基于LMI的一类关联模糊大系统的稳定性分析及分散化控制器设计
|
摘要
传统控制理论难以解决复杂非线性系统分析、建模与控制问题，而模糊控制技术由于能够方便地利用专家经验及语言信息，甚至无需建立系统数学模型即可对系统进行控制，目前已逐渐成为复杂非线性系统分析与设计所采用的主要方法之一。但是由于模糊控制系统自身的非线性特性，使得其稳定性分析与性能设计缺乏有效的解析方法，很多设计过程是通过尝试的方法来完成的。因此，如何将传统控制理论中的解析设计方法与模糊系统理论相结合，产生一套完整的系统化的模糊控制理论，已成为模糊控制理论研究人员的一项迫切任务。
此外随着现代科技的迅速发展，实际控制系统变得越来越复杂，越来越大型化，所以近年来关于大系统分散控制理论的研究引起了学术界和工程界的广泛兴趣。本论文的主要目的是将模糊控制技术与大系统分散控制理论相结合，建立一套系统化的非线性关联模糊大系统稳定性分析与性能设计的有效方法。
首先，本文对关联模糊大系统的分散镇定问题进行了研究。稳定性与相应的镇定问题是模糊控制系统分析与设计的基本问题。本文所研究的关联模糊大系统由一系列T-S模糊子系统构成。本文采用分散化并行分布补偿(DPDC)模糊控制器实现非线性关联模糊大系统的控制，即对每个子T-S模糊系统均采用一个PDC控制器进行控制。基于李雅普诺夫稳定性理论及大系统分散控制理论，采用LMI方法导出了该类模糊大系统在采用DPDC模糊控制器时闭环渐近稳定的充分条件，并利用隶属函数的信息对该稳定性条件进行了改进，得出了保守性更小的稳定性条件。此外，考虑到实际系统的状态通常不能完全量测，本文研究了其分散状态观测器的设计方法。所设计的分散状态观测器与DPDC模糊控制器类似，本身也是一系列T-S模糊子系统，本论文给出了这些分散化状态观测器能渐近估计出原系统状态的LMI形式的充分条件。并证明了对于关联模糊大系统而言，线性系统中著名的控制器及观测器设计的分离原理也是成立的，这对于非线性关联模糊大系统控制器与观测器的分析与设计问题具有重要的意义。
其次，本论文研究了一类具有参数不确定性的连续时间及离散时间关联模糊大系统的分散鲁棒镇定问题。所考虑的参数不确定性以范数有界的形式出现在各个子模糊系统的系统矩阵、输入矩阵及输出矩阵中，本论文讨论了该类不确定性关联大系统DPDC控制器的设计问题。采用LMI方法给出了该类不确定性关联模糊大系统可分散鲁棒镇定的条件。同时通过利用隶属度函数的信息对该鲁棒镇定条件进行了改进，得到了保守性更小的LMI形式的鲁棒镇定条件。
第11页
西南交通大学博士研究生学位论文
此外，本文考虑了具有时滞关联项的模糊大系统的分散镇定问题。众所周知，
由于系统中信息传输和测量的不灵敏性，其关联项常常存在时滞现象，而时滞常
常是导致系统不稳定的因素。基于李雅普诺夫稳定性理论及大系统分散控制理论，
通过定义增广的状态变量，本文给出了LMI形式的连续及离散时滞模糊大系统的
时滞无关分散能镇定条件。
最后，本文采用LMI技术，研究了一类具有参数不确定性的连续时间及离散
时间关联模糊大系统的保性能控制问题，给出了其分散状态反馈保成本控制器的
设计方案，所设计的控制器不但能使系统闭环稳定，而且闭环系统的性能也得到
了一定的保证。
本文的研究结果提供了一套非线性关联模糊大系统控制器、观测器及性能分
析与设计的有效方法，为实际的复杂工业大系统的模糊控制提供一套现实可行的
方案，LMI方法的数值有效性保证了本文方法的切实可行性。
By utilizing expert experience and language information, analyzing, modeling and control of many industrial complex plants can be handled effectively by fuzzy control technology, which otherwise will be very hard by approaches of traditional control theory, if not impossible. In addition, these complex plants can be controlled easily even without exact mathematical models, so fuzzy control has become a popular topic for analysis and design of complex nonlinear systems. However, the nonlinear nature of fuzzy control technology sets an obstacle to development of analytic method for stability analysis and systematic performance design of fuzzy control systems, and many design procedures are performed by trial-and-error. So, how to combine the advantages of analytic methods of traditional control theory and fuzzy systems theory and develop an integrated and systematic fuzzy control theory has increasingly becoming an urgent task for researchers of fuzzy control theory.
On the other hand, with the rapid development of modern science and technology, the practical control system has become very huge and complex, so decentralized control theory of large-scale systems has attracted great attentions in both academic research and industrial applications. The main aim of this dissertation is to fuse the fuzzy logic control technology and decentralized control theory of large-scale system to develop a systematic design methodology that guaranteeing some basic requirements, such as stability and acceptable performance, for nonlinear interconnected fuzzy large-scale systems.
Firstly, decentralized stabilization problems for interconnected fuzzy large-scale systems are considered. Stability and stabilization are the most basic problems in analysis and design of fuzzy control systems. The interconnected fuzzy large-scale systems considered in this dissertation consists of some interconnected T-S fuzzy subsystems, Decentralized Parallel Distributed Compensation (DPDC) fuzzy controllers are designed for this fuzzy large-scale systems, namely each T-S fuzzy subsystems will be controlled only by one PDC fuzzy controllers. Based on Lyapunov stability theory and decentralized control theory of large-scale systems, sufficient conditions for asymptotic stability of the closed-loop fuzzy large-scale systems are derived via LMI technology, and by using information of membership functions these LMI-based
sufficient conditions are relaxed and less conservative stabilization conditions are obtained. Considering that not all of the states variables of the system can be detected, decentralized states observers are also designed to estimate the system states. Similar to DPDC fuzzy controllers, these decentralized states observer are T-S fuzzy systems themselves. And LMI-based sufficient conditions for these states observers to estimate the true states of the fuzzy large-scale system asymptotically are developed. Furthermore, the well-known separation principle for designs of controllers and observers in linear system theory are proved to be hold for fuzzy large-scale systems considered in this dissertation, which is important for analysis and design problems of controllers and observers of interconnected fuzzy large-scale systems.
Next, robust decentralized stabilization problems for a class of interconnected fuzzy large-scale systems with parametric uncertainties are considered in this dissertation, both for continuous-time and discrete-time case. The norm-bounded parametric uncertainties entered into system matrices, input matrices and interconnections in all of the T-S fuzzy subsystems. DPDC controllers are designed for the uncertain interconnected fuzzy large-scale systems and LMI-based decentralized robust stabilizable conditions for uncertain interconnected fuzzy large-scale systems are developed. By utilizing information of membership functions these robust stabilizable conditions are also relaxed and less conservative LMI-based conditions are obtained.
