用户名: 密码: 验证码:
永磁同步电机的混沌控制方法研究
详细信息    本馆镜像全文|  推荐本文 |  |   获取CNKI官网全文
摘要
永磁同步电动机(PMSM)具有体积小、重量轻、反应快、效率高等优点,随着电力电子技术和控制技术的发展,永磁同步电动机交流伺服系统已经在现代高性能伺服系统中得到了极为广泛的应用,尤其是近年来,随着永磁材料的迅速发展,电力电子和控制技术的进步,永磁同步电机将越来越多地替代传统电机,应用前景非常的乐观,因而对永磁同步电机的研究是非常有意义的。
     本篇论文首先研究了永磁同步电机的混沌行为,研究表明,永磁同步电机对输入参数非常敏感,当参数落入某个区域时,永磁同步电机会产生混沌现象,由于这种混沌现象对于永磁同步电机来说是非常有害的,应该给予抑制。所以,本文研究的重点是对永磁同步电机中的混沌现象实施控制。另外,系统可能由于机械磨损,建模误差,或者测量误差导致参数的不确定性,于是,在研究的过程中考虑了参数不确定的情况,针对参数不确定的永磁同步电机,分析了混沌现象的存在,然后也研究其混沌现象的控制策略。
     对于永磁同步电机的混沌控制策略的研究,主要做了以下工作:(1)研究了参数固定永磁同步电机的脉冲控制策略,通过Lyapunov方法得出使其稳定运行的充分条件,然后对参数不确定的永磁同步电机设计脉冲控制器,并通过矩阵分析,将系统不确定矩阵进行了有效的表示,在此基础上,得到了参数不确定的永磁同步电机系统渐近稳定和指数稳定的充分条件。(2)提出了永磁同步电机模糊控制的数学模型,并针对参数固定和参数不确定的永磁同步电机设计相应的模糊控制器,并分别得出了参数固定和参数不确定的永磁同步电机的稳定性条件。(3)在研究脉冲控制和模糊控制的基础上,提出模糊脉冲控制的混沌数学模型,设计一种能够综合利用脉冲控制和模糊控制优点的控制器,并研究其稳定性,得出了参数固定和参数不确定的两种永磁同步电机的渐近稳定和指数稳定的充分条件,同时也指出,当脉冲间距比较大的时候,模糊脉冲控制的控制难度越来越大,理论上虽然存在相应的模糊脉冲控制器,但在实际应用中会增大成本,因此不利于实际利用,于是,在脉冲间隔比较小的情况小,做相应的模糊脉冲控制是非常有效的。本文对所提出的方法都做了数值模拟,模拟结果表明所得的结果对于永磁同步电机的稳定性控制是有效的。
     在实际运行中的永磁同步电机,由于电压的不稳定,工作环境的瞬间振动等,有可能导致电机系统出现扰动现象,于是本文最后对具有扰动的永磁同步电机进行研究,重点研究具有脉冲扰动的永磁同步电机,同样考虑了其中参数固定和参数不确定的两种情况,首先提出数学模型,然后设计相应的控制规则,并研究其稳定性,得到了参数固定和参数不确定的永磁同步电机渐近稳定和指数稳定的充分条件。最后针对上面的研究结果,进行了相应的数值模拟,数值实验进一步证实了本论文所研究结果的有效性。
     总而言之,本文把脉冲理论、模糊理论引入到永磁同步电机系统是一种全新的思想,根据脉冲微分方程的基本理论、模糊控制的基本理论和Lyapunov稳定性理论,研究在脉冲控制、模糊控制以及模糊脉冲控制框架下的永磁同步电机系统稳定和控制问题,为永磁同步电机的应用和发展打下了良好的基础。
Permanent magnet synchronous motors (PMSMs) have superior features such as compact size, high torque/weight ratio, high torque/inertia ratio and absence of rotor losses, and advantages of higher efficiency compared with induction motors. With the development of electronic technology and control technology, the PMSMs are widely applied in high performance servosystem. Especially in rencent years, the conventional motors were superseded by PMSMs due the development of permanent-magnet material and control echnology. The foreground application is very optimistic. So it is important to sduty the permanent magnet synchronous motors.
