基于混合仿真平台的智能变结构控制及其应用研究
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摘要
变结构控制本质上是一类特殊的非线性控制,其非线性表现为控制的不连续性,这种控制策略与其它控制的不同之处在于系统的“结构”并不固定,而是可以在动态过程中根据系统当前的状态(如偏差及其各阶导数等)有目的地不断变化,迫使系统按照预定“滑动模态”的状态轨迹运动。由于滑动模态可以进行设计且与对象参数及扰动无关,这就使得变结构控制具有快速响应、对参数变化及扰动不灵敏、无需系统在线辩识,物理实现简单等优点,越来越受到研究人员的关注。
本文针对工业控制过程中的实际问题,对变结构控制进行了深入的研究,并结合智能控制算法,提出了两种新的变结构控制方法。第一是针对时滞系统的滞后特性,设计了特殊的线性变换,使时滞系统变成无时滞系统,并用RBF神经网络设计了控制算法;第二是使用智能控制结合多模变结构控制设计了多变量的变结构控制。本文共分六章,主要内容和结论如下:
第一章系统地回顾了变结构控制的发展概况、研究现状。
第二章详细介绍了混合仿真平台的原理与实现过程。介绍了混合仿真平台的系统配置、RTW下实时代码生成的过程、RTWT实时内核的功能及其对数据采集卡的支持,以及如何使用RTW进行实时仿真。
第三章介绍了变结构算法的基本原理与设计方法,以及离散时间系统的滑模控制。并有针对性的使用了三种方法设计了滑模控制器。
第四章介绍了两种基于智能控制的滑模变结构控制算法。针对离散系统和滑模控制在实现过程中所必须要克服的抖振问题。然后结合模糊控制设计滑模控制器,在保证良好控制效果的基础上,有效地削弱了抖振。最后,给出了针对时滞系统的一种RBFNN滑模控制实现,在半实物仿真平台上显示出了良好的性能
第五章结合智能控制算法,通过对系统进行辨识设计了带有时序逻辑,误差反馈目标优化和模糊监督控制器的多模变结构控制器。通过在仿真平台上的仿真试验验证,算法充分考虑到系统对快速型和稳定性的要求,满足了稳态和暂态多个性能指标,仿真效果优异。
第六章给出了本文的主要结论及创新点,并提出了进一步研究的问题和方向。
Variable structure control is a kind of special nonlinear control in its essence, its nonlinear behave is presented in the discontinuity of the control value. The distinctive difference between this kind of control algorithm and other traditional control algorithm is that the structure of controller is not fixed but variable, which could exchanges on propose all the times by the current status of the system in a dynamic process (as the error and its differential coefficient) to force the system moving into the estimated“sliding mode”surface.
According to the implement of the algorithm in the real industry control, we did a lot of researches about variable structure control based on intelligence control algorithm, and presented two kind of now variable structure control method. The first one is based on time delay system, a special linear exchange is designed for a RBFNN sliding mode control; the other is a variable sliding mode control with intelligence algorithm. There are six chapters in this paper, and the main contents and conclusions are summarized as follows:
The first chapter is completely reviews the development, present state and perspectives of intelligent variable structure control. In chapter 2, the implementation and principle of mixed simulation platform are introduced in detail. A simulation platform based on PC for designing and testing virtual controller is constructed, which successfully realizes real-time control with a PC under the windows. In chapter 3, the main characteristics and the design methods of variable structure algorithm is introduced for linear system and discrete system. In chapter 4, two kinds of intelligent sliding mode variable structure control algorithm is presented. First, a fuzzy sliding mode controller is structured to reducing the chattering of the discrete system and sliding mode control. Second, a RBFNN sliding mode controller with special linear transformation is presented for a kind of time delay nonlinear system. In chapter 5, integrating with the intelligent control, variable sliding mode controller with time change order and fuzzy supervisor is presented for a kind of long time delay of input and state. In last chaper, the conclusion of the thesis, the future work and research are presented.
