招生信息

在自动化、储能、计算机、应用数学等方向招收研究生。欢迎对自动控制、数学优化、氢水储能、人工智能等方向感兴趣的同学联系报考。

基本信息

 

胡建晨 助理教授

网络化系统工程团队

系统工程研究所

信息物理融合系统研究所

智能网络与网络安全教育部重点实验室

自动化科学与工程学院
电子与信息工程学部
西安交通大学

 

联系方式

 邮箱:horace89@xjtu.edu.cn 或 horacehu89@gmail.com

陕西省西安市碑林区咸宁西路28号西安交通大学科学馆247

西安交通大学创新港校区4号巨构4-5045

西安交通大学自动化科学与工程学院

获奖

2020中国自动化学会自然科学二等奖

2019西安交通大学优秀毕业研究生

站点计数器

研究领域

理论研究:

  • 鲁棒与非线性预测控制问题

  • 输出反馈预测控制问题

  • 向量装箱问题

实际应用

  • 云资源调度
  • 建筑能源系统优化调度

  • 含氢新能源电力系统优化调度

  • 多机协同与路径规划

 

研究问题简述

  • 输出反馈鲁棒预测控制引入N个自由控制作用难题难点:N步后的状态估计误差与N步后的未来未知输入信号有关,难以定界。目前进度:我们引入了1个自由控制作用(AJC2018, TFS2019),目前正在给估计误差集合定界,有希望在比较保守的情况下解决。
  • 双层结构滚动优化的递推可行性难题难点:下层滚动优化问题依赖于上层滚动优化问题的解,而上层滚动优化问题难以用一个解析性的动态预测方程描述,递推可行性分析无从入手。目前进度:我们假设上层滚动优化自己递推可行,利用这个信息保证下层也可行(2020TFS),整体上这个问题是hopeless
  • 模型预测控制的实时性问题难点:模型预测控制需要在线求解优化问题,有的系统实时性要求高。目前进度:我们通过离线求解(IJRNC2019, TFS2022),在采样间隔而非采样时刻的一步超前求解(EJC2020),改变决策变量(Auto2019, TCASII2021)等方法通过牺牲性能、计算并行等方法降低在线计算量,这块各种各样的研究很多,不难解决。
  • 障碍函数预测控制问题难点:直接将采用障碍函数法的优化问题求解和预测控制优化统一成单层优化,将内点法的动态特性系统地考虑在滚动优化过程中,自己编写迭代求解的算法,大大提高优化效率。目前进度:初步判断是很好的、可行的策略,没人资助,没时间开展。
  • 高效大规模动态向量装箱问题难点:实时性要求过高,难以采用整数规划求解,而启发式算法性能没有保障、也不够灵活。目前进度:算法一拍脑袋可以想一堆,理论的研究几乎是零。装箱问题理论偏向数学,太难,碎片化的时间不够研究数学。
  • 复杂约束下优化问题递推可行性问题难点:复杂约束下优化问题当前时刻可行能否保证其在下一个时刻仍可行?这与未来场景的选择相关。需要寻找未来场景的构造通用方法,以及递推可行性保障的要素。目前进度:与实际应用背景相关,目前正在思考和提炼其中的共性问题。

工作经历

  • 2021.9-至今 四川数字经济产业发展研究院 特聘研究员
  • 2020.4-至今 西安交通大学 助理教授/博士后 (Assistant Professor/PostDoc in Xi'an Jiaotong University)
  • 2014.5-2015.8 西安航天自动化股份有限公司 陕西省物联网与智能控制工程研发中心 项目经理/硬件工程师 (PM/Hardware Engineer in Xi'an Aerospace Automation Co., Ltd )

教育经历

  • 2015.9-2019.12 西安交通大学 博士 控制科学与工程 (Ph.D. in Xi’an Jiaotong University)
  • 2011.8-2013.12 亚利桑那州立大学 硕士 电子工程技术 (M.S. in Arizona State University)
  • 2007.9-2011.5 西北大学 学士 电子科学与技术 (B.S. in Northwest University)

学术论文审稿人

IEEE Transactions on Automatic Control, Automatica, IEEE Transactions on Fuzzy Systems, IEEE Transactions on Information Forensics and Security, IEEE Transactions on Industrial Informatics, IEEE Transactions on Cognitive and Development Systems, International Journal of Robust and Nonlinear Control, IEEE Transaction on Automation Science and Engineering, IEEE Transactions on Cybernetics, IEEE Robotics and Automation Letters, Journal of the Franklin Institute, International Journal of Production Research, Results in Control and Optimization, Mathematical Problems in Engineering, IEEE Access, 控制与决策, IFAC Conference on NMPC, Asian Control Conference, 中国自动化大会.

论文发表

2022

  1. Jianchen Hu, Xunhang Sun, Meng Zhang, Peng Shi. An off-line fuzzy model predictive control approach using cache. IEEE Transactions on Fuzzy Systems, 30(10): 4504-4514, 2022.

  2. Jianchen Hu, Baocang Ding, Meng Zhang, Jun Zhao, Zuhua Xu, Hongguang Pan. Enhancing output feedback robust MPC via lexicographic optimization. IEEE Transactions on Industrial Informatics, on-line, 2022.

  3. Jianchen Hu, Xingqi Li, Zhanbo Xu, Hongguang Pan. Co-design of Quantized Dynamic Output Feedback MPC for Takagi-Sugeno Model. IEEE Transactions on Industrial Informatics, on-line, 2022.