     In this paper, the chaos fo PMSMs is investigated firstly. The study indicates that PMSMs are sensitive to the parameters, the chaotic phenomena will happen if the parameters fall into some area. Because the chaos is baneful to the PMSMs, we must restrain it for PMSMs. So the emphasis of this paper is studying the method of controlling chaos of PMSMs. Furthermore, the values of parameters of the PMSM model are not constant, but span some interval. The main reason is that the permanent magnetic-flux will vary with the temperature rise of permanent-magnet material and rotary inertia will vary with the attrition of the device, or modelling errors, measurement inaccuracy, and so on. The parameters uncertains will be considerd in our study. So we investigate the chaos and the control strategy for PMSMs with parameters uncertains.
     As for the study of the chaotic control strategy for PMSMs, the main results in this paper can be described as follows: (1) The impusive control strategy for PMSMs with fixed parameters si investigated firstly. Then the sufficient conditions of the robust stability are established by employing the method of Lyapunov functions. Then the impulsive controller is designed for PMSMs with uncertain parameters. After the uncertain matrixes which represent the variable system parameters are formulated through matrix analysis, the asymptotical/exponential stability criteria of fuzzy control are established. (2) The fuzzy control mathematics model is established, and the fuzzy controllers for PMSMs with fixed and uncertain parameters are designed respectively. (3) Based on the above study, the chaotic fuzzy impulsive control model is brought forward. The fuzzy impulsive controller which containing the merits of fuzzy and impulsive controller is designed. The stability of fuzzy impulsive control is investigated, and the asymptotical/exponential stability criteria of fuzzy impulsive control are established for PMSMs with fixed and uncertain parameters. Our results indicate that the fuzzy impulsive control is difficult with the increase of pulse spacing, the theoretical controller exists but the control cost will increase. So the fuzzy impulsive control is effective for small pulse spacing. The numerical simulations illustrate the affectivity of all the above control strategy.
     Otherwise, the disturbances exist in PMSMs due to the instability of voltage, concussion of running circumstance and so on. So the PMSMs with disturbances especially impulsive effects are investigated in the end of this paper. As the analysis of the above, the PMSMs with fixed parameters and uncertain parameters are considered. Firstly, the chaotic mathematics model is brought forward. Then the control rules are designed. And the asymptotical/exponential stability criteria for PMSMs with impulsive effects are established. Furthermore, the numerical simulations illustrate the affectivity of the above control strategy for PMSMs with impulsive effects.
     In a word, it is creative to apply the impulsive theory and fuzzy theory to PMSMs. The stability of PMSMs is investigated by the theory of impulsive differential equation, fuzzy control and Lyapunov function. It is important for the application and development of PMSMs.
引文
[1]符曦.高磁场永磁式电动机及其驱动系统[M].机械工业出版社,北京, 1996.
    [2]唐任远.现代永磁电机的理论与设计[M].机械工业出版社,北京, 1997.
    [3]暨绵浩,曾岳南,曾建安,李长兵. [0]永磁同步电动机及其调速系统综述和展望[J].电气时代, 2005.5(1):20-23.
    [4]王江,李韬等.基于观测器的永磁同步电动机微分代数非线性控制[J].中国电机工程学报, 2005.25(2):87-92.
    [5]周世梁,韩璞,刘玉燕.永磁同步电机混沌系统的鲁棒PID控制[J].电机与控制学报, 2005.119(16):610-616
    [6] Bayer K H ,Blashke F. Stability problem with the control of induction motors using the method of field orientation[C]. Conf . Record of IEEE Industry Application Society Annual Meeting ,1989.15(5):384-389.