本文针对工业控制过程中的实际问题,对变结构控制进行了深入的研究,并结合智能控制算法,提出了两种新的变结构控制方法。第一是针对时滞系统的滞后特性,设计了特殊的线性变换,使时滞系统变成无时滞系统,并用RBF神经网络设计了控制算法;第二是使用智能控制结合多模变结构控制设计了多变量的变结构控制。本文共分六章,主要内容和结论如下:
第一章系统地回顾了变结构控制的发展概况、研究现状。
第二章详细介绍了混合仿真平台的原理与实现过程。介绍了混合仿真平台的系统配置、RTW下实时代码生成的过程、RTWT实时内核的功能及其对数据采集卡的支持,以及如何使用RTW进行实时仿真。
第三章介绍了变结构算法的基本原理与设计方法,以及离散时间系统的滑模控制。并有针对性的使用了三种方法设计了滑模控制器。
第四章介绍了两种基于智能控制的滑模变结构控制算法。针对离散系统和滑模控制在实现过程中所必须要克服的抖振问题。然后结合模糊控制设计滑模控制器,在保证良好控制效果的基础上,有效地削弱了抖振。最后,给出了针对时滞系统的一种RBFNN滑模控制实现,在半实物仿真平台上显示出了良好的性能
第五章结合智能控制算法,通过对系统进行辨识设计了带有时序逻辑,误差反馈目标优化和模糊监督控制器的多模变结构控制器。通过在仿真平台上的仿真试验验证,算法充分考虑到系统对快速型和稳定性的要求,满足了稳态和暂态多个性能指标,仿真效果优异。
第六章给出了本文的主要结论及创新点,并提出了进一步研究的问题和方向。
Variable structure control is a kind of special nonlinear control in its essence, its nonlinear behave is presented in the discontinuity of the control value. The distinctive difference between this kind of control algorithm and other traditional control algorithm is that the structure of controller is not fixed but variable, which could exchanges on propose all the times by the current status of the system in a dynamic process (as the error and its differential coefficient) to force the system moving into the estimated“sliding mode”surface.
According to the implement of the algorithm in the real industry control, we did a lot of researches about variable structure control based on intelligence control algorithm, and presented two kind of now variable structure control method. The first one is based on time delay system, a special linear exchange is designed for a RBFNN sliding mode control; the other is a variable sliding mode control with intelligence algorithm. There are six chapters in this paper, and the main contents and conclusions are summarized as follows:
The first chapter is completely reviews the development, present state and perspectives of intelligent variable structure control. In chapter 2, the implementation and principle of mixed simulation platform are introduced in detail. A simulation platform based on PC for designing and testing virtual controller is constructed, which successfully realizes real-time control with a PC under the windows. In chapter 3, the main characteristics and the design methods of variable structure algorithm is introduced for linear system and discrete system. In chapter 4, two kinds of intelligent sliding mode variable structure control algorithm is presented. First, a fuzzy sliding mode controller is structured to reducing the chattering of the discrete system and sliding mode control. Second, a RBFNN sliding mode controller with special linear transformation is presented for a kind of time delay nonlinear system. In chapter 5, integrating with the intelligent control, variable sliding mode controller with time change order and fuzzy supervisor is presented for a kind of long time delay of input and state. In last chaper, the conclusion of the thesis, the future work and research are presented.
