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研究领域与方向:控制系统的稳定性理论、故障诊断和安全可靠性以及优化协调控制理论。

具体学术研究方向为:递归神经网络稳定性理论、智能系统理论、复杂动力网络的同步与控制、故障诊断和容错控制、非线性时滞系统控制理论、无功补偿与优化控制、电力系统安全稳定控制及其在智能电网中的应用等。

 

总论

在稳定性理论方面取的主要研究成果:

1) 基于分解与合成原理,提出了时滞矩阵分解方法,对含有形式如$x_j(t-\tau_{ij})$等一类时滞项或耦合项的非线性系统,建立了基于矩阵不等式的稳定性判据,为这类非线性系统的综合提供了理论基础。

2) 基于变步长采样原理,针对固定时滞区间$[\tau_m, \tau_M]$,提出了不等划分的时滞加权的内插值方法,拓展了等划分时滞区间的时滞分解方法;采用凸组合原理,将固定时滞终端转化为含有可调参数的柔性终端,进而将固定时滞区间转化为动态收缩时滞区间,由此提出了含有柔性终端的外压缩时滞区间方法,这两类方法从不同的方式(内插值,外压缩)来改变时滞区间的大小,进而实现多步累积、空间增维的目的,基于上述两种方法及相应的求导方法并构造适宜的李雅普诺夫函数,建立了基于矩阵不等式的稳定判据。

3) 通过同步比较研究,揭示了李雅普诺夫函数意义下的稳定性及非线性自治系统$\dot x=f(x)$中要求$f(0)=0$的内涵,由此指出了Lyapunov理论中所考虑的非线性系统本质上就是一个误差动力系统,是相对于系统内部某个固有平衡点的误差系统(自稳定);同步性概念则是系统自稳定概念拓展,是相对于系统外的某个系统的动态或某个指定参考目标的稳定;自稳定是相对于调节作用,同步相当于跟踪作用。由此统一了稳定性与同步性的认识,稳定性本质就是相对静止,稳定性是竞争合作的相对静止状态! 

  

在故障诊断和优化控制方面的主要研究成果待整理。

 

 

一、论文专著

学术著作

 (1)  张化光, 季策, 王占山, 译著,递归人工神经网络的定性分析和综合,北京: 科学出版社,2004

(2) 王占山 著,连续时间时滞递归神经网络的稳定性,沈阳:东北大学出版社,   2007

(3)  王占山 著,复杂神经动力网络的稳定性和同步性,北京:科学出版社,2014

      (4) Zhanshan Wang, Zhenwei Liu, Chengde Zheng, Qualitative Analysis and Control of Complex Neural Networks with Delays,     

            Science Press and Springer, 2015

(5) 王占山,单麒赫,季策,编著,动力系统基础及其稳定特性分析,东北大学出版社,2015.

(6) 王占山,关焕新,编著, 智能控制及其在电力系统中的应用,东北大学出版社,2015.

 

教材: 

(7) 孙秋野,王占山,马大中,电力系统自动化,人民邮电出版社,20143

  

()、动力系统的稳定性、同步性和一致性

  

1.       Wang Zhanshan, Zhang Huaguang, Jiang Bin, LMI-based approach for global asymptotic stability analysis of recurrent neural networks with various delays and structures, IEEE Transactions on Neural Networks, 2011, 22(7): 1032-1045.

2. Wang Zhanshan, Zhang Huaguang, Li Ping, An LMI approach to stability analysis of reaction-diffusion Cohen-Grossberg neural networks concerning Dirichlet boundary conditions and distributed delays,  IEEE Transactions on Systems Man and Cybernetics Part B-Cybernetics, 2010, 40(6): 1596-1606.

3. Wang Zhanshan, Zhang Huaguang, Global asymptotic stability of reaction-diffusion Cohen-Grossberg neural networks with continuously distributed delays, IEEE Transactions on Neural Networks, 2010, 21(1): 39-49.

4. Wang Zhanshan, Zhang Huaguang, Yu Wen, Robust stability of Cohen-Grossberg neural networks via state transmission matrix, IEEE Transactions on Neural Networks, 2009, 20(1): 169-174.   

5. Zhanshan Wang, Lei Liu, Qihe Shan, Huaguang Zhang, Stability Criteria for Recurrent Neural Networks With Time-Varying Delay Based on Secondary Delay Partitioning Method, IEEE Transactions on Neural Networks and Learning Systems, DOI: 10.1109/TNNLS.2014.2387434  (to appear in 2015)

6. Huaguang Zhang; Zhanshan Wang; Derong Liu, A Comprehensive Review of Stability Analysis of Continuous-Time Recurrent Neural Networks, IEEE Transactions on Neural Networks and Learning Systems; Volume 25, Issue 7, 1229 -1262, July , 2014.