    [7] Krishan R , et al . A review of parameter sensitivity and adaptation in indirect vector controlled induction motor drives systems[J]. IEEE Trans. on Power Electronics , 1991.6(4):695-703.
    [8] Joachim H. The induction motor a dynamic system[C]. IEEE IECON’94 ,1994 :126.
    [9]张波,李忠,毛宗源,庞敏熙.电机传动系统不规则运动和混沌现象初探[J].中国电机工程学报, 2001, 21 (7) : 40 - 45.
    [10]曹志彤,郑中胜.电机运动系统的混沌特性[J].中国电机工程学报, 1998.18(5): 319-322.
    [11]张卓,李忠,任平.永磁同步电动机中的混沌现象[J].模糊系统与数学,2001.15(2):102-106.
    [12] Du Qu Wei, Xiao Shu Luo, Bing Hong Wang, Jin Qing Fang,Robust adaptive dynamic surface control of chaos in permanent magnet synchronous motor[J]. Physics Letters A 2007. 363(1):71–77.
    [13]张波,李忠,毛宗源,庞敏熙.一类永磁同步电动机混沌模型与霍夫分叉[J].中国电机工程学报, 2001.21(9):114-119.
    [14] Li Z, Park JB, et al. Bifurcations and chaos in a permanent-magnet synchronous motor[J]. IEEE Trans CAS (I) 2002.49(3):601–11.
    [15] Zhujun Jing, Chang Yu, Guanrong Chen. Complex dynamics in a permanent-magnet synchronous motor model[J].Chaos, Solitons and Fractals 2004.22(1):831–848.
    [16] Li Z, Zhang B, Mao Z Y, Analysis of the chaotic phenomena in permanent-magnet synchronous motors based on Poincare map[C]. The 3rd World Congress on IntelligenceControl and Intelligent Automation . Hefei , 2000.3255-3258
    [17]张波,李忠,毛宗源.永磁同步电动机的混沌特性及其反混沌控制[J].控制理论与应用,2002.19(4):545-548.
    [18] E. Ott, C. Grebogi, J.A. Yorke, Controlling chaos[J]. Phys. Rev. Lett. 1990.64(1):1196-1199.
    [19]王忠勇,蔡远利,贾冬.混沌系统的小波基控制[J].物理学报, 1999.48(2):206-212.
    [20]任海鹏,刘丁.混沌的模糊神经网络逆系统控制,物理学报, 2002.51(5):982-987.
    [21] Tanaka K, Sugeno M. Stability Analysis and Design of Fuzzy Control Systems[J]. Fuzzy Sets and Systems, 1992. 45(1):135-156.
    [22] Tanaka K, Sano M. Fuzzy Stability Criterion of a Class Nonlinear Systems[J]. Information Science, 1993.70(1): 1-26.
    [23] Jing Li, Hua O W, David N, Tanaka K. Dynamic Parallel Distributed Compensation for Takagi-Sugeno Fuzzy Systems: An LMI approach[J]. Information Sciences, 2000.123(3/4): 201-221.
    [24] K. R. Lee, J. H. Kim. Output Feedback Robust H Control of Uncertain Fuzzy Dynamic Systems with Time-Varying Delay[J]. IEEE Trans. On Fuzzy Systems, 2000.8(6):657-664.
    [25] C. C. Hua,X. P. Guan, P. Shi. Adaptive fuzzy control for uncertain interconnected time-delay systems[J]. Fuzzy Sets and Systems 2005.153(1):447–458.
    [26] C. C. Hua, F. L. Li, X. P. Guan. Observer-based adaptive control for uncertain time-delay systems[J]. Information Science 2006.176(1):201-214.
    [27] Liang Chen, Guanrong Chen, Yang-Woo Lee. Fuzzy modeling and adaptive control of uncertain chaotic systems[J]. Information Sciences 1999.121(2):27-37.
    [28] R. J. Wang, W. W. Lin, W. J. Wang. Stabilization of linear quadratic state feedback for uncertain fuzzy time-delay systems[J]. IEEE, Trans. On systems, Man, and Cybernetics-Part B: Cybernetics, 2004.34(2):1288-1292.
