轧机电液伺服系统的鲁棒自适应输出反馈控制研究
|
摘要
对于电液伺服系统的高精度控制问题，目前已经取得了较为丰富的研究成果，然而，这些成果绝大部分是在假设所有状态可测量的情况下，采用状态反馈取得的，输出反馈的成果却很少。在电液伺服系统的许多应用场合都存在不可测状态，如柱塞速度信号、加速度信号，因此，研究电液伺服系统的输出反馈控制是非常必要的。本课题结合河北省自然科学基金“液压伺服驱动的冷带轧机厚控系统自适应鲁棒控制研究”和国家自然科学基金“考虑输入受限的轧机液压伺服系统多模型切换自适应控制研究”，以轧机电液伺服系统为研究对象，针对系统中普遍存在的状态不可测、参数不确定、非线性、外负载力未知、输入饱和，以及轧机厚控系统存在的测量延时等问题进行了鲁棒自适应输出反馈控制方面的研究。本文主要做了以下几方面工作：
首先，针对轧机电液伺服位置系统中存在不确定参数和未知外负载力，提出了一种基于未知输入降维观测器的鲁棒输出反馈控制算法。将包含未知外负载力的干扰项视为系统的未知输入，构造未知输入降维观测器用于估计系统的不可测状态和未知干扰项，进而，基于所得到的估计值设计输出反馈控制器。与传统的输出反馈控制算法相比较，本文提出的算法具有更好的暂态性能和更小的稳态误差。
其次，针对轧机电液伺服位置系统中存在不确定参数，在假设不确定参数上界已知的情况下，提出了一种基于高增益观测器和参数估计器的自适应输出反馈控制算法。通过选取适当的设计参数，该算法能够保证闭环系统的所有信号最终有界，系统状态及其估计值最终收敛到原点的一个由高增益决定的邻域内；对于不确定参数上界未知的情况，并考虑一些未建模动态，可将电液伺服位置系统视为具有未知控制系数和未知线性增长率的非线性系统。对这样一类系统，提出了一种基于动态高增益观测器的自适应输出反馈控制算法。在该算法中，利用线性组合变换，使得变换后的广义误差的动态不再依赖于控制输入，以便于输出反馈控制器设计；通过引入动态高增益，解决了系统线性增长率未知的问题。该算法能够保证闭环系统所有信号有界，且系统状态和估计误差最终收敛到零。进而，将该算法应用到电液伺服位置系统中，并通过实例仿真验证了该算法的有效性。
第三，考虑到轧机电液伺服位置系统中存在的输入饱和，给出了一种抗饱和鲁棒动态输出反馈控制算法。首先在不考虑输入饱和情况下设计鲁棒动态输出反馈控制器，利用Finsler引理将保证闭环系统稳定的充分条件转化为线性矩阵不等式(LMI)条件，通过求解LMI可得到控制器参数矩阵。然后基于anti-windup方法设计了抗饱和鲁棒动态输出反馈控制器。所设计的控制器能够保证闭环系统有界稳定，并具有鲁棒H∞性能。
最后，考虑到轧机厚控系统的输出测量存在延时，给出了一种基于观测器的输出反馈鲁棒预测控制算法。首先，将具有测量延时的厚控系统变换为无输出测量延时的系统，再基于变换后的系统构造观测器重构系统状态，然后，基于状态估计设计鲁棒预测控制器。为减小在线计算负担，采用了离线、在线相结合的算法，最后通过实例仿真验证了所提出控制算法的有效性。
The problem of high accuracy hydraulic servo control was investigated quiteintensively in recent years, especially for state feedback control under the assumptionthat all the states are measurable. However, these studies do not provide much attentionto output feedback control. In most cases, there exists unmeasurable state in theelectro-hydraulic servo system (EHSS), such as the speed and acceleration of plunger.Therefore, the research on output feedback control for EHSS is very necessary. Thisresearch originates from the project of National Natural Science Foundation (NNSF) ofHebei Province “Research on adaptive robust control for cold-strip rolling mill AGCsystem driven by EHSS” and NNSF of China “Research on multi-model switch adaptivecontrol for EHSS of rolling mill with input saturation”. Focusing on the EHSS of rollingmill, this thesis concerns the development of robust adaptive output-feedback control forthe EHSS with unmeasurable state, uncertain parameters, nonlinearities, unknownexternal load force, input saturation, and delayed measurement. The main contents of thisthesis are as follows:
First, focusing on the uncertain parameters and unknown load force in EHSSposition control of rolling mill, a reduced-order unknown input observer based robustoutput-feedback control (UIOROFC) algorithm is proposed. A reduced-order unknowninput observer is first constructed to estimate unmeasurable state and unknownperturbation, in which the perturbation containing unknown external force is regarded asan unknown input. Then, a robust output feedback controller is developed. In comparisonwith traditional observer based robust output-feedback controller (OROFC), the proposedUIOROFC algorithm has better transient performance and smaller steady state error.
Second, a high gain observer (HGO) and parameter estimator based adaptive outputfeedback control algorithm is proposed for the EHSS of rolling mill with the assumptionthat the upper bounds of uncertain parameters are known. By choosing the appropriatehigh gain and design parameters, the proposed algorithm can guarantee that all signals ofthe closed loop system are ultimately bounded, the system state and its estimation error converge to a neighbourhood determined by the high gain of the origin. On the otherhand, if the upper bounds of the uncertain parameters are unknown, the EHSS can beregarded as an uncertain nonlinear system with unknown control coefficient andunknown linear growth rate. A dynamic HGO based adaptive output feedback controlalgorithm is proposed for this class of systems. By means of a linear combination, thedynamics of the resulting generalized error does not depend on the control input, and byintroducing a dynamic high gain, the unknown linear growth rate as a difficult issue issolved. It can be proved that all the signals of the closed-loop system are bounded, andthe system state and estimation errors ultimately converge to zero. Moreover, theproposed controller is applied to the EHSS, the effectiveness of the algorithm is validatedby example simulations.
Third, an anti-windup robust dynamic output feedback (DOF) control algorithm isproposed to solve the input saturation problem in EHSS. Without consideration of inputsaturation, a robust DOF controller is first designed for a class of uncertain nonlinearsystems. By using Finsler’s lemma, a sufficient condition of stability of the closed-loopsystem is transferred into a linear matrix inequality (LMI) condition, and the controllerparameter matrices are obtained by solving the LMI. Then, a static anti-saturation robustDOF controller, based on anti-windup method, is designed. It can be proved that theclosed-loop is robust stable and has robust H∞performance.
Finally, an observer based output-feedback robust predictive control algorithm isproposed to solve the delayed output measurement problem in hydraulic automatic gaugecontrol (HAGC) of rolling mill. Through proper transformation, a system withoutdelayed output measurement is obtained, and an observer is constructed to reconstruct thesystem state. Then, a robust predictive controller via output-feedback is developed. Toreduce on-line computational burden, an off/on-line algorithm is adopted. Theeffectiveness of the proposed algorithm is validated by simulations.