7. Zhang Huaguang, Wang Zhanshan, Liu Derong, Global asymptotic stability and robust stability of a class of Cohen-Grossberg neural networks with mixed delays, IEEE Transactions on Circuits and Systems I-Regular Papers, 2009, 56(3): 616-629.

8. Zhang Huaguang, Wang Zhanshan, Liu Derong, Global asymptotic stability of recurrent neural networks with multiple time-varying delays, IEEE Transactions On Neural Networks, 2008, 19(5): 855-873.

9. Zhang Huaguang, Wang Zhanshan, Liu Derong, Robust Stability Analysis for Interval Cohen-Grossberg Neural Networks With Unknown Time-Varying Delays, IEEE Transactions On Neural Networks, 2008, 19(11): 1942-1955.

10.   Zhang Huaguang, Wang Zhanshan, Global asymptotic stability of delayed cellular neural networks, IEEE Transactions on Neural Networks, 2007, 18(3): 947-950.

11.   Huaguang Zhang Zhanshan Wang Derong Liu, Robust Exponential Stability of Recurrent Neural Networks With Multiple Time-Varying Delays, IEEE Transactions on Circuits and Systems II: Express Briefs, vol. 54, no. 8, pp. 730-734, 2007. 

12.   Zhang HuaGuang, Wang ZhanShan, New delay-dependent criterion for the stability of recurrent neural networks with time-varying delay, Science in China Series F-Information Sciences, 2009, 52(6): 942-948.

13.   Huaguang Zhang, Junyi Wang, Zhanshan Wang, Hongjing Liang, Mode-Dependent Stochastic Synchronization for Markovian Coupled Neural Networks With Time-Varying Mode-Delays, IEEE Transactions on Neural Networks and Learning Systems, DOI: 10.1109/TNNLS.2014.2387885 (to appear in 2015)

14.   Zhang Huaguang, Liu Zhenwei, Huang Guang-Bin, Wang Zhanshan, Novel weighting delay based stability criteria for recurrent neural networks with time-varying delay, IEEE Transactions on Neural Networks, 2010, 21(1): 91-106.

15.   Zheng Cheng-De, Zhang Huaguang, Wang Zhanshan, Novel exponential stability criteria of high-order neural networks with time-varying delays, IEEE Transactions on Systems Man and Cybernetics Part B-Cybernetics, 2011, 41(2): 486-496.

16.   Zheng Cheng-De, Zhang Huaguang, Wang Zhanshan, Improved robust stability criteria for delayed cellular neural networks via the LMI approach, IEEE Transactions on Circuits and Systems II-Express Briefs, 2010, 57(1): 41-45.

17.   Zheng Cheng-De, Zhang Huaguang, Wang Zhanshan, Delay-dependent globally exponential stability criteria for static neural networks: an LMI approach, IEEE Transactions on Circuits and Systems II-Express Brief, 2009, 56(7): 605-609.

18.   Zheng Cheng-De, Zhang Huaguang, Wang Zhanshan. New delay-dependent global exponential stability criterion for cellular-type neural networks with time-varying delays, IEEE Transactions on Circuits and Systems II-Express Briefs, 2009, 56(3): 250-254.         

19.   Zheng Cheng-De, Zhang Huaguang, Wang Zhanshan, An augmented LKF approach involving derivative information of both state and delay, IEEE Transactions on Neural Networks, 2010, 21(7): 1100-1109.     

20.   Cheng-De Zheng, Qi-He Shan, Huaguang Zhang, Zhanshan Wang, On Stabilization of Stochastic Cohen-Grossberg Neural Networks With Mode-Dependent Mixed Time-Delays and Markovian Switching IEEE Transactions on Neural Networks and Learning Systems, vol. 24, no. 5, pp. 800-811, 2013. 

21.   ZhanshanWang, Huaguang.Zhang, Synchronization stability in complex interconnected neural networks with nonsymmetric coupling, Neurocomputing, vol. 108, pp. 84-92, 2013,

22.   Wang Zhanshan, Zhang Enlin, Zhang Huaguang, Ren Zhengyun, Global stability analysis of multitime-scale neural networks,: Neural Computing & Applications, 2013, 22(2): 211-217.

23.   Wang Zhanshan, Zhang Huaguang, Yu Wen, Robust stability criteria for interval Cohen-Grossberg neural networks with time varying delay, Neurocomputing, 2009, 72(4-6): 1105-1110.