In addition, decentralized stabilization problems for fuzzy large-scale
此外随着现代科技的迅速发展，实际控制系统变得越来越复杂，越来越大型化，所以近年来关于大系统分散控制理论的研究引起了学术界和工程界的广泛兴趣。本论文的主要目的是将模糊控制技术与大系统分散控制理论相结合，建立一套系统化的非线性关联模糊大系统稳定性分析与性能设计的有效方法。
首先，本文对关联模糊大系统的分散镇定问题进行了研究。稳定性与相应的镇定问题是模糊控制系统分析与设计的基本问题。本文所研究的关联模糊大系统由一系列T-S模糊子系统构成。本文采用分散化并行分布补偿(DPDC)模糊控制器实现非线性关联模糊大系统的控制，即对每个子T-S模糊系统均采用一个PDC控制器进行控制。基于李雅普诺夫稳定性理论及大系统分散控制理论，采用LMI方法导出了该类模糊大系统在采用DPDC模糊控制器时闭环渐近稳定的充分条件，并利用隶属函数的信息对该稳定性条件进行了改进，得出了保守性更小的稳定性条件。此外，考虑到实际系统的状态通常不能完全量测，本文研究了其分散状态观测器的设计方法。所设计的分散状态观测器与DPDC模糊控制器类似，本身也是一系列T-S模糊子系统，本论文给出了这些分散化状态观测器能渐近估计出原系统状态的LMI形式的充分条件。并证明了对于关联模糊大系统而言，线性系统中著名的控制器及观测器设计的分离原理也是成立的，这对于非线性关联模糊大系统控制器与观测器的分析与设计问题具有重要的意义。
其次，本论文研究了一类具有参数不确定性的连续时间及离散时间关联模糊大系统的分散鲁棒镇定问题。所考虑的参数不确定性以范数有界的形式出现在各个子模糊系统的系统矩阵、输入矩阵及输出矩阵中，本论文讨论了该类不确定性关联大系统DPDC控制器的设计问题。采用LMI方法给出了该类不确定性关联模糊大系统可分散鲁棒镇定的条件。同时通过利用隶属度函数的信息对该鲁棒镇定条件进行了改进，得到了保守性更小的LMI形式的鲁棒镇定条件。
第11页
西南交通大学博士研究生学位论文
此外，本文考虑了具有时滞关联项的模糊大系统的分散镇定问题。众所周知，
由于系统中信息传输和测量的不灵敏性，其关联项常常存在时滞现象，而时滞常
常是导致系统不稳定的因素。基于李雅普诺夫稳定性理论及大系统分散控制理论，
通过定义增广的状态变量，本文给出了LMI形式的连续及离散时滞模糊大系统的
时滞无关分散能镇定条件。
最后，本文采用LMI技术，研究了一类具有参数不确定性的连续时间及离散
时间关联模糊大系统的保性能控制问题，给出了其分散状态反馈保成本控制器的
设计方案，所设计的控制器不但能使系统闭环稳定，而且闭环系统的性能也得到
了一定的保证。
本文的研究结果提供了一套非线性关联模糊大系统控制器、观测器及性能分
析与设计的有效方法，为实际的复杂工业大系统的模糊控制提供一套现实可行的
方案，LMI方法的数值有效性保证了本文方法的切实可行性。
By utilizing expert experience and language information, analyzing, modeling and control of many industrial complex plants can be handled effectively by fuzzy control technology, which otherwise will be very hard by approaches of traditional control theory, if not impossible. In addition, these complex plants can be controlled easily even without exact mathematical models, so fuzzy control has become a popular topic for analysis and design of complex nonlinear systems. However, the nonlinear nature of fuzzy control technology sets an obstacle to development of analytic method for stability analysis and systematic performance design of fuzzy control systems, and many design procedures are performed by trial-and-error. So, how to combine the advantages of analytic methods of traditional control theory and fuzzy systems theory and develop an integrated and systematic fuzzy control theory has increasingly becoming an urgent task for researchers of fuzzy control theory.
On the other hand, with the rapid development of modern science and technology, the practical control system has become very huge and complex, so decentralized control theory of large-scale systems has attracted great attentions in both academic research and industrial applications. The main aim of this dissertation is to fuse the fuzzy logic control technology and decentralized control theory of large-scale system to develop a systematic design methodology that guaranteeing some basic requirements, such as stability and acceptable performance, for nonlinear interconnected fuzzy large-scale systems.
Firstly, decentralized stabilization problems for interconnected fuzzy large-scale systems are considered. Stability and stabilization are the most basic problems in analysis and design of fuzzy control systems. The interconnected fuzzy large-scale systems considered in this dissertation consists of some interconnected T-S fuzzy subsystems, Decentralized Parallel Distributed Compensation (DPDC) fuzzy controllers are designed for this fuzzy large-scale systems, namely each T-S fuzzy subsystems will be controlled only by one PDC fuzzy controllers. Based on Lyapunov stability theory and decentralized control theory of large-scale systems, sufficient conditions for asymptotic stability of the closed-loop fuzzy large-scale systems are derived via LMI technology, and by using information of membership functions these LMI-based
sufficient conditions are relaxed and less conservative stabilization conditions are obtained. Considering that not all of the states variables of the system can be detected, decentralized states observers are also designed to estimate the system states. Similar to DPDC fuzzy controllers, these decentralized states observer are T-S fuzzy systems themselves. And LMI-based sufficient conditions for these states observers to estimate the true states of the fuzzy large-scale system asymptotically are developed. Furthermore, the well-known separation principle for designs of controllers and observers in linear system theory are proved to be hold for fuzzy large-scale systems considered in this dissertation, which is important for analysis and design problems of controllers and observers of interconnected fuzzy large-scale systems.
Next, robust decentralized stabilization problems for a class of interconnected fuzzy large-scale systems with parametric uncertainties are considered in this dissertation, both for continuous-time and discrete-time case. The norm-bounded parametric uncertainties entered into system matrices, input matrices and interconnections in all of the T-S fuzzy subsystems. DPDC controllers are designed for the uncertain interconnected fuzzy large-scale systems and LMI-based decentralized robust stabilizable conditions for uncertain interconnected fuzzy large-scale systems are developed. By utilizing information of membership functions these robust stabilizable conditions are also relaxed and less conservative LMI-based conditions are obtained.