首先，针对轧机电液伺服位置系统中存在不确定参数和未知外负载力，提出了一种基于未知输入降维观测器的鲁棒输出反馈控制算法。将包含未知外负载力的干扰项视为系统的未知输入，构造未知输入降维观测器用于估计系统的不可测状态和未知干扰项，进而，基于所得到的估计值设计输出反馈控制器。与传统的输出反馈控制算法相比较，本文提出的算法具有更好的暂态性能和更小的稳态误差。
其次，针对轧机电液伺服位置系统中存在不确定参数，在假设不确定参数上界已知的情况下，提出了一种基于高增益观测器和参数估计器的自适应输出反馈控制算法。通过选取适当的设计参数，该算法能够保证闭环系统的所有信号最终有界，系统状态及其估计值最终收敛到原点的一个由高增益决定的邻域内；对于不确定参数上界未知的情况，并考虑一些未建模动态，可将电液伺服位置系统视为具有未知控制系数和未知线性增长率的非线性系统。对这样一类系统，提出了一种基于动态高增益观测器的自适应输出反馈控制算法。在该算法中，利用线性组合变换，使得变换后的广义误差的动态不再依赖于控制输入，以便于输出反馈控制器设计；通过引入动态高增益，解决了系统线性增长率未知的问题。该算法能够保证闭环系统所有信号有界，且系统状态和估计误差最终收敛到零。进而，将该算法应用到电液伺服位置系统中，并通过实例仿真验证了该算法的有效性。
第三，考虑到轧机电液伺服位置系统中存在的输入饱和，给出了一种抗饱和鲁棒动态输出反馈控制算法。首先在不考虑输入饱和情况下设计鲁棒动态输出反馈控制器，利用Finsler引理将保证闭环系统稳定的充分条件转化为线性矩阵不等式(LMI)条件，通过求解LMI可得到控制器参数矩阵。然后基于anti-windup方法设计了抗饱和鲁棒动态输出反馈控制器。所设计的控制器能够保证闭环系统有界稳定，并具有鲁棒H∞性能。
最后，考虑到轧机厚控系统的输出测量存在延时，给出了一种基于观测器的输出反馈鲁棒预测控制算法。首先，将具有测量延时的厚控系统变换为无输出测量延时的系统，再基于变换后的系统构造观测器重构系统状态，然后，基于状态估计设计鲁棒预测控制器。为减小在线计算负担，采用了离线、在线相结合的算法，最后通过实例仿真验证了所提出控制算法的有效性。
The problem of high accuracy hydraulic servo control was investigated quiteintensively in recent years, especially for state feedback control under the assumptionthat all the states are measurable. However, these studies do not provide much attentionto output feedback control. In most cases, there exists unmeasurable state in theelectro-hydraulic servo system (EHSS), such as the speed and acceleration of plunger.Therefore, the research on output feedback control for EHSS is very necessary. Thisresearch originates from the project of National Natural Science Foundation (NNSF) ofHebei Province “Research on adaptive robust control for cold-strip rolling mill AGCsystem driven by EHSS” and NNSF of China “Research on multi-model switch adaptivecontrol for EHSS of rolling mill with input saturation”. Focusing on the EHSS of rollingmill, this thesis concerns the development of robust adaptive output-feedback control forthe EHSS with unmeasurable state, uncertain parameters, nonlinearities, unknownexternal load force, input saturation, and delayed measurement. The main contents of thisthesis are as follows:
First, focusing on the uncertain parameters and unknown load force in EHSSposition control of rolling mill, a reduced-order unknown input observer based robustoutput-feedback control (UIOROFC) algorithm is proposed. A reduced-order unknowninput observer is first constructed to estimate unmeasurable state and unknownperturbation, in which the perturbation containing unknown external force is regarded asan unknown input. Then, a robust output feedback controller is developed. In comparisonwith traditional observer based robust output-feedback controller (OROFC), the proposedUIOROFC algorithm has better transient performance and smaller steady state error.
Second, a high gain observer (HGO) and parameter estimator based adaptive outputfeedback control algorithm is proposed for the EHSS of rolling mill with the assumptionthat the upper bounds of uncertain parameters are known. By choosing the appropriatehigh gain and design parameters, the proposed algorithm can guarantee that all signals ofthe closed loop system are ultimately bounded, the system state and its estimation error converge to a neighbourhood determined by the high gain of the origin. On the otherhand, if the upper bounds of the uncertain parameters are unknown, the EHSS can beregarded as an uncertain nonlinear system with unknown control coefficient andunknown linear growth rate. A dynamic HGO based adaptive output feedback controlalgorithm is proposed for this class of systems. By means of a linear combination, thedynamics of the resulting generalized error does not depend on the control input, and byintroducing a dynamic high gain, the unknown linear growth rate as a difficult issue issolved. It can be proved that all the signals of the closed-loop system are bounded, andthe system state and estimation errors ultimately converge to zero. Moreover, theproposed controller is applied to the EHSS, the effectiveness of the algorithm is validatedby example simulations.
Third, an anti-windup robust dynamic output feedback (DOF) control algorithm isproposed to solve the input saturation problem in EHSS. Without consideration of inputsaturation, a robust DOF controller is first designed for a class of uncertain nonlinearsystems. By using Finsler’s lemma, a sufficient condition of stability of the closed-loopsystem is transferred into a linear matrix inequality (LMI) condition, and the controllerparameter matrices are obtained by solving the LMI. Then, a static anti-saturation robustDOF controller, based on anti-windup method, is designed. It can be proved that theclosed-loop is robust stable and has robust H∞performance.
Finally, an observer based output-feedback robust predictive control algorithm isproposed to solve the delayed output measurement problem in hydraulic automatic gaugecontrol (HAGC) of rolling mill. Through proper transformation, a system withoutdelayed output measurement is obtained, and an observer is constructed to reconstruct thesystem state. Then, a robust predictive controller via output-feedback is developed. Toreduce on-line computational burden, an off/on-line algorithm is adopted. Theeffectiveness of the proposed algorithm is validated by simulations.
引文
1慕春棣,梅生伟,申铁龙.非线性系统鲁棒控制理论的一些新进展[J].控制理论与应用,2001,18(1):1-9.
2俞立.鲁棒控制:线性矩阵不等式处理方法[M].北京:清华大学出版社,2002:1-20.
3Merritt H E. Hydraulic Control Systems[M]. New York: John Wiley and Sons,1967.
4路甬祥.流体传动与控制技术的历史进展与展望[J].机械工程学报,2001,37(10):1-10.
5连家创,刘宏民.板厚板形控制[M].北京:兵器工业出版社,1996:137,173-184.
6王占林.近代液压控制[M].北京:机械工业出版社,1997:1-16.
7Liu G P, Daley S. Optimal-Tuning Nonlinear PID Control of Hydraulic Systems[J]. ControlEngineering Practice2000,8(9):1045-1053.
8吴振顺,姚建均,岳东海.模糊自整定PID控制器的设计及其应用[J].哈尔滨工业大学学报,2004,36(11):1578-1582.
9邹俊,傅新,杨华勇,等.自适应交互PID在液压伺服系统中的应用[J].机械工程学报,2006,42(11):179-184.
10王益群,王海芳,高英杰,等.基于神经网络PID的轧机AGC力控制[J].中国机械工程,2005,16(18):1650-1654.
11Karam M E, Jiao Z X, Zhang H Q. PID Controller Optimization by GA and Its Performances onthe Electro-Hydraulic Servo Control System[J]. Chinese Journal of Aeronautics,2008,21(4):378-384.