  4. Jianchen Hu, Xiaoliang Lv, Hongguang Pan, Meng Zhang. Handling the Constraints in Min-Max MPC. IEEE Transactions on Automation Science and Engineering, on-line, 2022.

  5. Xubin Ping, Jianchen Hu, Tingyu Lin, Baocang Ding, Peng Wang, Zhiwu Li. A survey of output feedback robust MPC for linear parameter varying systems. IEEE/CAA Journal of Automatica Sinica, 9(10): 1717-1751, 2022.

  6. Chunxiang Zhou, Lei Yang, Jianchen Hu, Zhanbo Xu, Xiaohong Guan. Double-layered model predictive control for building HVAC systems considering thermal comfort. IFAC workshop on Control of Smart Cities, Sozopol, Bulgaria, June 27-30, 2022.

  7. Xuke Fu, Deming Wang, Jianchen Hu, Junhu Wei, Chao-Bo Yan. Leader-follower based two-AGV cooperative transportation system in 5G environment. IEEE 18th International Conference on Automation Science and Engineering (CASE), Mexico City and Chengdu, Mexico, August 20-24, 2022, pp. 67-72.

2021

  1. Jianchen Hu, Baocang Ding. A periodic approach to dynamic output feedback MPC for quasi-LPV model. IEEE Transactions on Automatic Control, 66(5): 2257-2264, 2021. 

  2. Jianchen Hu. Dynamic output feedback MPC of polytopic uncertain systems: Efficient LMI conditions. IEEE Transactions on Circuits and Systems-II: Express Briefs, 68(7):2568-2572, 2021.

  3. Jianchen Hu, Baocang Ding. Output feedback robust MPC for uncertaint norm-bounded linear systems with disturbance. International Journal of Control, 94(9):2388-2395, 2021. 

  4. Jun Wang, Baocang Ding, Jianchen Hu. Security control for LPV system with deception attacks via model predictive control: A dynamic output feedback approach. IEEE Transactions on Automatic Control, 66(2): 760-767, 2021.

2020

  1. Jianchen Hu, Baocang Ding. Output feedback MPC with steady state target calculation for fuzzy systems. IEEE Transactions on Fuzzy Systems, 28(12): 3442-3449, 2020.

  2. Jianchen Hu, Baocang Ding. Off-line output feedback robust MPC with general polyhedral and ellipsoidal true state bound. Journal of the Frankline Institure, 357(8): 4505-4523, 2020.

  3. Jianchen Hu, Baocang Ding. One-step ahead robust MPC for LPV model with bounded disturbance. European Journal of Control, 52:59-66, 2020.  

  4. Jianchen Hu, Baocang Ding. Heuristic open-loop output feedback MPC for control of intermittent transonic wind tunnel. Transactions of the Institute of Measurement and Control, 42(4): 832-839, 2020. 

  5. Baocang Ding, Jianchen Hu, Xiaoming Tang, Jun Wang. A synthesis approach to output feedback MPC for LPV model with bounded disturbance. IEEE Access, 8: 228337-228348, 2020.

  6. 胡建晨, 王勇, 丁宝苍. 一种开环输出反馈预测控制, 控制理论与应用, 37(1): 31-37, 2020.

2019

  1.  Jianchen Hu, Baocang Ding. Output feedback robust MPC for linear systems with norm-bounded uncertainty and disturbance. Automatica, 108: 1-7, 2019. 

  2. Jianchen Hu, Baocang Ding. Dynamic output feedback predictive control with one free control move for the Takagi-Sugeno model with bounded disturbance. IEEE Transactions on Fuzzy Systems, 27(3): 462-473, 2019. 

  3. Jianchen Hu, Baocang Ding. An efficient offline implementation for output feedback min-max MPC. International Journal of Robust and Nonlinear Control, 29(2): 492-506, 2019.  

  4. Jianchen Hu, Baocang Ding. Dynamic output feedback robust MPC with convex optimisation for system with polytopic uncertainty. International Journal of Systems Science, 50(4): 739-748, 2019. 

  5. Baocang Ding, Jie Dong, Jianchen Hu. Output feedback robust MPC using general polyhedral and ellipsoidal true state bounds for LPV model with bounded disturbance. International Journal of Systems Science, 50(3): 625-637, 2019. 

  6. Baocang Ding, Xiaoming Tang, Jianchen Hu. A summary of dynamic output feedback robust MPC for linear polytopic uncertainty model with bounded disturbance. Mathematical Problems in Engineering, 3830724: 1-19, 2019.

  7. Jianchen Hu, Baocang Ding, Yong Wang, Jun Zhao, Tao Zou, Yuuanqing Yang, Xubin Ping. An efficient approach for dynamic output feedback robust model predictive control. Proceeding of the 12th Asian Control Conference (ASCC2019), Kitakyushu, Fukuoka, Japan, June 9-12, 1283-1288, 2019.

2018

  1. Baocang Ding, Pengjun Wang, Jianchen Hu. Dynamic output feedback robust MPC with one free control move for LPV model with bounded disturbance. Asian Journal of Control, 20(2): 755-767, 2018.

  2. Jianchen Hu, Baocang Ding. An off-line output feedback MPC strategy for nonlinear systems represented by quasi-LPV model. Proceeding of the 6th IFAC Conference on NMPC, Madison, WI, U.S., August 19-22, 51(20): 66-71, 2018.