    [29] Shousong Hu, Ya Liu. Robust H∞control of multiple time-delay uncertain nonlinear system using fuzzy model and adaptive neural network[J]. Fuzzy Sets and Systems 2004.146(1):403-420.
    [30]王江,李韬等.基于观测器的永磁同步电动机微分代数非线性控制[J].中国电机工程学报,2005.25(2):87-92.
    [31] Franco Blanchinia et al. Aminimum-time control strategy for torque tracking in permanent magnet AC motor drives[J]. Automatica 2007.43(1):505–512.
    [32] Elmas, C. et al.. A neuro-fuzzy controller for speed control of a permanent ... [J]. Expert Systems with Applications (2006), doi:10.1016/j.eswa.2006.10.002.
    [33] Ahmad M. Harb, Ashraf A. Zaher. Nonlinear control of permanent magnet stepper motors[J].Communications in Nonlinear Science and Numerical Simulation, 2004.9(2):443-458.
    [34]谢成祥,曾庆军,许德.交流伺服系统的串级滑模变结构控制仿真研究[J].华东船舶工业学院学报(自然科学版), 2001.15(1):43-44.
    [35]李鸿儒,王建辉.带神经网络观测器的永磁同步电机极点配置自校正前馈控制[J].控制与决策, 2001. 16(S):681-684.
    [36]白华煜,刘军,楚小刚.基于模糊控制永磁同步电机直接转矩控制研究[J].电气传动. 2005.35(5):6-9.
    [37] I.-C. Baik, K.-H. Kim, M.-J. Youn. Robust nonlinear speed control of PM synchronous motor using boundary layer integral sliding mode control technique[J]. Control Systems Technology. 2000. 1:47-54.
    [38] I.-C. Baik, K.-H. Kim, M.-J. Youn. Robust nonlinear speed control of PM synchronous motor using adaptive and sliding mode control techniques[J]. Electric Power Applications. 1998. 4:369-376.
    [39]李忠,张波,毛宗源.永磁同步电动机系统的纳入轨道和强迫迁徙控制[J].控制理论与应用,2002.19(1):53-56.
    [40]韦笃取,罗晓曙,方锦清,汪秉宏.基于微分几何方法的永磁同步电动机的混沌运动的控制[J].物理学报, 2006.55(1):54-59.
    [41]任海鹏,刘丁,李洁.永磁同步电动机中混沌运动的延迟反馈控制[J].中国电机工程学报, 2003.23(6):175-178.
    [42] Ahmad M. Harb, Ashraf A. Zaher. Nonlinear control of permanent magnet stepper motors. Communications in Nonlinear Science and Numerical Simulation. 2004.9(1):443-458.
    [43] Harb A, Zaher A, Al-Qaisia A, Zohdy M. Estimation-based control of chaotic duffing oscillators. Int. J. Vibrat. Contr., in press.
    [44] R. Wai. Total sliding-mode controller for PM synchronous servo motor drive using recurrent fuzzy neural network[J]. Industrial Electronics, 2001.5(1):926-944.
    [45] T.-S. Lee et al.. An adaptive H∞controller design for permanent magnet synchronous motor drives[J]. Control Engineering Practice, 2005.13(1):425-439.
    [46] C. Attaianese, A. Perfetto, G, Tomasso. Robust position control of DC drives by means of H∞controllers[J]. Electric Power Applications, 1999.4:391-396.
    [47] Cetin Elmas, Oguz Ustun. A hybrid controller for the speed control of a permanent magnet synchronous motor drive[J]. Control Engineering Practice, In press.
    [48] B. Liu, X. Liu, X. Liao. Robust stability of uncertain impulsive dynamical systems[J]. J. Math. Anal. Appl.. 2004.290:519-533.
    [49] D.Bainov , V. Covachev. Impulsive differential equations with a small parameter[M]. WorldScientific, Singapore, 1994.