12姜万录,刘伟,张瑞娟,等.基于蚁群优化的神经网络智能PID控制策略研究[J].机床与液压,2010,38(13):22-26.
13Hsia T C. A New Technique for Robust Control of Servo System[J]. IEEE Transactions onIndustrial Electronics,1989,36(1):1-7.
14Jen Y, Lee C. Robust Speed Control of a Pump-Controlled Motor System[J]. IEEE Proceeding D.Control Theory and Applications,1992,139(6):503-510.
15方一鸣,嵇胜龙,卜劭华,等.液压伺服驱动位置控制系统的鲁棒性能设计[J].系统仿真学报,2002,14(4):467-469.
16胡广平,陈乃超.基于H2H∞控制的液压伺服系统鲁棒性设计[J].机床与液压,2007,35(2):125-128.
17Mili V, itum, Essert M. Robust H∞Position Control Synthesis of an Electro-HydraulicServo System[J]. ISA Transactions,2010,49(4):535-542.
18段锁林,魏聪梅,安高成,等.不确定性电液伺服位置系统的滑模鲁棒跟踪控制[J].太原重型机械学院学报,2001,22(2):89-93.
19王本永,董彦良,赵克定.高精度液压仿真转台鲁棒控制[J].航空学报,2007,28(5):1252-1258.
20Yu H, Feng Z J, Wang X Y. Nonlinear Control for a Class of Hydraulic Servo System[J]. Journalof Zhejiang University: Science,2004,5(11):1413-1417.
21Niksefat N, Sepehri N. Design and Experimental Evaluation of a Robust Force Controller for anElectro-Hydraulic Actuator via Quantitative Feedback Theory[J]. Control Engineering Practice,2000,8(12):1335-1345.
22富强,尔联洁,赵国荣.基于定量反馈理论的飞行仿真转台鲁棒控制[J].北京航空航天大学学报,2004,30(5):410-413.
23Ahn K K, Dinh Q T. Self-Tuning of Quantitative Feedback Theory for Force Control of anElectro-Hydraulic Test Machine[J]. Control Engineering Practice,2009,17(11):1291-1306.
24王增会,陈增强,孙青林,等.定量反馈理论发展综述[J].控制理论与应用,2006,23(3):404-411.
25吴士昌,吴忠强.自适应控制[M].第2版.北京:机械工业出版社,2005:3-8.
26管成.非线性系统的滑模自适应控制及其在电液控制系统中的应用[D].杭州:浙江大学博士论文,2005:5-9,51-79.
27张友旺.电液伺服系统的动态递归模糊神经网络辨识与鲁棒控制研究[D].长沙:中南大学博士学位论文,2006:3-13.
28焦晓红,耿秋实,方一鸣,等.液压伺服并联机器人的自适应鲁棒跟踪控制[J].系统仿真学报,2003,15(3):401-404.
29Alleyne A, Hedrick J K. Nonlinear Adaptive Control of Active Suspension[J]. IEEETransactions on Control Systems Technology,1995,3(1):94-101.
30Alleyne A. Nonlinear Force Control of an Electro-Hydraulic Actuator[C]. Proceedings of theJapan/USA Symposium on Flexible Automation, Boston, USA: ASME&ISCIE,1996,193-200.
31Yao B, Chiu G T C, Reedy J T. Nonlinear Adaptive Robust Control of One-Dof Electro-Hydraulic Servo Systems[C]. Proceedings of the ASME International Mechanical EngineeringCongress and Exposition (IMECE’97), Dallas, TX, USA: ASME,1997,4:191-197.
32Yao B, Bu F P, Reedy J, et al. Adaptive Robust Motion Control of Single-Rod HydraulicActuators: Theory and Experiments[J]. IEEE/ASME Transactions on Mechatronics,2000,5(1):79-92.
33Yao B, Tomizuka M. Adaptive Robust Control of MIMO Nonlinear Systems in Semi-StrictFeedback Forms[J]. Automatica,2001,37(9):1305-1321.
34Yao B, Bu F P, Chiu G T C. Non-linear Adaptive Robust Control of Electro-Hydraulic SystemsDriven by Double-Rod Acturators[J]. International Journal of Control,2001,74(8):761-775.
35Hua C X, Yao, B, Wang Q F. Integrated Direct/Indirect Adaptive Robust Contouring Control ofa Biaxial Gantry with Accurate Parameter Estimations[J]. Automatica,2010,46(4):701-707.
36Mohanty A, Yao B. Indirect Adaptive Robust Control of Hydraulic Manipulators with AccurateParameter Estimates[J]. IEEE Transactions on Control Systems Technology,2011,19(3):567-575.
37Choux M, Karimi H R, Hovland G, et al. Robust Adaptive Backstepping Control Design for aNonlinear Hydraulic-Mechanical System[C]. Proceedings of the Joint48th IEEE Conference onDecision and Control and28th Chinese Control Conference, Shanghai, China: IEEE&CAA,2009:2460-2467.
38方一鸣,王志杰,谢云鹏,等.轧机液压伺服位置系统多模型切换滑模变结构控制[J].电机与控制学报,2010,14(5):91-97.
39Guan C, Zhu S A. Adaptive Time-Varying Sliding Mode Control for Hydraulic Servo System[C].Proceedings of the8th International Conference on Control, Automation, Robotics and Vision(ICARCV2004), Kunming, China: IEEE,2004:1774-1779.
40管成,朱善安.电液伺服系统的积分滑模自适应控制[J].电工技术学报,2005,20(4):52-57.
41管成,朱善安.一类非线性系统的微分与积分滑模自适应控制及其在电液伺服系统中的应用[J].中国电机工程学报,2005,25(4):103-108.
42管成,朱善安.电液伺服系统的多滑模鲁棒自适应控制[J].控制理论与应用,2005,22(6):931-938.
43刘金琨,孙富春.滑模变结构控制理论及其算法研究与进展[J].控制理论与应用,2007,24(3):407-418.
44刘云峰,缪栋.电液伺服系统的自适应模糊滑模控制研究[J].中国电机工程学报,2006,26(14):140-144.
45杨勇.液压伺服系统自适应模糊变结构控制[J].电子学报,2008,36(1):86-89.
46Zhang Y W, Gui W H. Compensation for Secondary Uncertainty in Electro-Hydraulic ServoSystem by Gain Adaptive Sliding Mode Variable Structure Control[J]. Journal of Central SouthUniversity of Technology,2008,15(2):256-263.
47方一鸣,聂颖,王众.电液伺服位置系统的变结构自适应鲁棒控制[J].计算机仿真,2006,23(11):149-153.
48管成,潘双夏.含有非线性不确定参数的电液系统滑模自适应控制[J].控制理论与应用,2008,25(2):261-167.
49Guan C, Pan S X. Adaptive Sliding Mode Control of Electro-Hydraulic System with NonlinearUnknown Parameters [J]. Control Engineering Practice,2008,16(11):1275-1284.
50Ursu I, Ursu F, Popescu F. Backstepping Design for Controlling Electrohydraulic Servos[J].Journal of the Franklin Institute,2006,343(1):94-110.
51Smaoui M, Brun X, Thomasset D. A Study on Tracking Position Control of an ElectropneumaticSystem Using Backstepping Design[J]. Control Engineering Practice,2006,14(8):923-933.
