基于观测器的动态系统故障估计和调节
|
摘要
由于对实际工业过程控制系统安全性与可靠性的要求日益提高，动态系统的故障诊断与容错控制的研究受到越来越多的关注。用故障调节来提高系统的稳定性和可靠性是有效方法之一，因此得到了广泛而深入地研究并成为最近几年研究的一个热点。故障检测技术是用于检测系统是否发生了故障，是故障调节的第一个环节。故障估计则要在故障检测的基础上，在线估计出故障的幅值，是故障调节中一个非常重要的环节，因为附加控制器是依据故障估计值设计的。相比于故障检测，故障估计的设计难度无疑增加了许多，因此故障估计和调节的研究是更富有挑战性的。虽然近几年动态系统的故障估计和调节取得了一些研究成果，但是目前常用的设计方法各自均存在着一定的设计难点，正是这些设计难点限制了各自的应用。因此，故障估计和调节问题仍是一个有待深入研究的课题。本文研究了基于观测器的动态系统故障估计和调节理论方法与技术，建立起了一套系统、全面的，包括连续和离散系统的故障估计和调节理论框架。论文的主要工作如下：
首先，针对传统自适应故障估计(CAFE)算法难以满足故障估计性能问题，提出了一种新的快速自适应故障估计(FAFE)算法，显著提升了故障估计的性能，包括快速性和准确性。然后，对其证明过程进行了改进，通过不等式变换消除了存在的等式约束。进一步，将提出的FAFE算法推广到了时滞系统。基于松弛矩阵设计思想，研究了快时变时滞系统的故障估计，解决了CAFE算法仅适用于慢时变时滞系统的设计难点，并且研究了中立时滞系统的故障估计，解决了CAFE算法难以应用于此类系统的技术难点。
其次，针对一类特定的执行器损伤故障，提出了基于自适应观测器的快速执行器损伤故障估计算法。同时，基于在线获取的故障估计值，给出了一种故障调节设计方案。值得注意的是，提出的故障估计观测器和故障调节是分开设计的，南南简化了设计过程。当执行器发生损伤故障时，给出的故障调节方案可以确保整个系统是渐近稳定的。
再次，针对自适应观测器需要误差系统满足严格正实(SPR)条件，提出了一种全阶故障估计观测器(FFEO)设计方法，并基于此设计了基于动态输出反馈的故障调节。这种观测器设计比自适应观测器具有更广的应用范围。进一步，提出了基于动态输出反馈的故障调节设计方案，有效地避免了基于观测器的状态反馈容错控制器的设计难点。同时，将此研究结果推广到离散系统，得到了离散系统的故障估计和调节设计方法。
然后，在FFEO设计基础上研究了一种降阶故障估计观测器(RFEO)方法，基于此设计了基于静态输出反馈的故障调节。这种RFEO保留了FFEO较为宽广的应用范围，而且由RFEO推出的在线故障估计子可以包含系统当前的输出信息以提升故障估计的性能。然后，基于松弛矩阵方法，提出了一种基于静态输出反馈的故障调节方案。进一步，将连续系统的研究结果推广到离散系统，得到了相应的离散系统故障估计和调节研究结果。
进一步，针对现阶段基于Takagi-Sugeno(T-S)模糊模型的非线性系统故障估计和调节鲜有研究的现状，将提出的故障估计和调节设计方法推广到了基于T-S模糊模型的非线性系统，给出了T-S模糊模型的故障估计和调节设计方法。我们的研究涉及到了连续、离散系统的故障估计和调节，丰富了该领域的研究内容。
最后，为了验证提出理论方法的实用价值，将提出的部分理论应用到了三自由度直升机飞控平台。给出的故障估计设计方法可以实时在线估计出发生的执行器故障，基于在线的故障估计值，故障调节方案能够恢复系统的性能。实验结果表明了取出的研究结果对于提高飞控系统可靠性和安全性等研究具有一定的理论参考价值，且具有较为广泛的应用前景。
Due to the increasing security and reliability demand of actual industrial process control systems, thestudy on fault diagnosis and fault tolerant control of dynamic systems has received considerableattention. Fault accommodation is one of effective methods that can be used to enhance systemstability and reliability, so it has been widely and in-depth studied and become a hot topic in recentyears. Fault detection is used to monitor whether a fault occurs, which is the first step in faultaccommodation. On the basis of fault detection, fault estimation is utilized to determine online themagnitude of the fault, which is a very important step because the additional controller is designedusing the fault estimate. Compared with fault detection, the design difficulties of fault estimationwould increase a lot, so the study on fault estimation and accommodation is very challenging.Although there has been some study results on fault estimation and accommodation for dynamicsystems, the common methods at the present stage have design difficulties, which limit applications ofrespective design approaches. Therefore, the problems of fault estimation and accommodation areneeded to be in-depth studied. This dissertation studies observer-based fault estimation andaccommodation for dynamic systems, and establishes a systemic and comprehensive framework offault estimation and accommodation for continuous/discrete-time systems. Main contributions of thisdissertation are as follows:
Firstly, for the conventional adaptive fault estimation (CAFE) algorithm, the performance of faultestimation can not be met, a novel fast adaptive fault estimation (FAFE) algorithm is proposed, whichevidently enhances the fault performance, including rapidity and accuracy. Then, the proof process isimproved to eliminate the strict equation constraint by using inequality transform. Furthermore, theproposed FAFE algorithm is extended to time-delay systems. Based on the slack-matrix design idea,fault estimation of fast time-varying time-delay systems is studied to deal with the difficulty that theCAFE algorithm can only be used in slow time-varying time-delay systems, and fault estimation ofneutral delay systems is addressed to treat the difficulty of the CAFE algorithm can not be used insuch systems.
Secondly, for a class of specific faults of loss of actuator effectiveness, a fast fault estimationalgorithm for such kind of faults is proposed. Meanwhile, based on the on-line obtained fault estimate,a fault accommodation scheme is proposed. Note that, the presented fault estimation observer andfault accommodation are designed separately such that the design process can be greatly simplified.When faults of loss of actuator effectiveness occur, the provided fault accommodation scheme canguarantee the asymptotic stability of the whole system.
Thirdly, for adaptive observer design, the error dynamics is needed to satisfy the strictly positive real (SPR) condition, a novel full-order fault estimation observer (FFEO) design is proposed, and adynamic output feedback-based fault accommodation is provided. The FFEO possesses widerapplication scopes compared with adaptive observer. Then, a dynamical output feedback-based faultaccommodation design is proposed to avoid design difficulties caused by observer-based statefeedback fault tolerant control. Meanwhile, the results on continuous-time systems are extended todiscrete-time systems, and it is obtained that the corresponding results of discrete-time systems.
Fourthly, on the basis of FFEO design, a reduced-order fault estimation observer (RFEO) approach isstudied, and a static output feedback-based fault accommodation is provided. The RFEO possesses thewider application scope of the FFEO, and the on-line fault estimator generated by the RFEO containsthe current output information to enhance the performance of fault estimation. Then, based on theslack-matrix method, a static output feedback-based fault accommodation is proposed. Furthermore,the obtained research results of continuous-time systems are extended to discrete-time systems, and theresults of fault estimation and accommodation for corresponding discrete-time systems are derived.
Fifthly, for the research status that the study of fault estimation and accommodation forTakagi-Sugeon (T-S) fuzzy models based nonlinear systems estimation is very few, the fault estimationand accommodation approaches that are proposed in above chapters are extended to T-S fuzzy modelsbased nonlinear systems, the design of fault estimation and accommodation for T-S fuzzy models areobtained. Our studies involve continuous and discrete-time systems, and enrich the content of this studyfield.
Finally, in order to verify the practical value of the proposed theoretical methods, a part of theproposed theories is applied to the three degrees of freedom helicopter flight control platform. Thegiven fault estimation design can real-time online estimate actuator faults, and based on the online faultestimate, the designed fault accommodation restores the system performances. Experimental resultsshow that the obtained research results to improve the flight control system reliability and security havesome theoretical reference value, and have broad application prospects.