    [50] D. D. Bainov, P.S. Simeonov. Systems with impulse effect: Stability, theory, and applications[M]. Ellis Horwood Limited, Chichester, 1989.
    [51] D. D. Bainov, P.S. Simeonov. Impulsive differential equations: Periodic solutions and applications[M]. Longman Group UK Limited, 1993.
    [52] A.F.Filippov. Differential equations with discontinuous right-hand sides. Mathematics and its applications[M]. Soviet series. Kluwer Academic, Boston, USA, 1998.
    [53] Z.Y. He, Y.F. Zhang, L.X. Yang, Y.H. Shi, Control chaos in nonautonomous cellular neural networks using impulsive control methods(C), In IJCNN’99. International Joint Conference on Neural Networks. Proceedings (Cat.No.99CH36339), 1999.1:262-267.
    [54] R.A. Kiehl, T.Ohshima. Bistable locking of single-electron tunneling elements for digitl circuitry[J]. Applied Physics Letters, 1995.67(17): 2494-2496.
    [55] V.Lakshmikantham, D.D Bainov, and P.S Simeonov. Theory of Impulsive Differential Equations, Series in modern applied mathematics[M]. Singapore and Teanech, NJ:World Scientific, 1989.
    [56] P.S. Simeonov , D.D. Bainov. Stability with respect to part of the variables in systems with impulse effect[J]. Journal of Mathematical Analysis and Applications, 1986.117(1): 247-263.
    [57] L.B. Yang, T. Yang, Impulsive synchronization of nonautonomous chaotic systems[J]. Acta Physica Sinica, 2000.49(1): 33-37.
    [58] T. Yang, C. M. Yang, L.-B. Yang. Control of R?ssler system to periodic motions using impulsive control method[J]. Physics Letters A, 1997.232(5): 356-361.
    [59] T. Yang, L. B. Yang, C. M. Yang. Impulsive control of Lorenz system[J]. Physica D, 1997.110(1-2): 18-24.
    [60] T. Yang, L.B. Yang. The global stability of fuzzy cellular neural network[J]. IEEE Transactions on Circuits and Systems-I: Fundamental Theory and Applications, 1996.43(10): 880-883
    [61] F. Zou, J.A. Nossek. A chaotic attractor with cellular neural networks[J]. IEEE Transactions on Circuits and Systems, 1991.38(7): 811-12.
    [62] X.J. Ma, Z.Q. Sun, Y.Y. He. Analysis and Design of Fuzzy Controller and Observer[J]. IEEE Transactions on Fuzzy Systems, 1998.16(1): 41-51.
    [63] H.J. Lee, J.B. Park, G.R. Chen. Robust Fuzzy Control of Nonlinear Systems with Parametric Uncertainties[J]. IEEE Transactions on Fuzzy Systems, 2001.9(2):369-379
    [64] L. Xie. Output Feedback H∞Control of System with Parameter Uncertainties[J]. Int. J. Control, 1996.63(4):741-750.
    [65]张文修,梁广锡.模糊控制与系统[M].西安交通大学出版社, 1998.
    [66]诸静等.模糊控制原理与应用[M].机械工业出版社, 1995.
    [67]张乃尧,阎平凡.神经网络与模糊控制[M].清华大学出版社, 2002.
    [68]韩峻峰.模糊控制技术[M].重庆大学出版社, 2003.
    [69] K. Tanaka, T. Ikeda, H. O. Wang. A unified approach to controlling Chaos via an LMI-based fuzzy control system design[J]. IEEE Trans. Circuits Syst. I, 1998.45:1021–1040,
    [70] S. W. Kau, H. J. Lee, C. M. Yang, etc.,Robust H∞fuzzy static output feedback control of T-S fuzzy systems with parametric uncertainties[J]. Fuzzy Sets and Systems, 2007.158 (1): 135-146.