引文
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[2] Yu X H , Xu J X.Advances in variable structure systems:analysis , integrations and applications.Proceedings 6 th .IEEE International workshop on variable structure systems,Australia,World Scientific,11,2000
[3] 高为炳.《变结构控制的理论及设计方法》.中国科学技术出版社,1998:98~103
[4] V.T.Utkin.Variable Structure Systems with Sliding Modes,IEEE Trans.Automatic Control,1977,22:212~222
[5] K.K.Shyu and J.J Yan.Variable Structure Model Following Adaptive Control for Systems with Time-varying Delay.Control Theory Adv.Technol,1994,10(3):513~521
[6] P.L.Liu and T.J.Su.Robust Stability of Interval Time-delay Systems with Delay-dependence.Systems Control Lett,1998,33:231~2396
[7] M.S.Yang.,P.Liu.and Lu H.C.Output Feedback Stabilization of Uncertain Dynamic Systems with Multiple State Delays Via Sliding Mode Control Strategy. Proceedings of the IEEE International Symposium on Industrial Electronics,1999,3:1147~1152
[8] H.H.Choi.A New Method for Variable Structure Control System Design.A linear matrix inequality approach.Automatica,1997,33(11):2089~2092
[9] M.L.Chan,C.W.Tao and T.T.Lee.Sliding Mode Controller for Linear Systems with Mismatched Time-varying Uncertainties.Journal of Franklin Institute,2000,337:105~115
[10] C.H.Chou and C.C.Cheng.Design of Adaptive Variable Structure Controllers for Perturbed Time-varying State Delay Systems.Journal of Franklin Institute,2001,338:35~46
[11] J.B Hu.J.Chu and Su H.Y.SMVSC for a Class of Time-delay Uncertain Systems with Mismatching Uncertainties.IEEE Proceeding–Control Theory and Applications,2000,147(6):687~693
[12] LIN S C, CHEN Y Y. RBF network based sliding mode control[C] // IEEE Int Conf on Systems, Man, and Cybernetics. San Antonio, USA : IEEE Press, 1994, 10: 1957 – 1961.
[13] MUNOZ D, D.SBARBARO D. An adaptive sliding-mode controller for discrete nonlinear systems[J]. IEEE Trans on Industrial Electronics, 2000, 47(3): 574 – 581.
[14] MAN Z H, YU X H, ESHRAGHIAN K, PALANISWAMI M. A robust adaptive sliding mode tracking control using an RBF neural network for robotic manipulators[C] // IEEE Int Conf on Neural Networks. Perth, Australia: IEEE Press, 1995, 11: 2403 – 2408.
[15] CARRASCO J M, QUERO J M,RIDAO F P,PERALES M A, FRANQUELO. Sliding mode control of a DC/DC PWM converter with PFC implemented by neural networks[J]. IEEE Trans on Circuits and Systems-I: Fundamental Theory and Applications, 1997, 44(8): 743 – 749.
[16] PARMA G G, MENEZES B R, BRAGA A P, COSTA M A. Sliding mode neural network control of an induction motor drive[J]. Int J of Adaptive Control and Signal Processing, 2003, 17(6): 501 – 508.
[17] Lin C M,MONY J. Decoupling control by hierarchial fuzzy sliding mode controller[J]. IEEE Trans on Control Systems Technology,2005, 13(4): 593 – 598.
[18] KIM S W, LEE J J. Design of a fuzzy controller with fuzzy sliding surface[J]. Fuzzy Sets and Systems, 1995, 71(3): 359 – 367.
[19] YOO B, HAMW. Adaptive fuzzy sliding mode control of nonlinear system[J]. IEEE Trans on Fuzzy Systems, 1998, 6(2): 315 – 321.
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[22] WAI R J, LIN C M, HSU C F. Adaptive fuzzy sliding-mode control for electrical servo drive[J]. Fuzzy Sets and Systems, 2004, 143(2): 295 – 310.
[23] CHEN J Y. Expert SMC-based fuzzy control with genetic algorithms[J]. J of the Franklin Institute, 1999, 336(4): 589 – 610.
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[28] SHTESSEL Y B, ZINOBER A S I, SHKOLNIKOV I A. Sliding mode control for nonlinear systems with output delay via method of stable center[J]. J of Dynamic Systems, Measurement, and Control, 2003, 125: 158 – 165.
[29] 胡跃明, 周其节. 带有滞后影响的控制系统的变结构控制[J].自动化学报, 1991, 17(5): 587 – 591.(HU Yueming, ZHOU Qijie. Variable structure control for a control system with time-delay[J]. Acta Automatica Sinica, 1991, 17(5):587 – 591.)
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[31] 高存臣, 袁付顺, 肖会敏. 时滞变结构控制系统[M]. 北京: 科学出版社, 2004.
