimensional Generalized Predictive Control (2D-GPC) Scheme for the Batch Processes with Two-dimensional (2D) Dynamics”. Multidimensional Systems and Signal Processing. (2015), 26(4): 941-966.

    3. Wang L, Yu J, Shi J, Gao F. “Delay-Range Dependent H-inf Control for Uncertain 2D-Delayed Systems”. Numerical Algebra, Control and Optimization. (2015), 5(1): 11-23.

    4. Shi J, Zhou H, Cao Z, Jiang Q. “A design method for indirect iterative learning control based on two-dimensional generalized predictive control algorithm”. Journal of Process Control. (2014), 24(10): 1527-1537.

    5. Shi J, Zhou H, Cao Z, Jiang Q. “A Cascade Iterative Learning Control Scheme for a Class of Repetitive Cascaded Processes”: The 13th International Conference on Control, Automation, Robotics and Vision (ICARCV’14). Singapore: (2014)1449-1454.

    6. Yang B, Shi J, Yang Y, Gao F. “Two Dimensional Predictive Functional Control for Injection Molding Process”: SPE-ANTEC 2014. Las Vegas, Nevada, USA , April 28-30, 2014)2305-2310.

    7. Shi J, Yang Y, Zhou H, Cao Z, Jiang Q. “Synchronization Control Scheme for Multi-Process Systems Based on Model Predictive Control”: The 25th Chinese Control and Decision Conference (2013 CCDC). Guiyang, Guizhou.: 2013)4063-4069.

    8. Shi J, Yang Y, Lu N. “A PID-Type Model Predictive Iterative Learning Control For Injection Molding Process”: The SPE ANTEC@NPE2013 Conference. Cincinnati, Ohio，USA: 2013).

    9. Yang Y, Shi J, Gao F. “Injection velocity control using 2d model predictive iterative learning algorithm”. The SPE ANTEC@NPE2012 Conference. Orlando, Florida，USA, (2012).

    10. Shi J, Jiang Q, Cao Z, Zhou H, Yang Y. “Design method of PID-Type model predictive iterative learning control based on the Two-Dimensional generalized predictive control scheme”: The 12th International Conference on Control, Automation, Robotics and Vision, (ICARCV 2012). Guangzhou, China: (2012)452-457.

    11. Shi J, Yang Y, Gao F. “Injection molding process control using 2D model predictive iterative learning algorithm”. The Polymer Processing Society 26th Annual Meeting (PPS-26). Banff (Canada), (2010).

    12. Shi J, Gao F, Jiang Q, Cao Z. “A Design Framework for Iterative Learning Control (ILC) Based on 2-Dimensional Model Predictive Control (2D-MPC)”. The 21st Chinese Control and Decision Conference (2009 CCDC). Guilin, Guangxi, (2009)

    13. Shi J, Gao F R, Wu T J. “Single-cycle and multi-cycle generalized 2D model predictive iterative learning control (2D-GPILC) schemes for batch processes”. Journal of Process Control. (2007), 17(9): 715-727.

    14. Shi J, Gao F R, Wu T J. “Robust iterative learning control design for batch processes with uncertain perturbations and initialization”. AIChE Journal. (2006), 52(6): 2171-2187.

    15. Shi J, Gao F R, Wu T J. “From two-dimensional linear quadratic optimal control to iterative learning control. Paper 1. Two-dimensional linear quadratic optimal controls and system analysis”. Industrial & Engineering Chemistry Research. (2006), 45(13): 4603-4616.

    16. Shi J, Gao F R, Wu T J. “From two-dimensional linear quadratic optimal control to iterative learning control. Paper 2. Iterative learning controls for batch processes”. Industrial & Engineering Chemistry Research. (2006), 45(13): 4617-4628.

    17. Wang Y Q, Shi J, Zhou D H, Gao F R. “Iterative learning fault-tolerant control for batch processes”. Industrial & Engineering Chemistry Research. (2006), 45(26): 9050-9060.

    18. Shi J, Gao F R, Wu T J. “Integrated design and structure analysis of robust iterative learning control system based on a two-dimensional model”. Industrial & Engineering Chemistry Research. (2005), 44(21): 8095-8105.

    19. Shi J, Gao F R, Wu T J. “Robust design of integrated feedback and iterative learning control of a batch process based on a 2D Roesser system”. Journal of Process Control. (2005), 15(8): 907-924.

    20. 吴微，师佳，周华，曹志凯，江青茵. “基于样条插值模型的间歇精馏模拟与预测控制”. 化工学报. (2012), 63(4): 1124-1131.

    21. 吴微，师佳，周华，曹志凯，江青茵. “基于变增益迭代学习控制算法的多元间歇精馏”. 厦大学报. (2012), 52(3): 336-341.

    22. 师佳，江青茵，曹志凯，周华，高福荣. “基于2 维性能参考模型的2 维模型预测迭代学习控制策略”. 自动化学报. (2013), 39(5): 565-573.

    23. 龚哲衍，曹志凯，周华，江青茵，师佳. “罐头食品蒸汽灭菌过程的数学建模与仿真”. 系统仿真学报. (2013), 25(10): 2492-2498.

    24. 吴微，师佳，周华，曹志凯，江青茵. “基于参数批次调整模型的间歇精馏最小时间优化策略”. 厦门大学学报（自然科学版）. (2013), 52(2): 209-214.

    Monographs 专著

    1. 江青茵，曹志凯，师佳. 《化工过程控制》. 高等教育出版社, (2007).

    Projects 科研项目

    1. 浙江省横店污水处理厂自动控制系统设计（2000）。

    2. 注射成型机的先进计算机控制系统集成开发 （Development of integrated advanced computer control system for injection molding machines）（2004-2006）。

    3. 循环流化床锅炉燃烧过程优化控制（2007-2008）。

    4. 大流量固相萃取仪应用软件开发，项目负责人（2010）。

    5. 小流量固相萃取仪应用软件开发，项目负责人（2011）。

    6. 无辨识自适应控制算法在制丝加料加香过程控制试验（2010-2011）。

    7. 无辨识自适应控制算法在制丝加料加香过程的PLC实现，项目负责人（2011-2012）。

    8. 针对复杂批次过程的2维自校正模型预测控制理论与应用研究，国家自然科学基金（NSFC），项目负责人（2012-2015）。

    9. 机械可控裂结分子电导扫描仪控制系统开发，项目负责人（2014-2016）

    10. 基于过程时段相似性分析的迭代自学习控制算法、理论及应用，国家自然科学基金（NSFC），项目负责人（2016-2019）

    Selected awards 主要获奖

    1. 自然科学一等奖，教育部，批次过程高性能控制系统基础理论研究，第4完成人（2013）。

    2. 科技进步二等奖，福建省，循环流化床（CFB）锅炉燃烧过程优化控制系统，第3完成人（2012）。