In addition, decentralized stabilization problems for fuzzy large-scale
引文
1 L.A.Zadeh. Fuzzy Sets, Inform. And Control, 1965, 8:338-353
2 L.A.Zadeh. Fuzzy Sets and Fuzzy Systems, Proc. Syrup. On Systems Theory, Polytech. Inst. Brooklyn: 29-37
3 L.A.Zadeh. Outline of a new approach to the analysis of complex systems and decision processes, IEEE Trans. Systems Man, and Cybernetics, 1973, 3(1): 28～44
4 E.H. Mamdani, S. Assilian, Applications of fuzzy algorithms for control of simple dynamic plant, Proc. Inst. Elec. Eng, 1974(121): 1585-1588
5 W.M. Kickert, E. H. Mamdani, Analysis of a fuzzy logic controller. Fuzzy Sets and Systems, 1978(1):29-44
6 R.M.Tong, Analysis and control of fuzzy systems using finite discrete relations, Int. J. Control, 1978(27):431-440
7 R.M.Tong, Analysis and control of fuzzy systems using the relation matrix, Int. J. Control, 1978(271):679-686
8 M. Braae, D.A. Rutherford, Selection of parameters for a fuzzy logic controller, Fuzzy Sets and Systems,. 1979(2):185-199
9 邓聚龙，Fuzzy 控制的稳定性问题，模糊数学，1983(3)：71-84
10 J.B. Kiszka, M.M. Gupta, P.N. Nikiforuk, Energetic stability of fuzzy dynamic systems, IEEE Trans. Systems Man, and Cybernetics, 1985:783-792
11 T. Takagi, M. Sugeno, Fuzzy identification of systems and its application to modeling and control. IEEE Trans. Systems Man, and Cybernetics, 1985, 15(1): 116-132
12 K. Tanaka, M. Sugeno. Stability analysis and design of fuzzy control systems. Fuzzy Sets and Systems, 1992,45(2): 135-156
13 S.G. Cao, N.W. Rees, G. Feng, Quadratic stability analysis and design of continuous-time fuzzy control systems. Int., J. Systems Science, 1996,27(2):193-203
14 S.G. Cao, N.W. Rees, G. Feng, Analysis and design of a class of continuous time fuzzy control system. Int., J. Control, 1996,64(6):1069-1087
15 S.G. Cao, N.W. Rees, G. Feng. Analysis and design for a class of complex control systems-PartⅡ: fuzzy controller design. Automatica, 1997, 33(6): 1029-1039
16 S.G. Cao, N.W. Rees, G. Feng, Lyapunov-like stability theorems for discrete-time fuzzy control systems. Int., J. Systems Science, 1997,28(3): 297-308
17 H. O. Wang, K. Tanaka, M.F. Griffin, An approach to fuzzy control of nonlinear systems: stability and design issues, IEEE Trans. Fuzzy Syst., 1996,4(1): 14-23
18 H.O. Wang, K. Tanaka, M.F. Griffin, Parallel distributed compensation of nonlinear systems by T-S fuzzy model, Proc. Fuzzy-IEEE/IFES'95, 1995:531-538
19 K. Tanaka, T. lkeda, and H.O. Wang, Fuzzy control systems design via LMI, in Proc. The Amer. Contr. Conf., New Mexico, June, 1997:2873-2877
20 K. Tanaka, T. Ikeda, H.O. Wang, Fuzzy regulators and fuzzy observers: relaxed stability
conditions and LMI-based designs, IEEE Trans., Fuzzy Syst., 1998, 6(2): 250-265
21 E. Kim. H. Lee, New approaches to relaxed quadratic stability condition of fuzzy control systems, IEEE Trans. Fuzzy Syst., 2000, 8(5): 523-534
22 H. J. Lee, J.B. Park, G. Chen, Robust fuzzy control of nonlinear systems with parametric uncertainties, IEEE Trans., Fuzzy Syst., 2001, 9(2): 369-379
23 E. Kim, D. Kim, Stability analysis and synthesis for an affine fuzzy system via LMI and ILMI:Discrete Case. IEEE Trans. Syst., Man, Cyber, 2001, 31(1):132-140
24 C.S. Tseng, B.S. Chen, H∞ decentralized fuzzy model reference tracking control design for nonlinear interconnected systems, IEEE Trans. Fuzzy Systems, 2001, 9(6):795-809
25 Y. Wang, Q.L. Zhang, Robust fuzzy decentralized control for nonlinear interconnected descriptor systems, 2001. Proc. The 10th IEEE International Conference on Fuzzy Systems, 2001:1392-1395
26 T. Taniguchi, K. Tanaka, K. Yamafuji, H. O. Wang, Fuzzy descriptor systems: Stability analysis and design via LMIs, Proc. Amer. Contr. Conf., San Diego, California, June, 1999:1827-1831
27 R. Palm, D. Driankov, Stability of fuzzy gain schedulers: Sliding-mode based analysis, Proc. 6th IEEE Int Conf Fuzzy systems, Spain, 1997,1:177-183
28 T.P. Zhang, C.B. Feng, Fuzzy variable structure control via output feedback, Int., J. Systems Science, 1997,28(3):309-319
29 S.S. Farinwata, G. Vachtsevanos, Stability analysis of the fuzzy logic controller designed by the phase portrait assignment algorithm, Proc. the 2nd IEEE Int. Conf. Fuzzy Syst. San Francisco, 1993:1377-1382
30 H.A. Malki, H. Li, G.R. Chen, New design and stability analysis of fuzzy proportional derivative control systems, IEEE Trans. Fuzzy Syst., 1994, 2(4): 245-254
31 D. Misir,H.A. Malki, G.R. Chen, Design and analysis of a fuzzy proportional-integrative-derivative controller, Fuzzy Sets and Systems, 1996, 79(3):297-314
32 路兆梅，柏广昌，冷增祥，模糊控制系统的相平面分析，电气自动化，1996，18(6)：11-13
33 G. Abdelnour, J. Y. Cheung, C. Chang, Application of describing functions in the transient response analysis of a three-term fuzzy control. IEEE Trans. Systems Man, and Cybernetics, 1993, 23(2): 603-606
34 K.S. Ray, D.D. Majumder, Application of circle criteria for stability analysis of linear SISO and MIMO systems associated with fuzzy logic controller. IEEE Trans. Systems Man, and Cybernetics, 1984, 14(2): 345-349
35 J.X. Xu, C. Liu, C.C. Hang, Designing a stable fuzzy PI control system using:extended circle criteria. Int. J. Intelligent Control and systems, 1996, 1(3): 355-366
36 E. Furutani, M. Saeki, M. Araki, Shifted Popov criteria on and stability analysis of fuzzy control systems, Proc. 31st Conf. Decision and Control, Tucson, Arizona, 1992:2790-2795
37 S.Y. Yi, M.J. Chung, A robust fuzzy logic controller for robot manipulators with uncertainties, IEEE Trans. Systems Man, and Cybernetics, 1997, 27(4): 706-713
38 Y. R. Hwang, M.Tomizuka, Fuzzy smoothing algorithms for variable structure systems, IEEE
Tmas. Fuzzy Systems, 1994, 2(4): 277-284
39 K. Tanaka, A robust stabilization fuzzy control systems and its application to backing up control of a truck-trailer. IEEE Trans. Fuzzy Syst., 1994, 2(2):119-134
40 K. Tanaka, T. Ikeda, H.O. Wang, Robust stabilization of a class of uncertain nonlinear systems via fuzzy control: Quadratic stabilizability, H~∞ control theory, and linear matrix inequalities, IEEE Trans. Fuzzy Systems, 1996, 4(1): 1-13
41 张友刚，刘志刚，肖建，基于LMI的仿射型模糊控制系统的稳定性研究，《控制与决策》，2003年第6期
42 Y.Y. Cao, EM. Frank, Analysis and synthesis of nonlinear time-delay systems via fuzzy control approach, IEEE Trans. Fuzzy Systems, 2000, 8(2): 200-211