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[36] 杨涤.系统实时仿真开发环境与应用.北京:清华大学出版社,2002
[37] 王宁强,刘向东,陈振.基于 MATLAB 的卫星姿态控制半物理实时仿真平台.系统仿真学报,2005,17(7):1617～1620
[38] MathWorks.The Real-Time Windows Target User’s Guide. Version 2.5.1,2004
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[40] 张建灵,安锦文,王米娜.基于 Simulink 和 C/C++混合编成的模糊控制系统仿真.系统仿真学报,2004,16(12): 2774～2776
[41] Utkin V I.Variable structure system with sliding modes.IEEE Transactions on Automatic and Control,1979,22(2):212-222
[42] 刘金琨,滑模变结构控制 MATLAB 仿真,清华大学出版社,2005
[43] Chyi-Tsong Chen *, Shih-Tien Peng. Design of a sliding mode control system for chemical processes. Journal of process control. 15 (2005) 515–530
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[2] Yu X H , Xu J X.Advances in variable structure systems:analysis , integrations and applications.Proceedings 6 th .IEEE International workshop on variable structure systems,Australia,World Scientific,11,2000
[3] 高为炳.《变结构控制的理论及设计方法》.中国科学技术出版社,1998:98~103
[4] V.T.Utkin.Variable Structure Systems with Sliding Modes,IEEE Trans.Automatic Control,1977,22:212~222
[5] K.K.Shyu and J.J Yan.Variable Structure Model Following Adaptive Control for Systems with Time-varying Delay.Control Theory Adv.Technol,1994,10(3):513~521
[6] P.L.Liu and T.J.Su.Robust Stability of Interval Time-delay Systems with Delay-dependence.Systems Control Lett,1998,33:231~2396
[7] M.S.Yang.,P.Liu.and Lu H.C.Output Feedback Stabilization of Uncertain Dynamic Systems with Multiple State Delays Via Sliding Mode Control Strategy. Proceedings of the IEEE International Symposium on Industrial Electronics,1999,3:1147~1152
[8] H.H.Choi.A New Method for Variable Structure Control System Design.A linear matrix inequality approach.Automatica,1997,33(11):2089~2092
[9] M.L.Chan,C.W.Tao and T.T.Lee.Sliding Mode Controller for Linear Systems with Mismatched Time-varying Uncertainties.Journal of Franklin Institute,2000,337:105~115
[10] C.H.Chou and C.C.Cheng.Design of Adaptive Variable Structure Controllers for Perturbed Time-varying State Delay Systems.Journal of Franklin Institute,2001,338:35~46
[11] J.B Hu.J.Chu and Su H.Y.SMVSC for a Class of Time-delay Uncertain Systems with Mismatching Uncertainties.IEEE Proceeding–Control Theory and Applications,2000,147(6):687~693
[12] LIN S C, CHEN Y Y. RBF network based sliding mode control[C] // IEEE Int Conf on Systems, Man, and Cybernetics. San Antonio, USA : IEEE Press, 1994, 10: 1957 – 1961.
[13] MUNOZ D, D.SBARBARO D. An adaptive sliding-mode controller for discrete nonlinear systems[J]. IEEE Trans on Industrial Electronics, 2000, 47(3): 574 – 581.
[14] MAN Z H, YU X H, ESHRAGHIAN K, PALANISWAMI M. A robust adaptive sliding mode tracking control using an RBF neural network for robotic manipulators[C] // IEEE Int Conf on Neural Networks. Perth, Australia: IEEE Press, 1995, 11: 2403 – 2408.
[15] CARRASCO J M, QUERO J M,RIDAO F P,PERALES M A, FRANQUELO. Sliding mode control of a DC/DC PWM converter with PFC implemented by neural networks[J]. IEEE Trans on Circuits and Systems-I: Fundamental Theory and Applications, 1997, 44(8): 743 – 749.
[16] PARMA G G, MENEZES B R, BRAGA A P, COSTA M A. Sliding mode neural network control of an induction motor drive[J]. Int J of Adaptive Control and Signal Processing, 2003, 17(6): 501 – 508.
[17] Lin C M,MONY J. Decoupling control by hierarchial fuzzy sliding mode controller[J]. IEEE Trans on Control Systems Technology,2005, 13(4): 593 – 598.
[18] KIM S W, LEE J J. Design of a fuzzy controller with fuzzy sliding surface[J]. Fuzzy Sets and Systems, 1995, 71(3): 359 – 367.