    [71] W. Chang, J. B Park, Y. H. Joo, G. R. Chen. Static output-feedback fuzzy controller for Chen’s chaotic system with uncertainties[J]. Information Sciences, 2003.151 (2):227-244.
    [72] X. W. Liu, S. M Zhong. T-S fuzzy model-based impulsive control of chaotic systems with exponential decay rate[J]. Phys. Lett. A, 2007.370( 1):260-264.
    [73] Daniel W. C. Ho, J. T. Sun. Stability of Takagi–Sugeno fuzzy delay systems with impulse, IEEE Trans. ON Fuzzy Syst. In press (2007).
    [74]张波,李忠,毛宗源.永磁同步电动机的混沌模型[J].控制理论与应用,2002.19(6):841-844.
    [75] Ahmad M. Harb. Nonlinear chaos control in a permanent magnet reluctance machine Chaos[J]. Solitons and Fractals, 2004.19 (1) 1217–1224.
    [76] Sanchez EN, Perez JP. Input-to-state stability analysis for dynamic NN[J]. IEEE Transactions on Circuits Systems. 1999.46(2):1395-1398.
    [77] Liang Chen, Guanrong Chen, Yang-Woo Lee. Fuzzy modeling and adaptive control of uncertain chaotic systems[J]. Information Sciences, 1999.121 (1) 27-37.
    [78] H. Lee, J. Park, G. Chen. Robust Fuzzy Control of Nonlinear Systems with Parametric Uncertainties[J]. IEEE Transactions on Fuzzy Systems, 2001. 9(3):369-379.
    [79] K. Tanaka, T. Ikeda, H. O. Wang. A unified approach to controlling Chaos via an LMI-based fuzzy control system design[J]. IEEE Trans. Circuits Syst. I, 1998.45(1):1021–1040.
    [80]张血琴,吴广宁,郭俊,佟来生,张国钦.高频连续脉冲作用下电机绝缘局部放电信号的提取[J].电工技术学报, 2005.20(9):103-107.
    [81] Campbell S R, Stone G C. Examples of stator winding partial discharge due to inverter drives[C]. Conference Record of the 2000 IEEE International Symposium on Electrical Insulation, Anaheim, CA USA, 2000:231-234.
    [82] Candela R, Petrarca C, Ronmano P , et al., Numerical simulation of PD activity in a spherical cavity embedded in the stator winding insulation of an inverter-fed insulation motor[C]. 2001Annual Report Conference on Electrical Insulation and Dielectric Phenomena, 2001:356-360.
    [83] Candela R, Petrarca C, Ronmano P. Effect of high frequency conducted disturbances on the interturn insulation of an inverter-fed induction motor[C]. 2003 Annual Report Conference on Electrical Insulation and Dielectric Phenomena, 2003:510-513.
    [84] Yongqing Yang, Jinde Cao. Exponential lag synchronization of a class of chaotic delayed neural networks with impulsive effects[J]. Physica A ,2007.386 (7) 492–502.
    [85] H. Ye, A. Michel, L. Hou. Stability analysis of systems with impulse effects[J]. IEEE Trans. on Automat. Control. 1998.43(1):1719-1723.
    [86] Yonghui Xia, Jinde Cao, Sui Sun Cheng. Global exponential stability of delayed cellular neural networks with impulses[J]. Neurocomputing ,2007.70 (1):2495–2501.
    [87] K. Gopalsamy. Stability of artificial neural networks with impulses[J]. Appl. Math. Comput. 2004.154(1):783–813.
    [88] H. Akca, R. Alassar, V. Covachev, Z. Covachev, E.A. Zahrani. Continuous-time additive Hopfield-type neural networks with impulses[J]. J. Math. Anal. Appl. 2004.290(1):436–451.
    [89] D. Xu, Z. Yang. Impulsive delay differential inequality and stability of neural networks[J]. J. Math. Anal. Appl. 2005.305 (1):107–120.