24.   Wang Zhanshan, Zhang Huaguang, Yu Wen, Robust exponential stability analysis of neural networks with multiple time delays, Neurocomputing, 2007,70(13-15): 2534-2543.

25.   Wang Zhanshan, Zhang Huaguang, Exponential stability analysis of neural networks with multiple time varying delays, Chinese Journal of Electronics, 2006, 15(4): 649-653.

26.   Wang Zhanshan, Zhang Huaguang, LMI-based criteria for globally asymptotic stability of cellular neural networks with multiple delays, Chinese Journal of Electronics, 2007, 16(1): 111-114.

27.   Wang Zhanshan, Zhao Yongbin, Lun Shuxian, Global stability of a class of high-order recurrent neural networks with multiple delays, Lecture Notes in Computer Science, v 7366 LNAI, p 268-277, 2012,

28.   Wang, Zhanshan, Zhang Enlin, Yun Kuo, Zhang Huaguang, Universal analysis method for stability of recurrent neural networks with different multiple delays, Lecture Notes in Computer Science, v 6675 LNCS, PART 1, p 148-157, 2011.

29.   Wang Zhanshan, Zhang Huaguang, Feng Jian, Stability Analysis of Recurrent Neural Networks with Distributed Delays Satisfying Lebesgue-Stieljies Measures, Lecture Notes in Computer Science, vol. 6063, pp. 504-511, Part I, 2010.

30.   Zhang Huaguang, Wang Zhanshan, Liu Derong,  Exponential stability analysis of neural networks with multiple time delays, Lecture Notes in Computer Science, v 3496, pp 142-148, 2005

31.   Zhang Huaguang, Wang Zhanshan, Globally exponential stability analysis and estimation of the exponential convergence rate for neural networks with multiple time varying delays, Lecture Notes in Computer Science, v 3610, n PART I, p 61-70, 2005.

32.   Hongjing Liang, Huaguang Zhang, Zhanshan Wang, Junyi Wang, Consensus robust output regulation of discrete-time linear multi-agent systems, IEEE/CAA Journal of Automatica Sinica, vol. 1, no. 2, 204-209, 2014.

33.   Junyi Wang , Huaguang Zhang,  Zhanshan Wang , Hongjing Liang, Stochastic synchronization for Markovian coupled neural networks with partial information on transition probabilities,  Neurocomputing, Volume 149, Part B, 3 February 2015, Pages 983–992

34.   Huang, Yujiao, Zhang, Huaguang; Wang, Zhanshan, Multistability of complex-valued recurrent neural networks with real-imaginary-type activation functions, Applied Mathematics and Computation, v 229, p 187-200, February 25, 2014

35.   Wang, Junyi, Zhang, Huaguang; Wang, Zhanshan; Liang, Hongjing, Stochastic synchronization for Markovian coupled neural networks with partial information on transition probabilities,  Neurocomputing, December 07, 2013

36.   Cheng-De Zheng, Huaguang Zhang and Zhanshan Wang, New less-conservative stability results for uncertain stochastic neural networks with fewer slack variables, International Journal Of Robust And Nonlinear Control 2013; 23:731–753.

37.   Zhang Huaguang, Huang Bonan; Gong Dawei, Wang, Zhanshan, New results for neutral-type delayed projection neural network to solve linear variational inequalities, Neural Computing and Applications, v 23, n 6, p 1753-1761,  2013

38.   Gong Dawei, Huaguang Zhang, Zhanshan Wang, Dazhong Ma, Synchronization criteria for an array of neutral-type neural networks with hybrid coupling: a novel analysis approach, Neural Processing Letters, Volume, 35, no. 1, pp. 29-45, 2012.

39.   Gong Dawei, Huaguang Zhang, Zhanshan Wang, Bonan Huang, Novel synchronization analysis for complex networks with hybrid coupling by handling multitude Kronecker product terms, Neurocomputing, Volume, vol. 82, pp. 14-20,  April 1, 2012,

40.   Huang Yujiao, Zhang Huaguang, Wang Zhanshan, Dynamical stability analysis of multiple equilibrium points in time-varying delayed recurrent neural networks with discontinuous activation functions, Neurocomputing, vol. 91, pp. 21-28, AUG 15 2012

41.   Feng Jian, Wang Shenquan, Wang Zhanshan, Stochastic synchronization in an array of neural networks with hybrid nonlinear coupling, Neurocomputing, 2011, 74(18): 3808-3815.

42.   Zheng Cheng-De, Zhang Huaguang, Wang Zhanshan, Novel delay-dependent criteria for global robust exponential stability of delayed cellular neural networks with norm-bounded uncertainties, Neurocomputing, 2009, 72(7-9): 1744-1754.