43 K.R. Lee, J.H. Kim, E.T. Jeung, H.B. Park, Output feedback robust H~∞ control of uncertain fuzzy dynamic systems with time-varying delay, IEEE Trans. Fuzzy Systems, 2000, 8(6): 657-664
44 Y. Zhang, A.H. Pheng, Stability of fuzzy control systems with bounded uncertain delays, IEEE Trans. Aut. Control, 2002, 10(1): 92-97
45 C.W. Park, J.H. Kim, S. Kim, M. Park, LMI-based quadratic stability analysis for hierarchical fuzzy systems, IEE Proc., Control Theory Appl., 2001, 148(5): 340-349
46 S. Boyd. L. Ghaoui, E. Feron, V. Balakrishnan, Linear matrix inequalities in systems and control theory. Philadelphia, PA: SIAM 1994
47 丁永生，应浩，任立红，邵世煌，解析模糊控制理论：模糊控制系统的结构和稳定性分析，控制与决策，2000，15(2)：129-135
48 Y. Nesterov, A. Nemirovskii, Interior-point polynomial methods in convex programming. Philadelphia, PA: SIAM 1994
49 P. Gahinet, A. Nemirovski, A.J. Laub, M. Chilali, LMI control toolbox. Natick, MA: Mathworks, 1995
50 H.D. Tuan, P. Apkarian, T. Narikiyo, and Y. Yamamoto, Parameterized linear matrix inequality techniques in fuzzy control system design, IEEE Trans., Fuzzy Syst., 2001, 9(2): 324-332
51 W. Wu, S. Xu, D. Yue, F.Liu, Fuzzy controller and observer design for nonlinear system-LMI method, Proc. The 4th World Congress on Intelligent Control and Automation, Shanghai,P.R.China, 2002:1920-1924
52 Y. Yang, Y. Dong, X. Guo, Guaranteed-cost design based on T-S fuzzy model, Proc. The 4th World Congress on Intelligent Control and Automation, Shanghai, P.R.China, 2002:1862-1866
53 L. Udawatta, K. Watanabe, K. Kiguchi, K. lzumi, Fuzzy-chaos hybrid controller for controlling of nonlinear systems, IEEE Trans. Fuzzy Systems, 2002, 10(3): 401-411
54 M.Jamshidi, Large-scale systems: modeling and control, North-Holland, 1983
55 M.S. Mahmoud, M.G. Singh, Large-scale systems modeling, Pergamon Press, 1981
56 陈禹六，大系统理论及其应用，北京，清华大学出版社，1988
57 M.D. Mesarovic, D. Macko, Y. Takahara, Theory of hierarchical multilevel systems, New York,Academic, 1970
58 S.A. Arafeh, Hierarchical control of power distribution systems, IEEE Trans. Aut. Control, 1978,
23(2): 333-343
59 M.G. Singh, Decentralized control, North-Holland, Amsterdam, 1981
60 S.H. Wang, E.J. Davison, On the stabilization of decentralized control systems, IEEE Trans. Aut. Control, 1973, 18(5): 473-478
61 M. Araki, Applications of M-matrices to the stability problems of composite systems, J. Math. Anal. Applic. 1975, 52:309-321
62 M. Araki, Input-output stability of composite feedback systems, IEEE Trans. Aut. Control, 1976, 21(2):254-259
63 M. Araki, Stability of large-scale nonlinear systems-quadratic order theory of composite system method using M-matrices, IEEE Trans. Aut. Control, 1978, 23(2):129-142
64 F.M. Callier, W.S. Chan, C.A. Desoer, Input-output stability of interconnected systems using decomposition: an improved formulation, IEEE Trans. Aut. Control, 1978, 23(2):150-163
65 E.J. Davison, Decentralized robust control of unknown systems using tuning regulators, IEEE Trans. Aut. Control, 1978, AC23:276-289
66 N. Sandell, P. Varaiya, M. Athans, M.G. Safonov, Survey of decentralized control methods for large scale systems, IEEE Trans. Aut. Control, 1978, AC23:108-128
67 G. Cohen, Optimization by decomposition and coordination: a unified approach, IEEE Trans. Aut. Control, 1978, 23(2): 222-232
68 J.C. Geromel, J. Bernussou, Optimal decentralized control of dynamic systems, Automatica, 1982, 18(5): 545-557
69 E.J. Davison, U. Ozguner, Characterization of decentralized fixed modes for interconnected systems, Automatica, 1983, 19(2): 169-182
70 A. Saberi, H. Khalil, Decentralized stabilization of interconnected systems using output feedback, Int. J. Control, 1985, 41:1461-1475
71 D.Z. Zheng, Decentralized output feedback stabilization of a class of nonlinear interconnected systems, IEEE Trans. Aut. Control, 1989, 34(12): 1297-1300
72 M.K. Sundareshan, R.M. Elbana, Qualitative analysis and decentralized controller synthesis for a class of large scale systems with symmetrically interconnected subsystems, Automatica, 1991,27:383-388
73 L. Shi, S.K. Singh, Decentralized control for interconnected uncertain systems: extensions to higher uncertainties, Int. J. Control, 1993, 57:1453-1468
74 T.N. Lee, U.L. Radovic, General decentralized stabilization of large-scale linear continuous and discrete time-delay systems, Int. J. Control, 1987, 46(6): 2127-2140
75 B.S. Chen, W.J. Wang, Robust stabilization of nonlinearly perturbed large-scale systems by decentralized observer-controller compensators, Automatica, 1990, 26(6): 1035-1041
76 X.G. Yan, G.Z. Dai, Decentralized output feedback robust control for nonlinear large-scale systems, Automatica, 1998, 34(11): 1469-1472
77 X.G. Yan, J.J. Wang, X.Y. Lu, S.Y. Zhang, Decentralized output feedback robust stabilization for a class of nonlinear interconnected systems with similarity, IEEE Trans. Aut. Control, 1998, 43(2): 294-299
78 温香彩，刘永清，不确定关联大系统的分散变结构控制设计，控制理论与应用，1995，12(4)：429-436
79 桂卫华，陈宁，吴敏，不确定关联大系统鲁棒分散可靠H_∞控制，控制理论与应用，2002，19(6)：923-926
80 关新平，不确定性离散时滞大系统的分散镇定控制，系统工程与电子技术，2002，24(6)：66-69
81 刘红霞，胥布工，朱学峰，一类不确定关联时滞大系统的分散H_∞控制器设计-LMI方法，控制理论与应用，2001，18(6)：954-960
82 F.N. Bailey, The application of Lyapunov's second method to interconnected system, SIAM J.Control, 1966, 3:443-462
83 D.D. Siljak, On stability of large-scale systems under structural perturbations, IEEE Trans. Systems Man, and Cybernetics, 1973, 3:415-417
84 D.D. Siljak, Large-scale dynamic systems—stability and structure, North-Holland, New York
85 E.L. Lasley, A.N. Michel, Input-output stability of interconnected systems, IEEE Trans. Aut. Control, 1976, 21(1): 84-89
86 D.Y. Xu, BIBO stabilization of large-scale systems, Control Theory and Applications, 1995,12(6): 758-763
87 V. Lakshmikantham, S. Leela, Differential and integral inequalities, New York: Academic, 1969
88 D.D. Siljak, Competitive economic systems: stability, decomposition and aggregation, IEEE Trans. Aut. Control, 1976, 21(2): 149-160
89 M. Araki, B. Kondo, Stability and transient behavior of composite nonlinear systems, IEEE Trans. Aut. Control, 17(4): 537-541
90 A.N. Michel, Stability analysis of interconnected systems, SIAM J. Contr., 1974, Vol. 12
91 F.H. Hsiao, J.D. Hwang, L.G. Shiau, Decentralized stabilization of fuzzy large-scale systems, In Proc. IEEE Conf. Decision Contr., Sydney, Australia, 2000:3447-3452