首先，针对传统自适应故障估计(CAFE)算法难以满足故障估计性能问题，提出了一种新的快速自适应故障估计(FAFE)算法，显著提升了故障估计的性能，包括快速性和准确性。然后，对其证明过程进行了改进，通过不等式变换消除了存在的等式约束。进一步，将提出的FAFE算法推广到了时滞系统。基于松弛矩阵设计思想，研究了快时变时滞系统的故障估计，解决了CAFE算法仅适用于慢时变时滞系统的设计难点，并且研究了中立时滞系统的故障估计，解决了CAFE算法难以应用于此类系统的技术难点。
其次，针对一类特定的执行器损伤故障，提出了基于自适应观测器的快速执行器损伤故障估计算法。同时，基于在线获取的故障估计值，给出了一种故障调节设计方案。值得注意的是，提出的故障估计观测器和故障调节是分开设计的，南南简化了设计过程。当执行器发生损伤故障时，给出的故障调节方案可以确保整个系统是渐近稳定的。
再次，针对自适应观测器需要误差系统满足严格正实(SPR)条件，提出了一种全阶故障估计观测器(FFEO)设计方法，并基于此设计了基于动态输出反馈的故障调节。这种观测器设计比自适应观测器具有更广的应用范围。进一步，提出了基于动态输出反馈的故障调节设计方案，有效地避免了基于观测器的状态反馈容错控制器的设计难点。同时，将此研究结果推广到离散系统，得到了离散系统的故障估计和调节设计方法。
然后，在FFEO设计基础上研究了一种降阶故障估计观测器(RFEO)方法，基于此设计了基于静态输出反馈的故障调节。这种RFEO保留了FFEO较为宽广的应用范围，而且由RFEO推出的在线故障估计子可以包含系统当前的输出信息以提升故障估计的性能。然后，基于松弛矩阵方法，提出了一种基于静态输出反馈的故障调节方案。进一步，将连续系统的研究结果推广到离散系统，得到了相应的离散系统故障估计和调节研究结果。
进一步，针对现阶段基于Takagi-Sugeno(T-S)模糊模型的非线性系统故障估计和调节鲜有研究的现状，将提出的故障估计和调节设计方法推广到了基于T-S模糊模型的非线性系统，给出了T-S模糊模型的故障估计和调节设计方法。我们的研究涉及到了连续、离散系统的故障估计和调节，丰富了该领域的研究内容。
最后，为了验证提出理论方法的实用价值，将提出的部分理论应用到了三自由度直升机飞控平台。给出的故障估计设计方法可以实时在线估计出发生的执行器故障，基于在线的故障估计值，故障调节方案能够恢复系统的性能。实验结果表明了取出的研究结果对于提高飞控系统可靠性和安全性等研究具有一定的理论参考价值，且具有较为广泛的应用前景。
Due to the increasing security and reliability demand of actual industrial process control systems, thestudy on fault diagnosis and fault tolerant control of dynamic systems has received considerableattention. Fault accommodation is one of effective methods that can be used to enhance systemstability and reliability, so it has been widely and in-depth studied and become a hot topic in recentyears. Fault detection is used to monitor whether a fault occurs, which is the first step in faultaccommodation. On the basis of fault detection, fault estimation is utilized to determine online themagnitude of the fault, which is a very important step because the additional controller is designedusing the fault estimate. Compared with fault detection, the design difficulties of fault estimationwould increase a lot, so the study on fault estimation and accommodation is very challenging.Although there has been some study results on fault estimation and accommodation for dynamicsystems, the common methods at the present stage have design difficulties, which limit applications ofrespective design approaches. Therefore, the problems of fault estimation and accommodation areneeded to be in-depth studied. This dissertation studies observer-based fault estimation andaccommodation for dynamic systems, and establishes a systemic and comprehensive framework offault estimation and accommodation for continuous/discrete-time systems. Main contributions of thisdissertation are as follows:
Firstly, for the conventional adaptive fault estimation (CAFE) algorithm, the performance of faultestimation can not be met, a novel fast adaptive fault estimation (FAFE) algorithm is proposed, whichevidently enhances the fault performance, including rapidity and accuracy. Then, the proof process isimproved to eliminate the strict equation constraint by using inequality transform. Furthermore, theproposed FAFE algorithm is extended to time-delay systems. Based on the slack-matrix design idea,fault estimation of fast time-varying time-delay systems is studied to deal with the difficulty that theCAFE algorithm can only be used in slow time-varying time-delay systems, and fault estimation ofneutral delay systems is addressed to treat the difficulty of the CAFE algorithm can not be used insuch systems.