52Yip P P, Hedrick J K. Adaptive Dynamic Surface Control: a Simplified Algorithm for AdaptiveBackstepping Control of Nonlinear Systems[J]. International Journal of Control,1998,71(5):959-979.
53Swaroop D, Hedrick J K, Yip P P, et al. Dynamic Surface Control for a Class of NonlinearSystems[J]. IEEE Transactions on Automatic Control,2000,45(10):1893-1899.
54Duraiswamy S, Chiu G T C. Nonlinear Adaptive Nonsmooth Dynamic Surface Control ofElectro-Hydraulic Systems[C]. Proceedings of the2003American Control Conference, Denver,Colorado, USA: AACC,2003,4:3287-3292.
55白寒,管成.电液比例系统鲁棒自适应动态表面控制[J].浙江大学学报(工学版),2010,44(8):1441-1448.
56刘强,冯培恩,潘双夏.基于干扰观测器的非对称液压缸鲁棒运动控制[J].浙江大学学报(工学版),2006,40(4):594-599.
57Shahruz S M. Performance Enhancement of a Class of Nonlinear Systems by DisturbanceObserver[J]. IEEE Transactions on Mechatronics,2000,5(3):319-323.
58Chen W H. Disturbance Observer Based Control for Nonlinear Systems[J]. IEEE/ASMETransactions on Mechatronics,2004,9(4):706-711.
59刘晓东,吴云洁,田大鹏,等.基于干扰观测器的飞行仿真转台滑模控制器[J].上海交通大学学报(自然版),2011,45(03):393-397.
60皮阳军,王宣银,李强.基于干扰观测器的舰船运动模拟器非线性控制[J].机械工程学报,2010,46(10):164-170.
61Pi Y J, Wang X Y. Observer-Based Cascade Control of a6-DOF Parallel Hydraulic Manipulatorin Joint Space Coordinate[J]. Mechatronics,2010,20(6):648-655.
62Canudas de Wit C, Olsson H, Astrom K J. A New Model for Control of Systems with Friction[J].IEEE Transactions on Automatic Control,1995,40(3):419-425.
63Bonchis A, Corke P I, Rye D C, et al. Variable Structure Methods in Hydraulic Servo SystemsControl[J]. Automatica,2001,37(4):589-595.
64Ramasubramanian A, Ray L R. Comparison of EKBF-Based and Classical FrictionCompensation [J]. Journal of Dynamic Systems, Measurement and Control,2007,129(2):236-242.
65Sekhavat P, Wu Q, Sepehri N. Lyapunov-Based Friction Compensation for Accurate Positioningof a Hydraulic Actuator[C]. Proceedings of the2004American Control Conference, Boston, MA,USA: American Automatic Control Council (AACC),2004,1:418-423.
66Han S I, Lee K S, Park M G, et al. Robust Adaptive Deadzone and Friction Compensation ofRobot Manipulator Using RWCMAC Network[J]. Journal of Mechanical Science andTechnology,2011,25(6):1583-1594.
67张友旺,桂卫华.基于自适应模糊神经网络的摩擦力分部补偿算法[J].控制与决策,2005,20(3):356-360.
68Vitiello V, Tornambe A. Adaptive Compensation of Modeled Friction Using a RBF NeuralNetwork Approximation[C]. Proceedings of the46th IEEE Conference on Decision and Control,New Orleans, LA, USA: IEEE,2007,4699-4704.
69仲伟峰,何小溪.电液伺服位置系统的模糊神经网络控制[J].电机与控制学报,2007,12(4):478-482.
70Hanh D L, Ahn K K, Kha N B, et al. Trajectory Control of Electro-Hydraulic Excavator UsingFuzzy Self-Tuning Algorithm with Neural Network[J]. Journal of Mechanical Science andTechnology,2009,23(1):149-160.
71杨逢瑜,杨云,吴军,等.模糊神经网络滑模控制在轧机中的应用[J].机床与液压,2009,37(3):122-123,98.
72Bessa W M, Dutra M S, Kreuzer E. Sliding Mode Control with Adaptive Fuzzy Dead-ZoneCompensation of an Electro-Hydraulic Servo System[J]. Journal of Intelligent&RoboticSystems,2010,58(1)3-16.
73Poursamad A. Adaptive Feedback Linearization Control of Antilock Braking Systems UsingNeural Networks[J]. Mechatronics,2009,19(5):767-773.
74韩崇伟,林廷圻,肖文伟,等.电液伺服系统滑动模态变结构控制[J].系统仿真学报,2002,16(6):821-823,826.
75Chen Y. Backstepping Controller Design for Electro-Hydraulic Servo System with SlidingObserver[C]. Proceedings of the29th Chinese Control Conference, Beijing, China: ChineseAssociation of Automation (CAA),2010:391-394.
76Nakkarat P, Kuntanapreeda, S. Observer-Based Backstepping Force Control of an Electro-Hydraulic Actuator[J]. Control Engineering Practice,2009,17(8):895-902.
77赵琳琳,方一鸣,仲伟峰,等.冷带轧机厚控系统自适应鲁棒输出反馈动态控制器设计[J].控制理论与应用,2008,25(4):787-790.
78刘允刚.一类具有不确定控制系数和依赖于不可测状态增长非线性系统的全局输出反馈镇定[J].中国科学E辑:信息科学,2008,38(12):2150-2162.
79Garimella P, Yao B. Nonlinear Adaptive Robust Observer for Velocity Estimation of HydraulicCylinders Using Pressure Measurement Only [C]. Proceedings of the ASME2002InternationalMechanical Engineering Congress and Exposition, New Orleans, USA: ASME,2002,907-916.
80闫茂德,张怀梅.磁悬浮机床主轴的非线性输出反馈自适应控制[J].机床与液压,2005,33(6):116-119.
81丁玉琴,刘允刚.无未知参数先验信息的非线性自适应观测器设计[J].控制理论与应用,2008,25(1):27-37.
82Besan on G, Zhang Q, Hammouri H. High-Gain Observer Based State and ParametersEstimation in Nonlinear Systems[C]\\IFAC. Nonlinear Control Systems2004: a Proceedings ofthe6th International Federal of Automatic Control (IFAC) Symposium, Stuttgart, Germany,September1-3,2004. Oxford: Elsevier,2005,1:327-332.
83Dong Y L, Mei S W. Adaptive Observer for a Class of Nonlinear Systems[J]. Acta AutomaticaSinica,2007,33(10):1081-1084.
84Zhang Q H, Clavel A. Adaptive Observer with Exponential Forgetting Factor for Linear TimeVarying Systems[C]. Proceedings of40th IEEE Conference on Decision and Control, Orlando,FL, USA: IEEE,2001:3886-3891.
85Zhang Q H. Adaptive Observers for Multiple-Input-Multiple-Output (MIMO) Linear Time-Varying Systems[J]. IEEE Transactions on Automatic Control,2002,47(3):1183-1193.
86Farza M, M’Saad M, Rossignol L. Observer Design for a Class of MIMO Nonlinear Systems[J].Automatica,2004,40(1):135-143.
87Farza M, M’Saad M, Maatoug T, et al. Adaptive Observers for Nonlinearly Parameterized Classof Nonlinear System[J]. Automatica,2009,45(10):2292-2399.