92 F.H. Hsiao, J.D. Hwang, Stability analysis of fuzzy large-scale systems. IEEE Trans. Syst., Man, and Cybern. 2001, 32(1): 122-126
93 W.J. Wang, L.G. Mao, Stabilization and estimation for perturbed discrete time-delay large-scale systems, IEEE Trans. Aut. Control, 1997, 42(9):1277-1282
94 L. Yu, U. Holmberg, D. Bonvin, Decentralized robust stabilization of a class of interconnected uncertain delay systems, Control-Theory and Advanced Technology, 1995, 10(4): 1475-1483
95 I.H. Suh, Bien Z, A note on the stability of large-scale systems with delays, IEEE Trans. Aut. Cotrol, 1982, 27(1): 256-258
96 俞立，一类线性离散时滞大系统的分散镇定，控制理论与应用，2000，17(1)：125-127，132
97 S. Xie, L. Xie, Y. Wang, G. Guo, Decentralised control of multi-machine power systems with guaranteed performance, IEE Proc. Control Theory Appl., 2000, 47(3): 355-365
98 A.N. Michel, R.K. Miller, Qualitative analysis of large scale dynamical systems, Academic Press, London, 1977
99 张友刚，向静，肖建，基于LMI的参数不确定性关联模糊大系统的分散鲁棒镇定，《控制
理论与应用》，已录用
100 张友刚，向静，肖建，离散模糊大系统的分散化PDC控制器设计：LMI方法，《控制与决策》，已录用。
101 关新平，陈彩莲，刘奕昌，段广仁，不确定时滞系统的模糊保成本控制，控制与决策，2002，17(2)：178-182
102 G. Zames, On the input-output stability of nonlinear time-varying feedback systems, Partⅰand part ⅱ, IEEE Trans. Aut. Control, 1966, 11(2) : 228-238,465-477
103 D.C. Youla, L.J. Castriota, H.J. Carlin, Bounded real scattering matrices and the foundation of linear passive network theory, IRE Tr. CT-4(1), 1959:102-124
104 M. Vidyasagar, Nonlinear systems analysis (2nd Edition), Prentice Hall, London, 1993
105 B. Barmish, H.I. Kang, A survey of extreme point results for robustness of control systems, Automatica, 1993,29(1):15-35
106 J. Ezzine, Robust stability of bounds for sample data systems, Int. J. Syst. Sci, 1995, 26(10): 1951-1966
107 F.M. Al-Sunni, Robust control of sample data systems, IEE Proc. Control Theory Applications, 1998, 145(2):236-240
108 冯纯伯，鲁棒控制系统分析与设计，东南大学出版社，1996
109 M. Malek-Zavarei, M. Jamshidi, Time-delay systems: analysis, optimization and applications, North-Holland, Amsterdam, 1987
110 P. Jiang, H. Su, J. Chu, Optimal guaranteed cost control for a class of linear uncertain time-delay systems, Proc. the 3th World Congress on Intelligent Control and Automation, Hefei, P.R. China, 2000:3354-3358
111 S. Chang, T. Peng, Adaptive guaranteed cost control of systems with uncertain parameters, IEEE Trans. Aut. Control, 1972, 17(4): 356-361
112 廖晓昕，动力系统的稳定性理论和应用，国防工业出版社，2000
113 廖晓昕，稳定性的数学理论和应用，武汉，华中师范大学出版社，1998
114 A.M. Lyapunov, Problème général de la stabilité du movement, V.17, Annals of Mathematics Studies, Princeton University Press, Princeton, 1947
115 L.X. Wang, J.M. Mendel, Fuzzy basis functions, universal approximation, and orthogonal least squares learning, IEEE Trans. Neural Networks, 1992, 3(5): 807-814
116 X.J. Zeng, M.G. Singh, Approximation theory of fuzzy systems-SISO case, IEEE Trans. Fuzzy Systems, 1994, 2(2): 162-176
117 X.J. Zeng, M.G. Sing, h, Approximation theory of fuzzy systems-MIMO case, IEEE Trans. Fuzzy Systems, 1995, 3(2):219-235 .
118 X.J. Zeng, M.G. Singh, Approximation accuracy analysis of fuzzy systems as function approximators, IEEE Trans. Fuzzy Systems, 1996, 4(1): 44-63
119 E.N. Lorenz, Deterministic non-periodic flow, J. Atmos. Sci., 1963(20): 130-141
120 K. Tanaka, Advanced fuzzy control, Kyoritsu Pub. 1994, in Japanese
121 A.I. Lur'e, V.N. Postnikov, On the theory of stability of control systems. Applied mathematics and mechanics,8(3), in Russian
122 V.A.Yakubovich, Frequency conditions for the existence of absolutely stable periodic and almost periodic limiting regimes of control systems with many non-stationary elements. In IFAC World Congress, London, 1966
123 V.A.Yakubovich, The method of matrix inequalities in the stability theory of nonlinear control systems, Ⅰ, Ⅱ, Ⅲ, Automation and Remote Control, 1967, 25-26(4): 905-917,577-592,753-763
124 V.M.Popov, Absolute stability of nonlinear systems of automatic control, Automation and Remote Control, 1962, 22:857-875
125 V.M.Popov, One problem in the theory of absolute stability of controlled systems, Automation and Remote Control, 1964, 25(9): 1129-1134
126 R.E.Kalman, Lyapunov functions for the problems of Lur's in automatic control, Proc. Nat. Acad. Sci, USA, 1963, 49:201-205
127 J.C.Willems, Least squares stationary optimal control and the algebraic Riccati equation, IEEE Trans. Aut. Control, 1971, 16(6):621-634
128 V.J.S. Karmarkar, D.D. Siljak, Maximization of absolute stability regions by mathematical programming methods, Regelungstechnik, 1975, 2:59-61
129 Y. Nesterov and A. Nemirovsky, A general approach to polynomial-time algorithms design for convex programming, Technical report, Centr. Econ. & Math. Inst., USSR Acad. Sci., Moscow, USSR, 1988
130 J. Yoneyama, M. Nishikawa, H. Katayama, A. Ichikawa, Output stabilization of Takagi-Sugeno fuzzy systems, Fuzzy Sets and Systems, 2000(111): 253-266
131 M.G. Safonov, Stability and robustness of multivariable feedback systems, MIT Press, Cambridge, MA, 1980
132 J. Doyle, K. Glover, P. Khargonekar, B. Francis, State space solutions to standard H~2 and H~∞ control problems, IEEE Trans. Aut. Control, 1989, 24(8): 731-747
133 J. Doyle, Synthesis of robust controllers and filters with structured plant uncertainty, in Proc. IEEE Conf. Decision and Control, New York, December, 1983
134 D.C. McFarlane, K. Glover, Robust controller design using normalized coprime Factor Plant. Descriptions. Berlin: Springer Verlag, 1990
135 Doyle J C, Francis B A and Tannenbaum A R. Feedback control theory.New York: Macmillan, 1992
136 J. Hale, S. Lunel, Introduction to functional differential equations, New York: Springer-Verlag,1993
137 I.R. Petersen, D.C. Mcfarlane, Optimal guaranteed cost control and filtering for uncertain linear systems, IEEE Trans. Aut. Control, 1994, 39(9):1971-1977
138 J. Zhao, R. Gorez, V. Wertz, Synthesis of fuzzy control systems with desired performances, Proc. The 1996 Int. Symp. Intelligent Control, Dearborn, MI, 1996:115-120
139 俞立，不确定离散系统的最优保性能控制，控制理论与应用，1999，16(5)：639-642
140 关新平，张群亮，一类广义系统的弹性保成本控制器设计，Proc. the 4th World Congress on Intelligent Control and Automation, Shanghai, ER. China, 2002:160-164