43.   Liu Zhenwei, Zhang Huaguang, Wang Zhanshan, Novel stability criterions of a new fuzzy cellular neural networks with time-varying delays, Neurocomputing, 2009, 72(4-6): 1056-1064. 

44.   王占山,王军义,梁洪晶,复杂网络的相关研究及其进展,中国自动化学会通讯,2013 341):4-16

45.   王占山, 张化光,余文,张庆灵,基于LMI的时变时滞Cohen-Grossberg神经网络鲁棒稳定性,电子学报,2008, 36(11): 2220-2223.

46.   王占山,张化光,时滞递归神经网络中神经抑制的作用,物理学报,200655(11): 5674-5680.

47.   钟向楠,王占山,张化光,转移概率部分未知的不确定Markov跳变系统的鲁棒镇定。吉林大学学报(工学版),2012,426): 1558-1562.

48.   季策,张化光,王占山,一类具有时滞的广义Hopfield神经网络的全局稳定性,控制与决策,2004 19(8): 935-938.

  

(二)、动力系统的故障诊断、容错控制与安全运行

  

1.         Zhang Huaguang, Liu Jinhai, Ma Dazhong, Wang Zhanshan, Data-core-based fuzzy min-max neural network for pattern classification, IEEE Transactions on Neural Networks, 2011, 22(12-2): 2339-2352..

2.         Wang Zhanshan, Li Tieshan, Zhang Huaguang, Fault tolerant synchronization for a class of complex interconnected neural networks with delay, International Journal of Adaptive Control and Signal Processing, 2014, 28: 859–881.

3.         Zhanshan Wang, Huanxin Guan, and Chengde Zheng, Fault Diagnosis Observer Design for Discrete-Time Delayed Complex Interconnected Networks with Linear Coupling, Mathematical Problems in Engineering, Volume 2012, Article ID 860489, 22 pages.

4.         Wang Zhanshan, Cai Chao,Wang Junyi, Zhang, Huaguang, Adaptive fault estimation of coupling connections for synchronization of complex interconnected networks, International Symposium on Neural Networks, 2013, 455-462.

5.         Zhanshan Wang, Fufei Chu, Hongjing Liang,Huaguang Zhang, Fault accommodation for complete synchronization of complex neural networks, 2013 IEEE Symposium on Adaptive Dynamic Programming And Reinforcement Learning (ADPRL), 2013 , 200 – 205

6.         Zhanshan Wang and Huaguang Zhang, Design of a bilinear fault detection observer for singular bilinear systems, Journal of Control Theory and Applications, 2007, 5(1): 28-36.

7.         Zhanshan Wang Huaguang Zhang, Design of bilinear observer for singular bilinear systems, Journal of Control Theory and Applications, 2006,4(4):413-417.

8.         Liu Lei, Wang Zhanshan, Zhang Huaguang, Adaptive NN fault-tolerant control for discrete-time systems in triangular Forms with actuator fault, Neurocomputing, 2015, 152: 209-221.

9.         Lei Liu, Zhanshan Wang, Jinhai Liu, Zhenwei Liu, Neural-Network-Based Adaptive Fault Estimation for a Class of Interconnected Nonlinear System with Triangular Forms, Lecture Notes in Computer Science, 2014, 8866: 110-120.

10.     Ma Da-Zhong, Zhang Hua-Guang, Wang Zhan-Shan, Fault tolerant synchronization of chaotic systems based on T-S fuzzy model with fuzzy sampled-data controller, Chinese Physics B, 2010, 19(5): 0505061-05050611 

11.     Ma Da-Zhong, Zhang Hua-Guang, Wang Zhan-Shan, Fault tolerant synchronization of chaotic systems based on T-S fuzzy model with fuzzy sampled-data controller, Chinese Physics B, 2010, 19(5): 0505061-05050611.

12.     王占山,张恩林,张化光,冯健,基于Hopfield神经网络的非线性系统故障估计方法,南京航空航天大学学报,201143(增刊)18-21. 7

13.     王占山,张化光,故障估计的自适应观测器设计,东北大学学报(自然科学版)200526(1): 221-224.

14.     张化光,马大中,王占山,冯健. 一类多时滞混沌系统的主从容错同步,物理学报,2010, 59(1): 147-156.

15.     王占山,张化光,状态和输入多时变时滞非线性系统的干扰补偿控制器设计, 应用科学学报, 2005, 23(2)144-147.

16.     王占山,张化光,王智良,Lipschitz非线性系统的鲁棒干扰抑制能力, 东北大学学报(自然科学版)2004 25(5): 457-459.