    [90] Y. Yang, J. Cao. Stability and periodicity in delayed cellular neural networks with impulsive effects[J]. Nonlinear Anal. RWA 2008.8 (1):362–374.
    [91] T. Stojanovski, L. Kocarev, U. Parlitz. Driving and synchronization by chaotic impulses[J]. Phys. Rev. E 1996.43(9):782–785.
    [92] M. U. Akhmetov and A. Zafer. Stability of the Zero Solution of Impulsive Differential Equations by the Lyapunov Second Method[J]. Journal of Mathematical Analysis and Applications, 2000.248(1):69-82
    [93] V. Lakshmikantham and X. Liu. On quasi stability for impulsive differential systems[J]. Nonlinear Anal. 1989.13:819-828.
    [94] X. Liu and R. Pirapakaran. Global stability results for impulsive differential equations[J]. Appl. Anal. 1989.33:87-102.
    [95] G. Ioannidis, S. Manias. H∞loop-shaping control schemes for the buck converter and their evaluation usingμ-analysis[J]. Electric Power Applications. 1999.2:237-246.
    [96] Karunadasa J.P., Renfrew A.C.. Design and implementation of microprocessor based sliding mode controller for brushless servomotor[J]. Electric Power Applications. 1991.6:345-363
    [97] F. Lin, S. Chiu. Adaptive fuzzy sliding-mode control for PM synchronous servo motor drives[J]. Control Theory and Applications. 1998.1:63-72.
    [98] J. Yan, J. Shen. Impulsive stabilization of functional differential equations byLyapunov-Razumikhin functions[J]. Nonlinear Analysis. 1999.37: 245-255.
    [99] V. Lakshmikantham, D.D. Bainov, P.S. Simeonov. Theory of Impulsive Differential Equations [M]. World Scientific, Singapore, 1989.
    [100] A.M.Samoilenko and N.A. Perestyuk. Impulsive Differential Equations[M]. World Scientific, Singapore, 1995.
    [101] T. Yang, L. Chua. Practical stability of impulsive synchronization between two nonautonomous chaotic systems[J]. International Journal of Bifurcation and Chaos in Applied Sciences and Engineering. 2000.10:859-867.
    [102] T. Yang, J. Suykens, L. Chua. Impulsive control of nonautonomous chaotic systems using practical stabilization[J]. International Journal of Bifurcation and Chaos. 1998.8: 1557-1564.
    [103] J. Cao. New results concerning exponential stability and periodic solutions of delayed cellular neural networks[J]. Phys. Lett. A. 2003.307:136-47.
    [104] J. Cao, Q. Li. On the Exponential Stability and Periodic Solutions of Delayed Cellular Neural Networks[J]. Journal of Mathematical Analysis and Applications. 2000.252:50-64.
    [105] X. Liao, J. Yu, G. Chen. Novel stability criteria for bidirectional associative memory neural networks with time delays[J]. Int. J. Circ. Theory Appl., 2002.30:519-46.
    [106] C. Li, X. Liao, R. Zhang, Ashutosh Prasad. Global robust exponential stability analysis for interval neural networks with time-varying delays[J]. Chaos, Solitons and Fractals. 2005.25:751-757.
    [107] M. Feng and C.J. Harris. Feedback Stabilization of Fuzzy Systems Via Linear Matrix Inequalities[J]. International Journal of Systems Science, 2001.32(2):221-231.
    [108] M. Feng and C.J. Harris. Piecewise Lyapunov Stability Conditions of Fuzzy Systems[J]. IEEE Transactions on Systems, Man and Cybernetics, 2001.32(3):1245-1256.
    [109] K. Tanaka, T. Ikeda and H.O. Wang. Robust Stabilization of a Class of Uncertain Nonlinear Systems via Fuzzy Control: Quadratic Stabilizability, H∞Control Theory and Linear Matrix Inequalities[J]. IEEE Transactions on Fuzzy Systems, 1996.4(1):1-13.