141 T. Kaileth, Linear Systems, Englewood Cliffs, N.J.: Prentice Hall, 1980
2 L.A.Zadeh. Fuzzy Sets and Fuzzy Systems, Proc. Syrup. On Systems Theory, Polytech. Inst. Brooklyn: 29-37
3 L.A.Zadeh. Outline of a new approach to the analysis of complex systems and decision processes, IEEE Trans. Systems Man, and Cybernetics, 1973, 3(1): 28～44
4 E.H. Mamdani, S. Assilian, Applications of fuzzy algorithms for control of simple dynamic plant, Proc. Inst. Elec. Eng, 1974(121): 1585-1588
5 W.M. Kickert, E. H. Mamdani, Analysis of a fuzzy logic controller. Fuzzy Sets and Systems, 1978(1):29-44
6 R.M.Tong, Analysis and control of fuzzy systems using finite discrete relations, Int. J. Control, 1978(27):431-440
7 R.M.Tong, Analysis and control of fuzzy systems using the relation matrix, Int. J. Control, 1978(271):679-686
8 M. Braae, D.A. Rutherford, Selection of parameters for a fuzzy logic controller, Fuzzy Sets and Systems,. 1979(2):185-199
9 邓聚龙，Fuzzy 控制的稳定性问题，模糊数学，1983(3)：71-84
10 J.B. Kiszka, M.M. Gupta, P.N. Nikiforuk, Energetic stability of fuzzy dynamic systems, IEEE Trans. Systems Man, and Cybernetics, 1985:783-792
11 T. Takagi, M. Sugeno, Fuzzy identification of systems and its application to modeling and control. IEEE Trans. Systems Man, and Cybernetics, 1985, 15(1): 116-132
12 K. Tanaka, M. Sugeno. Stability analysis and design of fuzzy control systems. Fuzzy Sets and Systems, 1992,45(2): 135-156
13 S.G. Cao, N.W. Rees, G. Feng, Quadratic stability analysis and design of continuous-time fuzzy control systems. Int., J. Systems Science, 1996,27(2):193-203
14 S.G. Cao, N.W. Rees, G. Feng, Analysis and design of a class of continuous time fuzzy control system. Int., J. Control, 1996,64(6):1069-1087
15 S.G. Cao, N.W. Rees, G. Feng. Analysis and design for a class of complex control systems-PartⅡ: fuzzy controller design. Automatica, 1997, 33(6): 1029-1039
16 S.G. Cao, N.W. Rees, G. Feng, Lyapunov-like stability theorems for discrete-time fuzzy control systems. Int., J. Systems Science, 1997,28(3): 297-308
17 H. O. Wang, K. Tanaka, M.F. Griffin, An approach to fuzzy control of nonlinear systems: stability and design issues, IEEE Trans. Fuzzy Syst., 1996,4(1): 14-23
18 H.O. Wang, K. Tanaka, M.F. Griffin, Parallel distributed compensation of nonlinear systems by T-S fuzzy model, Proc. Fuzzy-IEEE/IFES'95, 1995:531-538
19 K. Tanaka, T. lkeda, and H.O. Wang, Fuzzy control systems design via LMI, in Proc. The Amer. Contr. Conf., New Mexico, June, 1997:2873-2877
20 K. Tanaka, T. Ikeda, H.O. Wang, Fuzzy regulators and fuzzy observers: relaxed stability
conditions and LMI-based designs, IEEE Trans., Fuzzy Syst., 1998, 6(2): 250-265
21 E. Kim. H. Lee, New approaches to relaxed quadratic stability condition of fuzzy control systems, IEEE Trans. Fuzzy Syst., 2000, 8(5): 523-534
22 H. J. Lee, J.B. Park, G. Chen, Robust fuzzy control of nonlinear systems with parametric uncertainties, IEEE Trans., Fuzzy Syst., 2001, 9(2): 369-379
23 E. Kim, D. Kim, Stability analysis and synthesis for an affine fuzzy system via LMI and ILMI:Discrete Case. IEEE Trans. Syst., Man, Cyber, 2001, 31(1):132-140
24 C.S. Tseng, B.S. Chen, H∞ decentralized fuzzy model reference tracking control design for nonlinear interconnected systems, IEEE Trans. Fuzzy Systems, 2001, 9(6):795-809
25 Y. Wang, Q.L. Zhang, Robust fuzzy decentralized control for nonlinear interconnected descriptor systems, 2001. Proc. The 10th IEEE International Conference on Fuzzy Systems, 2001:1392-1395
26 T. Taniguchi, K. Tanaka, K. Yamafuji, H. O. Wang, Fuzzy descriptor systems: Stability analysis and design via LMIs, Proc. Amer. Contr. Conf., San Diego, California, June, 1999:1827-1831
27 R. Palm, D. Driankov, Stability of fuzzy gain schedulers: Sliding-mode based analysis, Proc. 6th IEEE Int Conf Fuzzy systems, Spain, 1997,1:177-183
28 T.P. Zhang, C.B. Feng, Fuzzy variable structure control via output feedback, Int., J. Systems Science, 1997,28(3):309-319
29 S.S. Farinwata, G. Vachtsevanos, Stability analysis of the fuzzy logic controller designed by the phase portrait assignment algorithm, Proc. the 2nd IEEE Int. Conf. Fuzzy Syst. San Francisco, 1993:1377-1382
30 H.A. Malki, H. Li, G.R. Chen, New design and stability analysis of fuzzy proportional derivative control systems, IEEE Trans. Fuzzy Syst., 1994, 2(4): 245-254
31 D. Misir,H.A. Malki, G.R. Chen, Design and analysis of a fuzzy proportional-integrative-derivative controller, Fuzzy Sets and Systems, 1996, 79(3):297-314
32 路兆梅，柏广昌，冷增祥，模糊控制系统的相平面分析，电气自动化，1996，18(6)：11-13
33 G. Abdelnour, J. Y. Cheung, C. Chang, Application of describing functions in the transient response analysis of a three-term fuzzy control. IEEE Trans. Systems Man, and Cybernetics, 1993, 23(2): 603-606
34 K.S. Ray, D.D. Majumder, Application of circle criteria for stability analysis of linear SISO and MIMO systems associated with fuzzy logic controller. IEEE Trans. Systems Man, and Cybernetics, 1984, 14(2): 345-349
35 J.X. Xu, C. Liu, C.C. Hang, Designing a stable fuzzy PI control system using:extended circle criteria. Int. J. Intelligent Control and systems, 1996, 1(3): 355-366
36 E. Furutani, M. Saeki, M. Araki, Shifted Popov criteria on and stability analysis of fuzzy control systems, Proc. 31st Conf. Decision and Control, Tucson, Arizona, 1992:2790-2795
37 S.Y. Yi, M.J. Chung, A robust fuzzy logic controller for robot manipulators with uncertainties, IEEE Trans. Systems Man, and Cybernetics, 1997, 27(4): 706-713
38 Y. R. Hwang, M.Tomizuka, Fuzzy smoothing algorithms for variable structure systems, IEEE
Tmas. Fuzzy Systems, 1994, 2(4): 277-284
39 K. Tanaka, A robust stabilization fuzzy control systems and its application to backing up control of a truck-trailer. IEEE Trans. Fuzzy Syst., 1994, 2(2):119-134
40 K. Tanaka, T. Ikeda, H.O. Wang, Robust stabilization of a class of uncertain nonlinear systems via fuzzy control: Quadratic stabilizability, H~∞ control theory, and linear matrix inequalities, IEEE Trans. Fuzzy Systems, 1996, 4(1): 1-13
41 张友刚，刘志刚，肖建，基于LMI的仿射型模糊控制系统的稳定性研究，《控制与决策》，2003年第6期
42 Y.Y. Cao, EM. Frank, Analysis and synthesis of nonlinear time-delay systems via fuzzy control approach, IEEE Trans. Fuzzy Systems, 2000, 8(2): 200-211
