?姓名：盛立
?系属：测控技术与仪器系


?学位：博士
?职称/职务：教授/副院长

?专业：控制理论与控制工程
?导师类别：博导/硕导

?电子邮箱：shengli@upc.edu.cn

?联系电话：

?通讯地址：青岛市黄岛区长江西路66号

?概况

◎研究方向
[1] 随机系统的控制与滤波
[2] 复杂系统的故障诊断与容错控制
[3] 网络化控制系统

◎教育经历
2006/09
2010/03，江南大学，通信与控制工程学院，博士
2008/10
2009/10, University of Maryland, College Park, U. S., 联合培养博士
2003/09
2006/07，山东师范大学，信息科学与工程学院，硕士
1999/09
2003/07，山东师范大学，信息管理学院，学士

◎工作经历
2018/01－至今，中国石油大学（华东），控制科学与工程学院，测控系，教授
2015/03
2016/03，Brunel University London, U.K., 青年骨干教师
2013/01
2017/12，中国石油大学（华东），信息与控制工程学院，自动化系，副教授
2010/04
2012/12，中国石油大学（华东），信息与控制工程学院，自动化系，讲师

◎学术兼职
Systems Science & Control Engineering编委
第五届中国自动化学会技术过程的故障诊断与安全性专业委员会委员
第七届中国自动化学会青年工作委员会委员
第二届智能物联系统建模与仿真专业委员会委员
IEEE Transactions on Automatic Control, Automatica, IEEE Transactions on Cybernetics, IEEE Transactions on Neural Networks and Learning Systems, Fuzzy Sets and Systems, Systems & Control Letters等国际期刊审稿人

◎主讲课程
本科生课程：自动控制原理、控制系统仿真技术
研究生课程：动态系统的故障诊断与容错控制、控制理论专题

◎指导研究生及博士后
2015级：牛艺春、曾菲
2016级：马萍萍、晁代坤、汤吉瑞
2017级：高晗、牟大伟、杨森、韩玉欣

◎承担项目
[1] 国家自然科学基金面上项目(No. **)，乘性噪声干扰下网络化闭环控制系统的故障检测，2018.01-2021.12，主持；
[2] 山东省重点研发计划(No. 2019GGX101046)，网络化随机系统的故障诊断及其在高速列车制动控制系统中的应用，2019/07-2021/07，主持；
[3] 自主创新科研计划青年基金延续资助项目(No. 17CX02059)，网络化闭环系统的滤波与故障诊断研究，2017/1-2019/12，主持
[4] 青岛市应用基础研究计划项目(No. 16-5-1-3-jch)，随机非线性系统的鲁棒滤波及其在微地震监测中的应用，2016.09-2018.09，10万元，主持；
[5] 国家自然科学基金青年基金(No. **)，基于H-表示的随机Markov跳跃系统的谱分析与H∞控制研究，2015.01-2017.12，主持；
[6] 教育部高等学校博士学科点新教师基金(No.014)，基于谱技术的随机Markov 跳跃系统的能稳性、能观性与鲁棒H∞控制研究，2013.01-2015.12，主持；
[7] 山东省自然科学基金(No. ZR2011FL025)，基于谱技术的随机系统的区域稳定性与控制问题研究，2011.12-2014.12，主持；
[8] 中国石油大学青年骨干教师建设工程项目(No. 12CX02010A)，随机系统的控制与滤波，2013.01-2015.12，主持；
[9] 自主创新科研计划项目(No. 11CX04042A) ，基于T-S模糊模型的Markov跳跃非线性系统的鲁棒控制与滤波研究，2011.04-2013.04，主持。

◎获奖情况
[1] 网络化随机系统的故障检测、估计与鲁棒控制方法及应用，2019年青岛市自然科学奖，青岛市科学技术局，三等奖，盛立(1/5)；
[2] 随机跳变系统的建模、分析与综合，2016年中国自动化学会(CAA)自然科学奖，中国自动化学会，二等奖，盛立(1/4)；
[3] 随机Markov跳跃系统分析与综合的新方法，2014年山东高等学校优秀科研成果奖，山东省教育厅，二等奖，盛立(1/4)；
[4] 传输信道受限下反馈神经网络的同步控制与状态估计，2019年山东省优秀硕士学位论文，山东省教育厅，盛立（导师）。