    [110] P.P.Khargonekar, I.R. Petersen and K. Zhou. Robust Stabilization of a Class of Uncertainty linear Systems: Quadratic Stabilizability and H∞Control Theory[J]. IEEE Transactions on Automatic Control, 1990.35(3):356-361
    [111] J. Yoneyama. H∞Control for Takagi-Sugeno Fuzzy Systems[J]. International of Systems Science, 2001.32(7):915-924.
    [112] K. Zhou, J.C. Doyle, K. Glover. Robust and Optimal Control[M]. Englewood, New Jersey: Prentice-Hall, 1996.
    [113] S.G.Gao, N.W. Rees, G.Feng. H∞Control of Uncertainty Fuzzy Continuous-TimeSystems[J]. Fuzzy Sets and Systems, 2000.115(1):171-190.
    [114] N. Zhang, G. Feng. H∞Control Feedback Control Design of Fuzzy Dynamic Systems via LMI[J]. Acta Automatics Sinical, 2001.27(27):495-505.
    [115] H.K. Lam, F.H.F. Leung, P.K.S. Tam. Fuzzy Control of a Class of Multivariable Nonlinear Systems Subject to Parameter Uncertainties: Model Reference Approach[J]. International Journal of Approximate Reasoning, 2001.26:129-144.
    [116] B.S. Razumikin. The Application of Lyapunov’s Method to Problem in Stability with Delay[J]. Automatic & Remote Control, 1960.21(3):515-520.
    [117] T.A. Johansen. Fuzzy Model Based Control: Stability, Robustness, and Performance Issues, IEEE Transactions on Fuzzy Systems, 1994.2(3):221-234.
    [118] S.C. Tong, T.Y. Chai. Direct Adaptive Fuzzy Control and Robust Analysis Systems for Unknown Multivariable Nonlinear Systems[J]. Fuzzy Sets and Systems, 1999.106:309-319.
    [119] T.A. Johansen, B.A. Foss. Constructing NARMAX Models Using ARMAX Models[J]. Int. J. Control, 1993.58(3):1125-1153.
    [120] B. Sen Chen, C.S. Tseng, H. Uang. Robustness Design of Nonlinear Dynamic via Fuzzy Linear Control[J]. IEEE Transactions on Fuzzy Systems, 1999.7(5):571-585.
    [121] C.S. Tseng, B.S., Chen H. Uang. Fuzzy Tracking Control Design for Nonlinear Dynamic Systems via T-S fuzzy Model[J]. IEEE Transactions on Fuzzy Systems, 2001.9(3): 381-392.
    [122] S.C. Tong, T. Wang, H.X. Li. Fuzzy Robust Tracking Control Design for Uncertain Nonlinear Dynamic Systems[J]. International Journal of Approximate Reasoning, 2002.30(2):73-90.
    [123] A.M.Samoilenko and N.A. Perestyuk. Impulsive Differential Equations[M]. World Scientific, Singapore, 1995.
    [124] Lu Z, Chi X, Chen L. Impulsive control strategies in biological control of pesticide[J]. J. Theor. Popul. Biol. 2003.64:39-47.
    [125] T. Yang, L.O. Chua. Practical stability of impulsive synchronization between two nonautonomous chaotic systems[J]. International Journal of Bifurcation and Chaos in Applied Sciences and Engineering, 2000.10:859-867.
    [126] T. Yang, J.A.K. Suykens, L.O. Chua. Impulsive control of nonautonomous chaotic systems using practical stabilization. International Journal of Bifurcation and Chaos, 1998.8(7):1557-1564.
    [127]李书舟,刘斌.脉冲控制在励磁电力系统中的应用研究[J].湖南工业大学学报, 2007.21(2):88-91

© 2004-2018 中国地质图书馆版权所有 京ICP备05064691号 京公网安备11010802017129号

地址:北京市海淀区学院路29号 邮编:100083

电话:办公室:(+86 10)66554848;文献借阅、咨询服务、科技查新:66554700