43 K.R. Lee, J.H. Kim, E.T. Jeung, H.B. Park, Output feedback robust H~∞ control of uncertain fuzzy dynamic systems with time-varying delay, IEEE Trans. Fuzzy Systems, 2000, 8(6): 657-664
44 Y. Zhang, A.H. Pheng, Stability of fuzzy control systems with bounded uncertain delays, IEEE Trans. Aut. Control, 2002, 10(1): 92-97
45 C.W. Park, J.H. Kim, S. Kim, M. Park, LMI-based quadratic stability analysis for hierarchical fuzzy systems, IEE Proc., Control Theory Appl., 2001, 148(5): 340-349
46 S. Boyd. L. Ghaoui, E. Feron, V. Balakrishnan, Linear matrix inequalities in systems and control theory. Philadelphia, PA: SIAM 1994
47 丁永生，应浩，任立红，邵世煌，解析模糊控制理论：模糊控制系统的结构和稳定性分析，控制与决策，2000，15(2)：129-135
48 Y. Nesterov, A. Nemirovskii, Interior-point polynomial methods in convex programming. Philadelphia, PA: SIAM 1994
49 P. Gahinet, A. Nemirovski, A.J. Laub, M. Chilali, LMI control toolbox. Natick, MA: Mathworks, 1995
50 H.D. Tuan, P. Apkarian, T. Narikiyo, and Y. Yamamoto, Parameterized linear matrix inequality techniques in fuzzy control system design, IEEE Trans., Fuzzy Syst., 2001, 9(2): 324-332
51 W. Wu, S. Xu, D. Yue, F.Liu, Fuzzy controller and observer design for nonlinear system-LMI method, Proc. The 4th World Congress on Intelligent Control and Automation, Shanghai,P.R.China, 2002:1920-1924
52 Y. Yang, Y. Dong, X. Guo, Guaranteed-cost design based on T-S fuzzy model, Proc. The 4th World Congress on Intelligent Control and Automation, Shanghai, P.R.China, 2002:1862-1866
53 L. Udawatta, K. Watanabe, K. Kiguchi, K. lzumi, Fuzzy-chaos hybrid controller for controlling of nonlinear systems, IEEE Trans. Fuzzy Systems, 2002, 10(3): 401-411
54 M.Jamshidi, Large-scale systems: modeling and control, North-Holland, 1983
55 M.S. Mahmoud, M.G. Singh, Large-scale systems modeling, Pergamon Press, 1981
56 陈禹六，大系统理论及其应用，北京，清华大学出版社，1988
57 M.D. Mesarovic, D. Macko, Y. Takahara, Theory of hierarchical multilevel systems, New York,Academic, 1970
58 S.A. Arafeh, Hierarchical control of power distribution systems, IEEE Trans. Aut. Control, 1978,
23(2): 333-343
59 M.G. Singh, Decentralized control, North-Holland, Amsterdam, 1981
60 S.H. Wang, E.J. Davison, On the stabilization of decentralized control systems, IEEE Trans. Aut. Control, 1973, 18(5): 473-478
61 M. Araki, Applications of M-matrices to the stability problems of composite systems, J. Math. Anal. Applic. 1975, 52:309-321
62 M. Araki, Input-output stability of composite feedback systems, IEEE Trans. Aut. Control, 1976, 21(2):254-259
63 M. Araki, Stability of large-scale nonlinear systems-quadratic order theory of composite system method using M-matrices, IEEE Trans. Aut. Control, 1978, 23(2):129-142
64 F.M. Callier, W.S. Chan, C.A. Desoer, Input-output stability of interconnected systems using decomposition: an improved formulation, IEEE Trans. Aut. Control, 1978, 23(2):150-163
65 E.J. Davison, Decentralized robust control of unknown systems using tuning regulators, IEEE Trans. Aut. Control, 1978, AC23:276-289
66 N. Sandell, P. Varaiya, M. Athans, M.G. Safonov, Survey of decentralized control methods for large scale systems, IEEE Trans. Aut. Control, 1978, AC23:108-128
67 G. Cohen, Optimization by decomposition and coordination: a unified approach, IEEE Trans. Aut. Control, 1978, 23(2): 222-232
68 J.C. Geromel, J. Bernussou, Optimal decentralized control of dynamic systems, Automatica, 1982, 18(5): 545-557
69 E.J. Davison, U. Ozguner, Characterization of decentralized fixed modes for interconnected systems, Automatica, 1983, 19(2): 169-182
70 A. Saberi, H. Khalil, Decentralized stabilization of interconnected systems using output feedback, Int. J. Control, 1985, 41:1461-1475
71 D.Z. Zheng, Decentralized output feedback stabilization of a class of nonlinear interconnected systems, IEEE Trans. Aut. Control, 1989, 34(12): 1297-1300
72 M.K. Sundareshan, R.M. Elbana, Qualitative analysis and decentralized controller synthesis for a class of large scale systems with symmetrically interconnected subsystems, Automatica, 1991,27:383-388
73 L. Shi, S.K. Singh, Decentralized control for interconnected uncertain systems: extensions to higher uncertainties, Int. J. Control, 1993, 57:1453-1468
74 T.N. Lee, U.L. Radovic, General decentralized stabilization of large-scale linear continuous and discrete time-delay systems, Int. J. Control, 1987, 46(6): 2127-2140
75 B.S. Chen, W.J. Wang, Robust stabilization of nonlinearly perturbed large-scale systems by decentralized observer-controller compensators, Automatica, 1990, 26(6): 1035-1041
76 X.G. Yan, G.Z. Dai, Decentralized output feedback robust control for nonlinear large-scale systems, Automatica, 1998, 34(11): 1469-1472
77 X.G. Yan, J.J. Wang, X.Y. Lu, S.Y. Zhang, Decentralized output feedback robust stabilization for a class of nonlinear interconnected systems with similarity, IEEE Trans. Aut. Control, 1998, 43(2): 294-299
78 温香彩，刘永清，不确定关联大系统的分散变结构控制设计，控制理论与应用，1995，12(4)：429-436
79 桂卫华，陈宁，吴敏，不确定关联大系统鲁棒分散可靠H_∞控制，控制理论与应用，2002，19(6)：923-926
80 关新平，不确定性离散时滞大系统的分散镇定控制，系统工程与电子技术，2002，24(6)：66-69
81 刘红霞，胥布工，朱学峰，一类不确定关联时滞大系统的分散H_∞控制器设计-LMI方法，控制理论与应用，2001，18(6)：954-960
82 F.N. Bailey, The application of Lyapunov's second method to interconnected system, SIAM J.Control, 1966, 3:443-462
83 D.D. Siljak, On stability of large-scale systems under structural perturbations, IEEE Trans. Systems Man, and Cybernetics, 1973, 3:415-417
84 D.D. Siljak, Large-scale dynamic systems—stability and structure, North-Holland, New York
85 E.L. Lasley, A.N. Michel, Input-output stability of interconnected systems, IEEE Trans. Aut. Control, 1976, 21(1): 84-89
86 D.Y. Xu, BIBO stabilization of large-scale systems, Control Theory and Applications, 1995,12(6): 758-763
87 V. Lakshmikantham, S. Leela, Differential and integral inequalities, New York: Academic, 1969
88 D.D. Siljak, Competitive economic systems: stability, decomposition and aggregation, IEEE Trans. Aut. Control, 1976, 21(2): 149-160
89 M. Araki, B. Kondo, Stability and transient behavior of composite nonlinear systems, IEEE Trans. Aut. Control, 17(4): 537-541
90 A.N. Michel, Stability analysis of interconnected systems, SIAM J. Contr., 1974, Vol. 12
91 F.H. Hsiao, J.D. Hwang, L.G. Shiau, Decentralized stabilization of fuzzy large-scale systems, In Proc. IEEE Conf. Decision Contr., Sydney, Australia, 2000:3447-3452
