导师姓名

杨煜普
研究方向 智能控制理论及应用;智能信息处理与机器学习
联系方式
通讯地址:200240, 上海市闵行区东川路800号,上海交通大学电子电信学院自动化系
邮政编码:200030
联系电话:021-34204427
Email:ypyang@sjtu.edu.cn
个人简介

   杨煜普,1957.11出生, 博士,上海交通大学电子信息与电气工程学院自动化系教授、博士生导师。中国科技大学控制科学与工程专业学士、硕士;上海交通大学控制科学与工程专业博士、博士后。 1982-1984,1988-1991在中国科学院合肥智能机械研究所工作,1996起上海交通大学自动化系工作至今。长期从事智能控制理论与应用、工业过程建模与控制、自动检测与自动化装置领域的科研与教学工作。任中国自动化学会应用委员会委员,上海市仪器仪表学会理事。 主持或主要参加国家、上海市及企业委托课题十余项,其中包括《气体超声波流量计研制》项目(获中国科学院科技进步一等奖,1985年);《非线性预测控制技术及在连续生产过程中的应用》项目(获上海市年科技进步三等奖 1998年);美国宇航局(NASA)颁发的“阿尔法磁谱仪项目特殊贡献嘉许奖” (2011年)。 2004-2011参加丁肇中教授领导的大型国际合作项目《国际空间站上的阿尔法磁谱仪实验(AMS02计划)》,负责其中的《低温超流氦太空超导磁体地面实验控制系统》研制工作。在丁肇中教授直接领导下进行阿尔法磁谱仪核心部件地面运行实验相关测控工作(欧洲核子研究中心CERN,日内瓦),具体包括太空超导磁体的超流氦输送控制、液氦杜瓦超流氦相变控制、1.8K超低温运行监控、高能加速器粒子束的标定实验监控、以及在欧洲宇航局空间测试中心(ESTE,荷兰)的太空环境绝热测试与电磁兼容性测试时的超导磁体运行监控等一系列极高可靠性要求的控制任务,得到美国洛克希德-马丁公司及法国国家强磁场实验室等有关专家的高度认可。也得到丁肇中教授的多次肯定:“上海交大杨煜普教授所做的软件为实验做出了重要贡献”。阿尔法磁谱仪于2011.5.16由美国奋进号航天飞机成功送往国际空间站,丁肇中教授评价“上海交大”做出了“决定性”的贡献。2011年获得美国宇航局(NASA)颁发的“阿尔法磁谱仪项目特殊贡献嘉许奖”。 发表论文150余篇;授权发明专利7项;软件著作权3项。 研究方向: 1 智能控制理论与应用 2 自动化系统与智能化装置 3 控制优化与机器学习 联系方式: Tel: 021-34204038(O) Email: ypyang@sjtu.edu.cn 通讯地址:200240, 上海市闵行区东川路800号,上海交通大学电子电信学院自动化系

代表性论著
[1] Yang Yupu, Xu Xiaoming and Zhang Wengyuan, Real-time stable self-learning FNN controller using genetic algorithm, Fuzzy Sets and Systems, Vol.100, No.1, pp173-178, 1998 (SCI) [2] Yang Yupu, Xu Xiaoming and Zhang Wengyuan, Design neural networks based fuzzy logic, Fuzzy Sets and Systems, Vol.114, No.2, pp325-328, 2000 (SCI) [3] Wei Li, Yupu Yang, Zhong Yang. T-S fuzzy modeling based on support vector learning, Lecture Notes in Computer Science, Vol. 4113 pp1294-1299. 2006 (EI) [4] Wei Li, Yupu Yang, A new approach to TS fuzzy modeling using dual kernel-based learning machines, Neurocomputing, Vol. 71, pp3660-3665, 2008 (SCI) [5] Yujia Wang, Yupu Yang, Handling Multi-objective Problems with A Novel Interactive Multi-swarm PSO, Advanced Intelligent Computing Theories and Applications, Vol.52, No.27, pp 575-582. 2008 (SCI) [6] X.B. He, Y.P. Yang, Variable MWPCA for adaptive process monitoring, Industrial and Engineering Chemistry Research, Vol.47, pp419-427, 2008 (SCI) [7] Wang Na, Yang Yupu, A fuzzy modeling method via enhanced objective cluster analysis for designing TSK model, Expert Systems with Applications. Vol.36, No.10, pp12375-12382, 2009 (SCI) [8] Liang Zhao, Yupu Yang, PSO-based single multiplicative neuron model for time series prediction, Expert Systems with Applications, Vol.36, pp2805-2812, 2009 (SCI). [9]Liang Zhao, Yupu Yang, Eliciting compact T-S fuzzy models using subtractive clustering and co-evolutionary particle swarm optimization, Neurocomputing, Vol.72, pp2569-2575, 2009(SCI). [10] Yujia Wang, Yupu Yang, Particle swarm optimization with preference order ranking for multi-objective optimization, Information Sciences. Vol. 17, No.12, pp1944-1959, 2009. (SCI) [11] Yong Zeng, Yupu Yang, and Liang Zhao, Nonparametric classification based on local mean and class statistics, Expert Systems with Applications, Vol.36, No.4, pp8443-8448, 2009. (SCI) [12] Yong Zeng, Yupu Yang, Liang Zhao, Pseudo nearest neighbor rule for pattern classification, Expert Systems with Applications, Vol.36, No.2, pp3587-3595, 2009. (SCI) [13] Ke, Peng, Yupu Yang, Leading-following consensus problem with a varying-velocity leader and time-varying delays, Physica A: Statistical Mechanics and its Applications, Vol.308, pp193-208, 2009 (SCI) [14] X.B. He, Y.P. Yang, Y.H. Yang, Variable-weighted fisher discriminate analysis for process fault diagnosis, Journal of Process Control, Vol. 19, No. 6, pp923-931, 2009 (SCI) [15] Wei Li, Yupu Yang, Hybrid kernel learning via genetic optimization for T-S fuzzy system identification, International Journal of Adaptive Control and Signal Processing, Vol;37, No.2, pp1216-1222, 2010 (SCI) [16] Zhong Yang, Yu-pu Yang, New delay-dependent stability analysis and synthesis of T-S fuzzy systems with time-varying delay, International Journal of Robust and Nonlinear Control. Vol.20, No. 3, pp313-322, 2010 (SCI) [17] Liang Zhao, Feng Qian, Yupu Yang, Automatically extracting T-S fuzzy models using cooperative random learning particle swarm optimization, Applied Soft Computing, Vol.10, No.3, pp938-944, 2010 (SCI) [18] Ke Peng, Yupu Yang, Collective tracking control for multi-agent system on balanced graphs, Asian Journal of Control, Vol.13, No.4, pp505-512, 2011(SCI) [19] Wei Li, Yupu Yang, Zhong Yang, Fuzzy system identification based on support vector regression and genetic algorithm, International Journal of Modeling, Identification and Control,Vol.12, No.1, pp50-55,2011 (SCI,EI) [20] Haijun Su, Yupu Yang, Differential evolution and quantum-inquired differential evolution for evolving Takagi–Sugeno fuzzy, Expert Systems with Applications, Vol.38, No.6, pp6447-6451,2011 (SCI)