[19] YOO B, HAMW. Adaptive fuzzy sliding mode control of nonlinear system[J]. IEEE Trans on Fuzzy Systems, 1998, 6(2): 315 – 321.
[20] LU Y S, CHEN J S. A self-organizing fuzzy sliding-mode controller design for a class of nonlinear servo systems[J]. IEEE Trans on Industrial Electronics, 1994, 41(5): 492 – 502.
[21] LIANG C Y, SU J P. A new approach to the design of a fuzzy sliding mode controller[J]. Fuzzy Sets and Systems, 2003, 139(1): 111– 124.
[22] WAI R J, LIN C M, HSU C F. Adaptive fuzzy sliding-mode control for electrical servo drive[J]. Fuzzy Sets and Systems, 2004, 143(2): 295 – 310.
[23] CHEN J Y. Expert SMC-based fuzzy control with genetic algorithms[J]. J of the Franklin Institute, 1999, 336(4): 589 – 610.
[24] LABIOD S, BOUCHERIT M S, GUERRA T M. Adaptive fuzzy control of a class of MIMO nonlinear systems[J]. Fuzzy Sets and Systems, 2005, 151(1): 59 – 77.
[25] GOUAISBAUT F, PERRUQETTI W, RICHARD J P. A sliding mode control for linear systems with input and state delays[C] Proc of the 38th IEEE Conf on Decision and Control. Phoenix, USA,1999, 12: 4234 – 4239.
[26] CHOU C H, CHENG C C. Decentralized mode following variable structure control for perturbed large scale systems with time-delay interconnections[C] // Proc of American Control Conf. Chicago: IEEE Press, 2000, 6: 641 – 645.
[27] XIA Y Q, JIA Y M. Robust sliding-mode control for uncertain time delay systems: a LMI approach[J]. IEEE Trans on Automatic Control, 2003, 48(6): 1086 – 1091.
[28] SHTESSEL Y B, ZINOBER A S I, SHKOLNIKOV I A. Sliding mode control for nonlinear systems with output delay via method of stable center[J]. J of Dynamic Systems, Measurement, and Control, 2003, 125: 158 – 165.
[29] 胡跃明, 周其节. 带有滞后影响的控制系统的变结构控制[J].自动化学报, 1991, 17(5): 587 – 591.(HU Yueming, ZHOU Qijie. Variable structure control for a control system with time-delay[J]. Acta Automatica Sinica, 1991, 17(5):587 – 591.)
[30] 郑锋, 程勉, 高为炳, 一类时滞系统的变结构控制[J]. 自动化学报, 1995, 21(2):221 – 225.(ZHENG Feng, CHENG Mian, GAO Weibing. Variable structure control of a class of time-delay system[J]. Acta Automatica Sinica,1995, 21(2): 221 – 225.)
[31] 高存臣, 袁付顺, 肖会敏. 时滞变结构控制系统[M]. 北京: 科学出版社, 2004.
[32] MathWorks.Matlab User’s Guide.2002
[33] MathWorks.Simulink 6.0 User’s Guide.Release 14,2004
[34] MathWorks.The Real-Time Workshop User’s Manual. Version 6.1,2004
[35] 薛定宇,陈阳泉.基于 MATLAB/Simulink 的系统仿真技术与应用.北京:清华大学出版社,2002
[36] 杨涤.系统实时仿真开发环境与应用.北京:清华大学出版社,2002
[37] 王宁强,刘向东,陈振.基于 MATLAB 的卫星姿态控制半物理实时仿真平台.系统仿真学报,2005,17(7):1617～1620
[38] MathWorks.The Real-Time Windows Target User’s Guide. Version 2.5.1,2004
[39] 余昌盛,许力.基于 MATLAB 的复杂非线性控制实验系统实时控制研究.实验室研究与探索,2005,24(4):14～18
[40] 张建灵,安锦文,王米娜.基于 Simulink 和 C/C++混合编成的模糊控制系统仿真.系统仿真学报,2004,16(12): 2774～2776
[41] Utkin V I.Variable structure system with sliding modes.IEEE Transactions on Automatic and Control,1979,22(2):212-222
[42] 刘金琨,滑模变结构控制 MATLAB 仿真,清华大学出版社,2005
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