92 F.H. Hsiao, J.D. Hwang, Stability analysis of fuzzy large-scale systems. IEEE Trans. Syst., Man, and Cybern. 2001, 32(1): 122-126
93 W.J. Wang, L.G. Mao, Stabilization and estimation for perturbed discrete time-delay large-scale systems, IEEE Trans. Aut. Control, 1997, 42(9):1277-1282
94 L. Yu, U. Holmberg, D. Bonvin, Decentralized robust stabilization of a class of interconnected uncertain delay systems, Control-Theory and Advanced Technology, 1995, 10(4): 1475-1483
95 I.H. Suh, Bien Z, A note on the stability of large-scale systems with delays, IEEE Trans. Aut. Cotrol, 1982, 27(1): 256-258
96 俞立，一类线性离散时滞大系统的分散镇定，控制理论与应用，2000，17(1)：125-127，132
97 S. Xie, L. Xie, Y. Wang, G. Guo, Decentralised control of multi-machine power systems with guaranteed performance, IEE Proc. Control Theory Appl., 2000, 47(3): 355-365
98 A.N. Michel, R.K. Miller, Qualitative analysis of large scale dynamical systems, Academic Press, London, 1977
99 张友刚，向静，肖建，基于LMI的参数不确定性关联模糊大系统的分散鲁棒镇定，《控制
理论与应用》，已录用
100 张友刚，向静，肖建，离散模糊大系统的分散化PDC控制器设计：LMI方法，《控制与决策》，已录用。
101 关新平，陈彩莲，刘奕昌，段广仁，不确定时滞系统的模糊保成本控制，控制与决策，2002，17(2)：178-182
102 G. Zames, On the input-output stability of nonlinear time-varying feedback systems, Partⅰand part ⅱ, IEEE Trans. Aut. Control, 1966, 11(2) : 228-238,465-477
103 D.C. Youla, L.J. Castriota, H.J. Carlin, Bounded real scattering matrices and the foundation of linear passive network theory, IRE Tr. CT-4(1), 1959:102-124
104 M. Vidyasagar, Nonlinear systems analysis (2nd Edition), Prentice Hall, London, 1993
105 B. Barmish, H.I. Kang, A survey of extreme point results for robustness of control systems, Automatica, 1993,29(1):15-35
106 J. Ezzine, Robust stability of bounds for sample data systems, Int. J. Syst. Sci, 1995, 26(10): 1951-1966
107 F.M. Al-Sunni, Robust control of sample data systems, IEE Proc. Control Theory Applications, 1998, 145(2):236-240
108 冯纯伯，鲁棒控制系统分析与设计，东南大学出版社，1996
109 M. Malek-Zavarei, M. Jamshidi, Time-delay systems: analysis, optimization and applications, North-Holland, Amsterdam, 1987
110 P. Jiang, H. Su, J. Chu, Optimal guaranteed cost control for a class of linear uncertain time-delay systems, Proc. the 3th World Congress on Intelligent Control and Automation, Hefei, P.R. China, 2000:3354-3358
111 S. Chang, T. Peng, Adaptive guaranteed cost control of systems with uncertain parameters, IEEE Trans. Aut. Control, 1972, 17(4): 356-361
112 廖晓昕，动力系统的稳定性理论和应用，国防工业出版社，2000
113 廖晓昕，稳定性的数学理论和应用，武汉，华中师范大学出版社，1998
114 A.M. Lyapunov, Problème général de la stabilité du movement, V.17, Annals of Mathematics Studies, Princeton University Press, Princeton, 1947
115 L.X. Wang, J.M. Mendel, Fuzzy basis functions, universal approximation, and orthogonal least squares learning, IEEE Trans. Neural Networks, 1992, 3(5): 807-814
116 X.J. Zeng, M.G. Singh, Approximation theory of fuzzy systems-SISO case, IEEE Trans. Fuzzy Systems, 1994, 2(2): 162-176
117 X.J. Zeng, M.G. Sing, h, Approximation theory of fuzzy systems-MIMO case, IEEE Trans. Fuzzy Systems, 1995, 3(2):219-235 .
118 X.J. Zeng, M.G. Singh, Approximation accuracy analysis of fuzzy systems as function approximators, IEEE Trans. Fuzzy Systems, 1996, 4(1): 44-63
119 E.N. Lorenz, Deterministic non-periodic flow, J. Atmos. Sci., 1963(20): 130-141
120 K. Tanaka, Advanced fuzzy control, Kyoritsu Pub. 1994, in Japanese
121 A.I. Lur'e, V.N. Postnikov, On the theory of stability of control systems. Applied mathematics and mechanics,8(3), in Russian
122 V.A.Yakubovich, Frequency conditions for the existence of absolutely stable periodic and almost periodic limiting regimes of control systems with many non-stationary elements. In IFAC World Congress, London, 1966
123 V.A.Yakubovich, The method of matrix inequalities in the stability theory of nonlinear control systems, Ⅰ, Ⅱ, Ⅲ, Automation and Remote Control, 1967, 25-26(4): 905-917,577-592,753-763
124 V.M.Popov, Absolute stability of nonlinear systems of automatic control, Automation and Remote Control, 1962, 22:857-875
125 V.M.Popov, One problem in the theory of absolute stability of controlled systems, Automation and Remote Control, 1964, 25(9): 1129-1134
126 R.E.Kalman, Lyapunov functions for the problems of Lur's in automatic control, Proc. Nat. Acad. Sci, USA, 1963, 49:201-205
127 J.C.Willems, Least squares stationary optimal control and the algebraic Riccati equation, IEEE Trans. Aut. Control, 1971, 16(6):621-634
128 V.J.S. Karmarkar, D.D. Siljak, Maximization of absolute stability regions by mathematical programming methods, Regelungstechnik, 1975, 2:59-61
129 Y. Nesterov and A. Nemirovsky, A general approach to polynomial-time algorithms design for convex programming, Technical report, Centr. Econ. & Math. Inst., USSR Acad. Sci., Moscow, USSR, 1988
130 J. Yoneyama, M. Nishikawa, H. Katayama, A. Ichikawa, Output stabilization of Takagi-Sugeno fuzzy systems, Fuzzy Sets and Systems, 2000(111): 253-266
131 M.G. Safonov, Stability and robustness of multivariable feedback systems, MIT Press, Cambridge, MA, 1980
132 J. Doyle, K. Glover, P. Khargonekar, B. Francis, State space solutions to standard H~2 and H~∞ control problems, IEEE Trans. Aut. Control, 1989, 24(8): 731-747
133 J. Doyle, Synthesis of robust controllers and filters with structured plant uncertainty, in Proc. IEEE Conf. Decision and Control, New York, December, 1983
134 D.C. McFarlane, K. Glover, Robust controller design using normalized coprime Factor Plant. Descriptions. Berlin: Springer Verlag, 1990
135 Doyle J C, Francis B A and Tannenbaum A R. Feedback control theory.New York: Macmillan, 1992
136 J. Hale, S. Lunel, Introduction to functional differential equations, New York: Springer-Verlag,1993
137 I.R. Petersen, D.C. Mcfarlane, Optimal guaranteed cost control and filtering for uncertain linear systems, IEEE Trans. Aut. Control, 1994, 39(9):1971-1977
138 J. Zhao, R. Gorez, V. Wertz, Synthesis of fuzzy control systems with desired performances, Proc. The 1996 Int. Symp. Intelligent Control, Dearborn, MI, 1996:115-120
139 俞立，不确定离散系统的最优保性能控制，控制理论与应用，1999，16(5)：639-642
140 关新平，张群亮，一类广义系统的弹性保成本控制器设计，Proc. the 4th World Congress on Intelligent Control and Automation, Shanghai, ER. China, 2002:160-164
141 T. Kaileth, Linear Systems, Englewood Cliffs, N.J.: Prentice Hall, 1980