88Shang F, Liu Y G, Adaptive Output-Feedback Stabilization for a Class of Uncertain NonlinearSystems[J]. Acta Automatica Sinica,2010,36(1):92-100.
89Lei H, Lin W. Universal Adaptive Control of Nonlinear Systems with Unknown Growth Rate byOutput Feedback[J]. Automatica,2006,42(10):1783-1789.
90刘胜,周丽明.一类饱和不确定非线性系统静态抗饱和控制设计[J].控制与决策,2009,24(5):764-768.
91Grimm G, Hatfield J, Postlethwaite I, et al. Antiwindup for Stable Linear Systems with InputSaturation: an LMI-Based Synthesis[J]. IEEE Transactions on Automatic Control,2003,48(9):1509-1525.
92Gomes da Silva Jr. J M, Tarbouriech S. Antiwindup Design with Guaranteed Regions of Stability:an LMI-Based Approach[J]. IEEE Transactions on Automatic Control,2005,50(1):106-111.
93iljak D D, Stipanovi D. Robust Stabilization of Nonlinear Systems: the LMI Approach[J].Mathematical Problems in Engineering,2000,6(5):461-493.
94Stankovi S S, iljak D D. Robust Stabilization of Nonlinear Interconnected Systems byDecentralized Dynamic Output Feedback[J]. System&Control Letters,2009,58(4):271-275.
95Boyd S, Ghaoui L EI, Balakrishnan V. Linear Matrix Inequalities in System and ControlTheory[M], Philadelphia: SIAM,1994.
96De Oliveira M C. A Robust Version of the Elimination Lemma[C]. Proceedings of the16thIFAC World Congress, CD-ROM, Prague, Czech Republic: IFAC,2005,16,1[2010-7-14].http://www.nt.ntnu.no/users/skoge/prost/proceedings/ifac2005/Fullpapers/04538.pdf.
97Germani A, Manes C, Pepe P. A New Approach to State Observeation of Nonlinear Dystemswith Delayed Output[J]. IEEE Transactions on Automatic Control,2002,47(1):96-101.
98Kazantzis N, Wright R A. Nonlinear Observer Design in the Presence of Delayed OutputMeasurements[J]. Sysems&Control Letters,2005,54(9):877-886.
99Lee S. Observer for Discrete-time Lipschitz Non-linear Systems with Delayed Output[J]. IETControl Theory and Applications,2011,5(1):54-62.
100朱建栋.带传输滞后的离散系统的观测器及输出动态反馈[J].控制与决策,2008,23(10):1178-1121.
101刘晓飞,焦晓红,王春艳.基于测量延时降维观测器的冷轧机厚控系统鲁棒控制[C].第29届中国控制会议,北京:中国自动化学会,2010:2047-2052.
102Jiao X H, Mei Z S. Reduced-Order Observer-Based Robust Synchronization Control of ColdRolling Mills with Measurement Delay[J]. International Journal of Control,2010,83(10):2080-2090.
103Modal S, Chakraborty G, Bhattacharyya, K. LMI Approach to Robust Unknown Input ObserverDesign for Continuous Systems with Noise and Uncertainties [J]. International Journal ofControl, Automation, and Systems,2010,8(2):210-219.
104朱淑倩,冯俊娥,程兆林.含未知输入的时滞系统的函数观测器及输出反馈镇定[J].控制理论与应用,2005,22(2):295-300.
105Kalsi K, Lian J M, Hui S, et al. Sliding-Mode Observers for Systems with Unknown Inputs: aHigh-gain Approach [J]. Automatica,2010,46(2):347-353.
106Orjuela R, Marx B, Tago J, et al. Estimating the State and the Unknown Inputs of NonlinearSystems Using a Multiple Model Approach [C]. Proceedings of the16th IEEE MediterraneanConference on Control and Automation (MED’08), Ajaccio, France: IEEE,2008:1375-1380.
107Gauthier J P, Kupka I. Deterministic Observation Theory and Applications[M]. UK, Cambridge:Cambridge University Press,2001.
108Boizot N, Busvelle E, Gauthier J P. An Adaptive High-Gain Observer for Nonlinear Systems[J].Automatica,2010,46(9):1483-1488.
109Praly L, Jiang Z P. Linear Output Feedback with Dynamic High Gain for Nonlinear Systems[J].Systems&Control Letters,2004,53(2):107-116.
110Praly L. Asymptotic Stabilization via Output Feedback for Lower Triangular Systems withOutput Dependent Incremental Rate[J]. IEEE Transactions on Automatic Control,2003,48(6):1103-1108.
111Gauthier J P, Hammouri H, Othman S. A Simple Observer for Nonlinear Systems Applicationsto Bioreactors[J]. IEEE Transactions on Automatic Control,1992,37(6):875-880.
112Busawon K, Farza M, Hammouri H. Observer Design for a Special Class of NonlinearSystems[J]. International Journal of Control,1998,71(3):405-418.
113Marino R, Tomei P. Noninear Control Design: Geonetric, Adaptive and Robust[M]. UK,Hertfordshire: Prentice Hall International (UK) Ltd.,1996.
114Skelton R E, Iwasaki T, Grigoriadis K M. A Unified Algebraic Approach to Linear ControlDesign [M]. London: Taylor&Francis,1998.
115Tan K, Grigoriadis K M. Stabilization and H∞Control of Symmetric Systems: an ExplicitSolution[J]. Systems&Control Letters,2001,44(1):57-72.
116Kothare M V, Balakrishnan V, Morari M. Robust Constrained Model Predictive Control UsingLinear Matrix Inequalities, Automatica,1996,32(10):1361-1379.
117Mayne D Q, Rawlings J B, Rao C V, et al. Constrained Model Predictive Control: Stability andOptimality[J], Automatica,2000,36(6):78-814.
118Mao W J. Robust Stabilization of Uncertain Time-varying Discrete Systems and Comments on“An Improved Approach for Constrained Robust Model Predictive Control”[J]. Automatica,2003,39(7):1109-1112.
119丁宝苍,杨鹏.基于标称性能指标的离线鲁棒预测控制器综合[J].自动化学报,2006,32(2):304-310.
120丁宝苍,邹涛.约束时变不确定离散系统的输出反馈预测控制综合[J].自动化学报,2007,33(1):78-83.
121Wan Z Y, Kothare M V. An Efficient Off-line Formulation of Robust Model Predictive ControlUsing Linear Matrix Inequalities [J]. Automatica,2003,39(5):837-846.
122Ding B C, Xi Y G, Cychowski M T, et al. Improving Off-line Approach to Robust MPCBased-on Nominal Performance cost [J]. Automatica,2007,43(1):158-163.
2俞立.鲁棒控制:线性矩阵不等式处理方法[M].北京:清华大学出版社,2002:1-20.
3Merritt H E. Hydraulic Control Systems[M]. New York: John Wiley and Sons,1967.
4路甬祥.流体传动与控制技术的历史进展与展望[J].机械工程学报,2001,37(10):1-10.
5连家创,刘宏民.板厚板形控制[M].北京:兵器工业出版社,1996:137,173-184.
6王占林.近代液压控制[M].北京:机械工业出版社,1997:1-16.
7Liu G P, Daley S. Optimal-Tuning Nonlinear PID Control of Hydraulic Systems[J]. ControlEngineering Practice2000,8(9):1045-1053.