◎荣誉称号

◎著作

◎论文
[1]L. Sheng*, Y. Niu, M. Gao, D. Zhou. Polynomial filtering for nonlinear stochastic systems with state- and disturbance-dependent noises. International Journal of Robust and Nonlinear Control, Accepted. (SCI二区)
[2] S. Zhang, L. Sheng, M. Gao, D. Zhou. Intermittent fault detection for discrete-time linear stochastic systems with time delay.IET Control Theory & Applications, vol. 14, no. 3, pp. 511-518, 2020.
[3]L. Sheng*, P. Ma, M. Gao. H∞ consensus control with spectrum constraints for stochastic multi-agent systems subject to (x,u,v)-dependent noises. Applied Mathematics and Computation, vol. 362, 124560, 2019. (SCI二区)
[4]L. Sheng*, Z. Wang, B. Shen, M. Gao. On mean-square H∞ control for discrete-time nonlinear stochastic systems with (x,u,v)-dependent noises. International Journal of Robust and Nonlinear Control, vol. 29, pp. 882-893, 2019. (SCI二区)
[5] L. Sheng*, Y. Niu, M. Gao. Distributed resilient filtering for time-varying systems over sensor networks subject to Round-Robin/stochastic protocol. ISA Transactions,vol. 87, 55–67, 2019. (SCI二区)
[6] Y. Niu, L. Sheng*. Uniform quantized synchronization for chaotic neural networks with successive packet dropouts. Asian Journal of Control, vol. 21, no. 1, pp. 639-646, 2019. (SCI四区)
[7] D. Chao, L. Sheng*, Y. Liu, F. E. Alsaadi. Event-based H∞ fault estimation for networked time-varying systems with randomly occurring nonlinearities and (x,v)-dependent noises, Neurocomputing, vol. 285, pp. 220-229, 2018. (SCI二区)
[8]L. Sheng*, Y. Niu, L. Zou, Y. Liu, F. E. Alsaadi. Finite-horizon state estimation for time-varying complex networks with random coupling strengths under Round-Robin protocol. Journal of the Franklin Institute, vol. 355, 7417-7442, 2018. (SCI二区)
[9] L. Sheng, Z. Wang, L. Zou, F. E. Alsaadi. Event-based H∞ state estimation for time-varying stochastic dynamical networks with state- and disturbance-dependent noises. IEEE Transactions on Neural Networks and Learning Systems, vol. 28, no. 10, pp. 2382-2394, 2017. (SCI一区 Top期刊)
[10]L. Sheng, Z. Wang, W. Wang, F. E. Alsaadi. Output-feedback control for nonlinear stochastic systems with successive packet dropouts and uniform quantization effects. IEEE Transactions on Systems, Man and Cybernetics: Systems, vol. 47, no. 7, pp. 1181-1191, 2017. (SCI二区)
[11] L. Sheng, Z. Wang, L. Zou. Output-feedback H2/H∞ consensus control for stochastic time-varying multi-agent systems with (x,u,v)-dependent noises, Systems & Control Letters, vol. 107, pp. 58-67, 2017. (SCI三区)
[12]L. Sheng, Z. Wang, E. Tian, F. E. Alsaadi. Delay-distribution-dependent H∞ state estimation for delayed neural networks with (x,v)-dependent noises and fading channels. Neural Networks, vol. 84, pp. 102-112, 2016. (SCI二区)
[13] Y. Niu, L. Sheng*, W. Wang. Delay-dependent H∞ synchronization for chaotic neural networks with network-induced delays and packet dropouts. Neurocomputing, vol. 214, pp. 7-15, 2016. (SCI二区)
[14]L. Sheng, M. Gao, W. Zhang, B. S. Chen. Infinite horizon H∞ control for nonlinear stochastic Markov jump systems with (x,u,v)-dependent noise via fuzzy approach. Fuzzy Sets and Systems, vol. 273, pp. 105–123, 2015. (SCI二区 Top期刊)
[15]L. Sheng, W. Zhang, M. Gao. Some remarks on infinite horizon stochastic H2/H∞ control with (x,u,v)-dependent noise and Markov jumps. Journal of the Franklin Institute, vol. 352, no. 10, pp. 3929-3946, 2015. (SCI二区)
[16]L. Sheng, W. Zhang, M. Gao. Relationship between Nash equilibrium strategies and H2/H∞ control of stochastic Markov jump systems with multiplicative noise. IEEE Transactions on Automatic Control, vol. 59, no. 9, pp. 2592-2597, 2014. (SCI二区 Top期刊)
[17]L. Sheng*, W. Zhang, M. Gao. Mixed H2/H∞ control of time-varying stochastic discrete-time systems under uniform detectability. IET Control Theory and Applications, vol. 8, no. 17, pp. 1866-1874, 2014. (SCI 三区)