17.     王占山,李奇安,李平,不确定时滞线性系统的鲁棒容错控制,石油化工高等学校学报,200114(2): 74-78.

18.     王占山,李平,任正云,李奇安,非线性系统的故障诊断技术,自动化与仪器仪表,2001, 58-10.

19.     王占山,李平,任正云,广义线性系统的鲁棒镇定分析,抚顺石油学院学报,2000 20(4): 73-75.

  

(三)、动力系统的优化控制 

 

1.         Xiangnan Zhong, Haibo He, Huaguang Zhang, and Zhanshan Wang, Optimal Control for Unknown Discrete-Time Nonlinear Markov Jump Systems Using Adaptive Dynamic Programming, IEEE Transactions on Neural Networks and Learning Systems, vol. 25, no. 12, 2141-2155, 2014.

2.         Zhanshan Wang, Longhu Quan, and Xiuchong Liu, Sensorless SPMSM Position Estimation Using Position Estimation Error Suppression Control and EKF in Wide Speed Range, Mathematical Problems in Engineering,  vol. 2014 , ID 480640, 11 pages, 2014.

3.         Lei Liu, Zhanshan Wang and Zhengwei Shen, Neural-Network-Based Adaptive Dynamic Surface Control for MIMO Systems with Unknown Hysteresis, 2014 IEEE Symposium Series on Computational Intelligence, December 9-12, Orlando, Florida, USA, 2014.  356-361.

4.         Liang Hongjing, Zhang Huaguang, Wang Zhanshan, Zhang Jilie, Output regulation for heterogeneous linear multi-agent systems based on distributed internal model compensator, Applied Mathematics and Computation, vol. 242, pp. 736-747, 2014.

5.         Hongjing Liang, Huaguang Zhang, Zhanshan Wang, Junyi Wang, Output regulation of state-coupled linear multi-agent systems with globally reachable topologies, Neurocomputing, Volume 123, pp. 337-343, 2014.

6.         Hongjing Liang, Yingchun Wang, Zhanshan Wang, Huaguang Zhang, Distributed control for second-order leader-following multi-agent systems with heterogeneous leader, 2014 International Joint Conference on Neural Networks (IJCNN),  pp. 1334-1338, July 6-11, 2014, Beijing, China.

7.         Liu, Wei; Zhang, Huaguang; Wang, Zhanshan,A novel truncated approximation based algorithm for state estimation of discrete-time Markov jump linear systems, Signal Processing, vol. 91, no. 4, pp. 702-712, 2011.

8.         Liu Wei, Zhang Huaguang, Wang Zhanshan, State Estimation for Discrete-Time Markov Jump Linear Systems Based on Orthogonal Projective Theorem, International Journal of Control Automation and Systems, vol. 10, no. 5, pp. 1049-1054, OCT 2012.

9.         Liu Wei, Zhang Huaguang, Fu Jie, Wang Zhanshan, A novel suboptimal algorithm for state estimation of Markov jump linear systems, Journal of Control Theory and Applications, 2011, 9(2): 148-154 .

10.     Zhanshan Wang, Zhengwei Shen, Chao Cai Kaili Jia, Adaptive Control of Wind Turbine Generator System Based on RBF-PID Neural Network, 2014 International Joint Conference on Neural Networks (IJCNN) July 6-11, 2014, Beijing, China, 538-543.

  

二、奖项成果

 

1、面向节能的复杂配电网监测控制与故障诊断关键技术研发及应用,2010年国家科技进步奖二等奖,排名第四

2、非线性系统的鲁棒自适应控制理论 及应用,2010年教育部自然科学奖一等奖,

排名第五,

3、复杂非线性系统的动态分析和智能控制理论及应用,2008年辽宁省自然科学奖一等奖,排序第三。

4、分布交互式的复杂配电自动化网络智能分析技术和监测控制系统,2007年中国电子学会电子信息科学技术奖一等奖,排序第四,

 

 

三、专利

  

1 中国科技发明专利,一种智能微网的源--荷自动控制系统及控制方法,

2 中国科技发明专利,一种有谐波抑制功能的分散式发电无功补偿装置及方法

 

3 德国科技发明专利,A distributed hybrid powered smart grid system and control method thereof, European Patent Office, Germany,

 

4 中国科技发明专利,一种用于谐波抑制和无功补偿的装置及方法,

 

5 中国科技发明专利,小型风光互补抽水蓄能并网发电系统及充放电控制方法

 

6中国科技发明专利,一种暂态电能质量检测装置和方法,

 

7中国科技发明专利,一种轻型高压直流输电系统交替潮流计算方法及装置

 

 

 

 

 
 
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