8吴振顺,姚建均,岳东海.模糊自整定PID控制器的设计及其应用[J].哈尔滨工业大学学报,2004,36(11):1578-1582.
9邹俊,傅新,杨华勇,等.自适应交互PID在液压伺服系统中的应用[J].机械工程学报,2006,42(11):179-184.
10王益群,王海芳,高英杰,等.基于神经网络PID的轧机AGC力控制[J].中国机械工程,2005,16(18):1650-1654.
11Karam M E, Jiao Z X, Zhang H Q. PID Controller Optimization by GA and Its Performances onthe Electro-Hydraulic Servo Control System[J]. Chinese Journal of Aeronautics,2008,21(4):378-384.
12姜万录,刘伟,张瑞娟,等.基于蚁群优化的神经网络智能PID控制策略研究[J].机床与液压,2010,38(13):22-26.
13Hsia T C. A New Technique for Robust Control of Servo System[J]. IEEE Transactions onIndustrial Electronics,1989,36(1):1-7.
14Jen Y, Lee C. Robust Speed Control of a Pump-Controlled Motor System[J]. IEEE Proceeding D.Control Theory and Applications,1992,139(6):503-510.
15方一鸣,嵇胜龙,卜劭华,等.液压伺服驱动位置控制系统的鲁棒性能设计[J].系统仿真学报,2002,14(4):467-469.
16胡广平,陈乃超.基于H2H∞控制的液压伺服系统鲁棒性设计[J].机床与液压,2007,35(2):125-128.
17Mili V, itum, Essert M. Robust H∞Position Control Synthesis of an Electro-HydraulicServo System[J]. ISA Transactions,2010,49(4):535-542.
18段锁林,魏聪梅,安高成,等.不确定性电液伺服位置系统的滑模鲁棒跟踪控制[J].太原重型机械学院学报,2001,22(2):89-93.
19王本永,董彦良,赵克定.高精度液压仿真转台鲁棒控制[J].航空学报,2007,28(5):1252-1258.
20Yu H, Feng Z J, Wang X Y. Nonlinear Control for a Class of Hydraulic Servo System[J]. Journalof Zhejiang University: Science,2004,5(11):1413-1417.
21Niksefat N, Sepehri N. Design and Experimental Evaluation of a Robust Force Controller for anElectro-Hydraulic Actuator via Quantitative Feedback Theory[J]. Control Engineering Practice,2000,8(12):1335-1345.
22富强,尔联洁,赵国荣.基于定量反馈理论的飞行仿真转台鲁棒控制[J].北京航空航天大学学报,2004,30(5):410-413.
23Ahn K K, Dinh Q T. Self-Tuning of Quantitative Feedback Theory for Force Control of anElectro-Hydraulic Test Machine[J]. Control Engineering Practice,2009,17(11):1291-1306.
24王增会,陈增强,孙青林,等.定量反馈理论发展综述[J].控制理论与应用,2006,23(3):404-411.
25吴士昌,吴忠强.自适应控制[M].第2版.北京:机械工业出版社,2005:3-8.
26管成.非线性系统的滑模自适应控制及其在电液控制系统中的应用[D].杭州:浙江大学博士论文,2005:5-9,51-79.
27张友旺.电液伺服系统的动态递归模糊神经网络辨识与鲁棒控制研究[D].长沙:中南大学博士学位论文,2006:3-13.
28焦晓红,耿秋实,方一鸣,等.液压伺服并联机器人的自适应鲁棒跟踪控制[J].系统仿真学报,2003,15(3):401-404.
29Alleyne A, Hedrick J K. Nonlinear Adaptive Control of Active Suspension[J]. IEEETransactions on Control Systems Technology,1995,3(1):94-101.
30Alleyne A. Nonlinear Force Control of an Electro-Hydraulic Actuator[C]. Proceedings of theJapan/USA Symposium on Flexible Automation, Boston, USA: ASME&ISCIE,1996,193-200.
31Yao B, Chiu G T C, Reedy J T. Nonlinear Adaptive Robust Control of One-Dof Electro-Hydraulic Servo Systems[C]. Proceedings of the ASME International Mechanical EngineeringCongress and Exposition (IMECE’97), Dallas, TX, USA: ASME,1997,4:191-197.
32Yao B, Bu F P, Reedy J, et al. Adaptive Robust Motion Control of Single-Rod HydraulicActuators: Theory and Experiments[J]. IEEE/ASME Transactions on Mechatronics,2000,5(1):79-92.
33Yao B, Tomizuka M. Adaptive Robust Control of MIMO Nonlinear Systems in Semi-StrictFeedback Forms[J]. Automatica,2001,37(9):1305-1321.
34Yao B, Bu F P, Chiu G T C. Non-linear Adaptive Robust Control of Electro-Hydraulic SystemsDriven by Double-Rod Acturators[J]. International Journal of Control,2001,74(8):761-775.
35Hua C X, Yao, B, Wang Q F. Integrated Direct/Indirect Adaptive Robust Contouring Control ofa Biaxial Gantry with Accurate Parameter Estimations[J]. Automatica,2010,46(4):701-707.
36Mohanty A, Yao B. Indirect Adaptive Robust Control of Hydraulic Manipulators with AccurateParameter Estimates[J]. IEEE Transactions on Control Systems Technology,2011,19(3):567-575.
37Choux M, Karimi H R, Hovland G, et al. Robust Adaptive Backstepping Control Design for aNonlinear Hydraulic-Mechanical System[C]. Proceedings of the Joint48th IEEE Conference onDecision and Control and28th Chinese Control Conference, Shanghai, China: IEEE&CAA,2009:2460-2467.
38方一鸣,王志杰,谢云鹏,等.轧机液压伺服位置系统多模型切换滑模变结构控制[J].电机与控制学报,2010,14(5):91-97.
39Guan C, Zhu S A. Adaptive Time-Varying Sliding Mode Control for Hydraulic Servo System[C].Proceedings of the8th International Conference on Control, Automation, Robotics and Vision(ICARCV2004), Kunming, China: IEEE,2004:1774-1779.
40管成,朱善安.电液伺服系统的积分滑模自适应控制[J].电工技术学报,2005,20(4):52-57.
41管成,朱善安.一类非线性系统的微分与积分滑模自适应控制及其在电液伺服系统中的应用[J].中国电机工程学报,2005,25(4):103-108.
42管成,朱善安.电液伺服系统的多滑模鲁棒自适应控制[J].控制理论与应用,2005,22(6):931-938.
43刘金琨,孙富春.滑模变结构控制理论及其算法研究与进展[J].控制理论与应用,2007,24(3):407-418.
44刘云峰,缪栋.电液伺服系统的自适应模糊滑模控制研究[J].中国电机工程学报,2006,26(14):140-144.
45杨勇.液压伺服系统自适应模糊变结构控制[J].电子学报,2008,36(1):86-89.
46Zhang Y W, Gui W H. Compensation for Secondary Uncertainty in Electro-Hydraulic ServoSystem by Gain Adaptive Sliding Mode Variable Structure Control[J]. Journal of Central SouthUniversity of Technology,2008,15(2):256-263.
47方一鸣,聂颖,王众.电液伺服位置系统的变结构自适应鲁棒控制[J].计算机仿真,2006,23(11):149-153.