[18]L. Sheng*, M. Gao, W. Zhang. Dissipative control for Markov jump non-linear stochastic systems based on T-S fuzzy model. International Journal of Systems Science, vol. 45, no. 5, pp. 1213-1224, 2014. (SCI 三区)
[19]L. Sheng*, M. Gao, W. Zhang. Spectral characterization for stability and stabilisation of linear stochastic systems with Markovian switching and its applications. IET Control Theory and Applications,vol. 7, no. 5, pp. 730-737, 2013. (SCI 三区)
[20] L. Sheng*, M. Gao. Robust stability of Markovian jump discrete-time neural networks with partly unknown transition probabilities and mixed mode-dependent delays. International Journal of Systems Science, vol. 44, no. 2, pp. 252-264, 2013. (SCI 三区)
[21] L. Sheng*, M. Gao, W. Zhang. General stability of stochastic Markov jump linear systems based on the spectrum technique. Asian Journal of Control, vol. 15, no. 5, pp. 1417-1425, 2013. (SCI 四区)
[22]L. Sheng*, M. Gao. Stabilization for Markovian jump nonlinear systems with partly unknown transition probabilities via fuzzy control. Fuzzy Sets and Systems, vol. 161, no. 21, pp. 2780-2792, 2010. (SCI二区 Top期刊)
[23]L. Sheng, M. Gao, H. Yang. Delay-dependent robust stability for uncertain stochastic fuzzy Hopfield neural networks with time-varying delays. Fuzzy Sets and Systems, vol. 160, no. 24, pp. 3503-3517, 2009. (SCI二区 Top期刊)
[24] X. Bai, Z. Wang,L. Sheng, Z. Wang. Reliable data fusion of hierarchical wireless sensor networks with asynchronous measurement for greenhouse monitoring, IEEE Transactions on Control Systems Technology, vol. 27, no. 3, pp. 1036-1046, 2019. (SCI)
[25] Q. Ye, X. Lou, L. Sheng. Generalized predictive control of a class of MIMO models via a projection neural network. Neurocomputing, vol. 234, pp. 192-197, 2017. (SCI二区)
[26] B. Song, Z. Wang,L. Sheng. A new genetic algorithm approach to smooth path planning for mobile robots. Assembly Automation, vol. 36, no. 2, pp. 138-145, 2016. (SCI四区)
[27] W. Zhang, Y. Zhao, L. Sheng. Some remarks on stability of stochastic singular systems with state-dependent noise. Automatica, vol. 51, no. 1, pp. 273-277, 2015. (SCI二区)
[28] W. Zhang, B. S. Chen, H. Tang,L. Sheng, M. Gao. Some remarks on general nonlinear stochastic H∞ control with state, control and disturbance-dependent noise. IEEE Transactions on Automatic Control, vol. 59, no. 1, pp. 237-242, 2014. (SCI二区 Top期刊)
[29] H. Yang, L. Sheng. Robust stability of uncertain stochastic fuzzy cellular neural networks. Neurocomputing, vol. 73, no. 1-3, pp. 133-138, 2009. (SCI二区)
[30] F. Zeng, L. Sheng*. State estimation for neural networks with random delays and stochastic communication protocol. Systems Science & Control Engineering, vol. 6, no.3, pp. 54-63, 2018. (EI)
[31] P. Ma,L. Sheng*.Static output feedback H2/H∞control with spectrum constraints for stochastic systems subject to multiplicative noises. Systems Science & Control Engineering,vol. 6, no.3, pp. 118-125,2018. (EI)
[32] J. Tang, L. Sheng*. Iterative learning fault-tolerant control for networked batch processes with event-triggered transmission strategy and data dropouts. Systems Science & Control Engineering, vol. 6, no. 3, pp. 44-53, 2018. (EI)
[33]盛立, 高明, 张维海. 基于H表示的时变随机Markov跳跃系统的能观性. 控制与决策, vol. 30, no. 1, pp. 181-184, 2015. (EI)
[34]盛立, 高明. 转移概率部分未知的随机Markov跳跃系统的镇定控制. 控制与决策, vol. 26, no. 11, pp. 1716-1720, 2011. (EI)
[35]L. Sheng, H. Yang. H∞ synchronization of chaotic systems via delayed feedback control. International Journal of Automation and Computing, vol. 7, no. 2, pp. 230-235, 2010. (EI)
[36]盛立, 杨慧中. 一类离散Markov跳变奇异系统的镇定控制. 控制与决策, vol. 25, no. 8, pp. 1189-1194, 2010. (EI)
[37] H. Yang, L. Sheng. Pinning control of a generalized complex dynamical network model. Journal of Control Theory and Applications, vol. 7, no. 1, pp. 1-8, 2009. (EI)

◎专利
[1] 盛立,牛艺春,高明. 一种信号量化情形下的混沌神经网络保密通信方法. 专利号: ZL1.9, 授权公告日: 2019-05-28.
[2] 盛立,牛艺春,高明,刘金鑫, 一种超混沌神经网络遮掩保密通信电路, 专利号：ZL4.X, 授权公告日: 2018-9-11.
[3] 盛立,牛艺春,高明,刘金鑫. 一种时滞神经网络超混沌电路. 专利号: ZL2.X, 授权公告日: 2018-7-17.
[4] 盛立,牛艺春,高明,刘金鑫. 具有脉冲效应的时滞超混沌神经网络电路. 专利号: ZL0.X, 授权公告日: 2017-12-26.