48管成,潘双夏.含有非线性不确定参数的电液系统滑模自适应控制[J].控制理论与应用,2008,25(2):261-167.
49Guan C, Pan S X. Adaptive Sliding Mode Control of Electro-Hydraulic System with NonlinearUnknown Parameters [J]. Control Engineering Practice,2008,16(11):1275-1284.
50Ursu I, Ursu F, Popescu F. Backstepping Design for Controlling Electrohydraulic Servos[J].Journal of the Franklin Institute,2006,343(1):94-110.
51Smaoui M, Brun X, Thomasset D. A Study on Tracking Position Control of an ElectropneumaticSystem Using Backstepping Design[J]. Control Engineering Practice,2006,14(8):923-933.
52Yip P P, Hedrick J K. Adaptive Dynamic Surface Control: a Simplified Algorithm for AdaptiveBackstepping Control of Nonlinear Systems[J]. International Journal of Control,1998,71(5):959-979.
53Swaroop D, Hedrick J K, Yip P P, et al. Dynamic Surface Control for a Class of NonlinearSystems[J]. IEEE Transactions on Automatic Control,2000,45(10):1893-1899.
54Duraiswamy S, Chiu G T C. Nonlinear Adaptive Nonsmooth Dynamic Surface Control ofElectro-Hydraulic Systems[C]. Proceedings of the2003American Control Conference, Denver,Colorado, USA: AACC,2003,4:3287-3292.
55白寒,管成.电液比例系统鲁棒自适应动态表面控制[J].浙江大学学报(工学版),2010,44(8):1441-1448.
56刘强,冯培恩,潘双夏.基于干扰观测器的非对称液压缸鲁棒运动控制[J].浙江大学学报(工学版),2006,40(4):594-599.
57Shahruz S M. Performance Enhancement of a Class of Nonlinear Systems by DisturbanceObserver[J]. IEEE Transactions on Mechatronics,2000,5(3):319-323.
58Chen W H. Disturbance Observer Based Control for Nonlinear Systems[J]. IEEE/ASMETransactions on Mechatronics,2004,9(4):706-711.
59刘晓东,吴云洁,田大鹏,等.基于干扰观测器的飞行仿真转台滑模控制器[J].上海交通大学学报(自然版),2011,45(03):393-397.
60皮阳军,王宣银,李强.基于干扰观测器的舰船运动模拟器非线性控制[J].机械工程学报,2010,46(10):164-170.
61Pi Y J, Wang X Y. Observer-Based Cascade Control of a6-DOF Parallel Hydraulic Manipulatorin Joint Space Coordinate[J]. Mechatronics,2010,20(6):648-655.
62Canudas de Wit C, Olsson H, Astrom K J. A New Model for Control of Systems with Friction[J].IEEE Transactions on Automatic Control,1995,40(3):419-425.
63Bonchis A, Corke P I, Rye D C, et al. Variable Structure Methods in Hydraulic Servo SystemsControl[J]. Automatica,2001,37(4):589-595.
64Ramasubramanian A, Ray L R. Comparison of EKBF-Based and Classical FrictionCompensation [J]. Journal of Dynamic Systems, Measurement and Control,2007,129(2):236-242.
65Sekhavat P, Wu Q, Sepehri N. Lyapunov-Based Friction Compensation for Accurate Positioningof a Hydraulic Actuator[C]. Proceedings of the2004American Control Conference, Boston, MA,USA: American Automatic Control Council (AACC),2004,1:418-423.
66Han S I, Lee K S, Park M G, et al. Robust Adaptive Deadzone and Friction Compensation ofRobot Manipulator Using RWCMAC Network[J]. Journal of Mechanical Science andTechnology,2011,25(6):1583-1594.
67张友旺,桂卫华.基于自适应模糊神经网络的摩擦力分部补偿算法[J].控制与决策,2005,20(3):356-360.
68Vitiello V, Tornambe A. Adaptive Compensation of Modeled Friction Using a RBF NeuralNetwork Approximation[C]. Proceedings of the46th IEEE Conference on Decision and Control,New Orleans, LA, USA: IEEE,2007,4699-4704.
69仲伟峰,何小溪.电液伺服位置系统的模糊神经网络控制[J].电机与控制学报,2007,12(4):478-482.
70Hanh D L, Ahn K K, Kha N B, et al. Trajectory Control of Electro-Hydraulic Excavator UsingFuzzy Self-Tuning Algorithm with Neural Network[J]. Journal of Mechanical Science andTechnology,2009,23(1):149-160.
71杨逢瑜,杨云,吴军,等.模糊神经网络滑模控制在轧机中的应用[J].机床与液压,2009,37(3):122-123,98.
72Bessa W M, Dutra M S, Kreuzer E. Sliding Mode Control with Adaptive Fuzzy Dead-ZoneCompensation of an Electro-Hydraulic Servo System[J]. Journal of Intelligent&RoboticSystems,2010,58(1)3-16.
73Poursamad A. Adaptive Feedback Linearization Control of Antilock Braking Systems UsingNeural Networks[J]. Mechatronics,2009,19(5):767-773.
74韩崇伟,林廷圻,肖文伟,等.电液伺服系统滑动模态变结构控制[J].系统仿真学报,2002,16(6):821-823,826.
75Chen Y. Backstepping Controller Design for Electro-Hydraulic Servo System with SlidingObserver[C]. Proceedings of the29th Chinese Control Conference, Beijing, China: ChineseAssociation of Automation (CAA),2010:391-394.
76Nakkarat P, Kuntanapreeda, S. Observer-Based Backstepping Force Control of an Electro-Hydraulic Actuator[J]. Control Engineering Practice,2009,17(8):895-902.
77赵琳琳,方一鸣,仲伟峰,等.冷带轧机厚控系统自适应鲁棒输出反馈动态控制器设计[J].控制理论与应用,2008,25(4):787-790.
78刘允刚.一类具有不确定控制系数和依赖于不可测状态增长非线性系统的全局输出反馈镇定[J].中国科学E辑:信息科学,2008,38(12):2150-2162.
79Garimella P, Yao B. Nonlinear Adaptive Robust Observer for Velocity Estimation of HydraulicCylinders Using Pressure Measurement Only [C]. Proceedings of the ASME2002InternationalMechanical Engineering Congress and Exposition, New Orleans, USA: ASME,2002,907-916.
80闫茂德,张怀梅.磁悬浮机床主轴的非线性输出反馈自适应控制[J].机床与液压,2005,33(6):116-119.
81丁玉琴,刘允刚.无未知参数先验信息的非线性自适应观测器设计[J].控制理论与应用,2008,25(1):27-37.
82Besan on G, Zhang Q, Hammouri H. High-Gain Observer Based State and ParametersEstimation in Nonlinear Systems[C]\\IFAC. Nonlinear Control Systems2004: a Proceedings ofthe6th International Federal of Automatic Control (IFAC) Symposium, Stuttgart, Germany,September1-3,2004. Oxford: Elsevier,2005,1:327-332.
83Dong Y L, Mei S W. Adaptive Observer for a Class of Nonlinear Systems[J]. Acta AutomaticaSinica,2007,33(10):1081-1084.
84Zhang Q H, Clavel A. Adaptive Observer with Exponential Forgetting Factor for Linear TimeVarying Systems[C]. Proceedings of40th IEEE Conference on Decision and Control, Orlando,FL, USA: IEEE,2001:3886-3891.
85Zhang Q H. Adaptive Observers for Multiple-Input-Multiple-Output (MIMO) Linear Time-Varying Systems[J]. IEEE Transactions on Automatic Control,2002,47(3):1183-1193.
86Farza M, M’Saad M, Rossignol L. Observer Design for a Class of MIMO Nonlinear Systems[J].Automatica,2004,40(1):135-143.
87Farza M, M’Saad M, Maatoug T, et al. Adaptive Observers for Nonlinearly Parameterized Classof Nonlinear System[J]. Automatica,2009,45(10):2292-2399.
88Shang F, Liu Y G, Adaptive Output-Feedback Stabilization for a Class of Uncertain NonlinearSystems[J]. Acta Automatica Sinica,2010,36(1):92-100.
89Lei H, Lin W. Universal Adaptive Control of Nonlinear Systems with Unknown Growth Rate byOutput Feedback[J]. Automatica,2006,42(10):1783-1789.
90刘胜,周丽明.一类饱和不确定非线性系统静态抗饱和控制设计[J].控制与决策,2009,24(5):764-768.
91Grimm G, Hatfield J, Postlethwaite I, et al. Antiwindup for Stable Linear Systems with InputSaturation: an LMI-Based Synthesis[J]. IEEE Transactions on Automatic Control,2003,48(9):1509-1525.
92Gomes da Silva Jr. J M, Tarbouriech S. Antiwindup Design with Guaranteed Regions of Stability:an LMI-Based Approach[J]. IEEE Transactions on Automatic Control,2005,50(1):106-111.
93iljak D D, Stipanovi D. Robust Stabilization of Nonlinear Systems: the LMI Approach[J].Mathematical Problems in Engineering,2000,6(5):461-493.
94Stankovi S S, iljak D D. Robust Stabilization of Nonlinear Interconnected Systems byDecentralized Dynamic Output Feedback[J]. System&Control Letters,2009,58(4):271-275.
95Boyd S, Ghaoui L EI, Balakrishnan V. Linear Matrix Inequalities in System and ControlTheory[M], Philadelphia: SIAM,1994.
96De Oliveira M C. A Robust Version of the Elimination Lemma[C]. Proceedings of the16thIFAC World Congress, CD-ROM, Prague, Czech Republic: IFAC,2005,16,1[2010-7-14].http://www.nt.ntnu.no/users/skoge/prost/proceedings/ifac2005/Fullpapers/04538.pdf.
97Germani A, Manes C, Pepe P. A New Approach to State Observeation of Nonlinear Dystemswith Delayed Output[J]. IEEE Transactions on Automatic Control,2002,47(1):96-101.
98Kazantzis N, Wright R A. Nonlinear Observer Design in the Presence of Delayed OutputMeasurements[J]. Sysems&Control Letters,2005,54(9):877-886.
99Lee S. Observer for Discrete-time Lipschitz Non-linear Systems with Delayed Output[J]. IETControl Theory and Applications,2011,5(1):54-62.
100朱建栋.带传输滞后的离散系统的观测器及输出动态反馈[J].控制与决策,2008,23(10):1178-1121.
101刘晓飞,焦晓红,王春艳.基于测量延时降维观测器的冷轧机厚控系统鲁棒控制[C].第29届中国控制会议,北京:中国自动化学会,2010:2047-2052.
102Jiao X H, Mei Z S. Reduced-Order Observer-Based Robust Synchronization Control of ColdRolling Mills with Measurement Delay[J]. International Journal of Control,2010,83(10):2080-2090.
103Modal S, Chakraborty G, Bhattacharyya, K. LMI Approach to Robust Unknown Input ObserverDesign for Continuous Systems with Noise and Uncertainties [J]. International Journal ofControl, Automation, and Systems,2010,8(2):210-219.
104朱淑倩,冯俊娥,程兆林.含未知输入的时滞系统的函数观测器及输出反馈镇定[J].控制理论与应用,2005,22(2):295-300.
105Kalsi K, Lian J M, Hui S, et al. Sliding-Mode Observers for Systems with Unknown Inputs: aHigh-gain Approach [J]. Automatica,2010,46(2):347-353.
106Orjuela R, Marx B, Tago J, et al. Estimating the State and the Unknown Inputs of NonlinearSystems Using a Multiple Model Approach [C]. Proceedings of the16th IEEE MediterraneanConference on Control and Automation (MED’08), Ajaccio, France: IEEE,2008:1375-1380.
107Gauthier J P, Kupka I. Deterministic Observation Theory and Applications[M]. UK, Cambridge:Cambridge University Press,2001.
108Boizot N, Busvelle E, Gauthier J P. An Adaptive High-Gain Observer for Nonlinear Systems[J].Automatica,2010,46(9):1483-1488.
109Praly L, Jiang Z P. Linear Output Feedback with Dynamic High Gain for Nonlinear Systems[J].Systems&Control Letters,2004,53(2):107-116.
110Praly L. Asymptotic Stabilization via Output Feedback for Lower Triangular Systems withOutput Dependent Incremental Rate[J]. IEEE Transactions on Automatic Control,2003,48(6):1103-1108.
111Gauthier J P, Hammouri H, Othman S. A Simple Observer for Nonlinear Systems Applicationsto Bioreactors[J]. IEEE Transactions on Automatic Control,1992,37(6):875-880.
112Busawon K, Farza M, Hammouri H. Observer Design for a Special Class of NonlinearSystems[J]. International Journal of Control,1998,71(3):405-418.
113Marino R, Tomei P. Noninear Control Design: Geonetric, Adaptive and Robust[M]. UK,Hertfordshire: Prentice Hall International (UK) Ltd.,1996.
114Skelton R E, Iwasaki T, Grigoriadis K M. A Unified Algebraic Approach to Linear ControlDesign [M]. London: Taylor&Francis,1998.
115Tan K, Grigoriadis K M. Stabilization and H∞Control of Symmetric Systems: an ExplicitSolution[J]. Systems&Control Letters,2001,44(1):57-72.
116Kothare M V, Balakrishnan V, Morari M. Robust Constrained Model Predictive Control UsingLinear Matrix Inequalities, Automatica,1996,32(10):1361-1379.
117Mayne D Q, Rawlings J B, Rao C V, et al. Constrained Model Predictive Control: Stability andOptimality[J], Automatica,2000,36(6):78-814.
118Mao W J. Robust Stabilization of Uncertain Time-varying Discrete Systems and Comments on“An Improved Approach for Constrained Robust Model Predictive Control”[J]. Automatica,2003,39(7):1109-1112.
119丁宝苍,杨鹏.基于标称性能指标的离线鲁棒预测控制器综合[J].自动化学报,2006,32(2):304-310.
120丁宝苍,邹涛.约束时变不确定离散系统的输出反馈预测控制综合[J].自动化学报,2007,33(1):78-83.
121Wan Z Y, Kothare M V. An Efficient Off-line Formulation of Robust Model Predictive ControlUsing Linear Matrix Inequalities [J]. Automatica,2003,39(5):837-846.
122Ding B C, Xi Y G, Cychowski M T, et al. Improving Off-line Approach to Robust MPCBased-on Nominal Performance cost [J]. Automatica,2007,43(1):158-163.