Secondly, for a class of specific faults of loss of actuator effectiveness, a fast fault estimationalgorithm for such kind of faults is proposed. Meanwhile, based on the on-line obtained fault estimate,a fault accommodation scheme is proposed. Note that, the presented fault estimation observer andfault accommodation are designed separately such that the design process can be greatly simplified.When faults of loss of actuator effectiveness occur, the provided fault accommodation scheme canguarantee the asymptotic stability of the whole system.
Thirdly, for adaptive observer design, the error dynamics is needed to satisfy the strictly positive real (SPR) condition, a novel full-order fault estimation observer (FFEO) design is proposed, and adynamic output feedback-based fault accommodation is provided. The FFEO possesses widerapplication scopes compared with adaptive observer. Then, a dynamical output feedback-based faultaccommodation design is proposed to avoid design difficulties caused by observer-based statefeedback fault tolerant control. Meanwhile, the results on continuous-time systems are extended todiscrete-time systems, and it is obtained that the corresponding results of discrete-time systems.
Fourthly, on the basis of FFEO design, a reduced-order fault estimation observer (RFEO) approach isstudied, and a static output feedback-based fault accommodation is provided. The RFEO possesses thewider application scope of the FFEO, and the on-line fault estimator generated by the RFEO containsthe current output information to enhance the performance of fault estimation. Then, based on theslack-matrix method, a static output feedback-based fault accommodation is proposed. Furthermore,the obtained research results of continuous-time systems are extended to discrete-time systems, and theresults of fault estimation and accommodation for corresponding discrete-time systems are derived.
Fifthly, for the research status that the study of fault estimation and accommodation forTakagi-Sugeon (T-S) fuzzy models based nonlinear systems estimation is very few, the fault estimationand accommodation approaches that are proposed in above chapters are extended to T-S fuzzy modelsbased nonlinear systems, the design of fault estimation and accommodation for T-S fuzzy models areobtained. Our studies involve continuous and discrete-time systems, and enrich the content of this studyfield.
Finally, in order to verify the practical value of the proposed theoretical methods, a part of theproposed theories is applied to the three degrees of freedom helicopter flight control platform. Thegiven fault estimation design can real-time online estimate actuator faults, and based on the online faultestimate, the designed fault accommodation restores the system performances. Experimental resultsshow that the obtained research results to improve the flight control system reliability and security havesome theoretical reference value, and have broad application prospects.
引文
[1]闻新,张洪钺,周露.控制系统的故障诊断和容错控制.北南:机械工业出版社,1998.
[2] J. Chen and R. J. Patton. Robust Model-based Fault Diagnosis for Dynamic Systems. Boston:Kluwer Academic Publishers,1999.
[3]周东华,叶银忠.现代故障诊断与容错控制.北南:清华南学出版社,2000.
[4]胡昌华,许华龙.控制系统故障诊断与容错控制的分析和设计.北南:国防工业出版社,2000.
[5]王仲生.智能容错技术及应用.北南:国防工业出版社,2002.
[6] M. Blanke, M. Kinnaert, J. Lunze, and M. Staroswiecki. Diagnosis and Fault-TolerantControl. Berlin Heidelberg: Springer Verlag,2006.
[7] S. X. Ding. Model-based Fault Diagnosis Techniques: Design Schemes, Algorithms, andTools. Berlin Heidelberg: Springer Verlag,2008.
[8]姜斌,冒泽慧,杨浩,张友民.控制系统的故障诊断与故障调节.北南:国防工业出版社,2009.
[9]周东华,胡艳艳.动态系统的故障诊断技术.自动化学报,2009,35(6):748-758.
[10]杨光红,王恒,李霄剑.基于模型的线性控制系统故障诊断方法.北南:科学出版社,2010.
[11] S. X. Ding. Integrated design of feedback controllers and fault detectors. Annual Reviews inControl,2009,33(2):124-135.
[12] I. Hwang, S. Kim, Y. Kim, and C. E. Seah. A survey of fault detection, isolation, andreconfiguration methods. IEEE Transactions on Control Systems Technology,2010,18(3):636-653.
[13] M. Blanke, M. Staroswiecki, and N. E. Wu. Concepts and methods in fault-tolerant control.Proceedings of the2001American Control Conference, Arlington:IEEE,2001:2606-2620.
[14] G.-H. Yang, J. L. Wang, and Y. C. Soh. Reliable H2controller design for linear systems.Automatica,2001,37(5):717-725.
[15] G. Tao, S. Chen, and S. M. Joshi. An adaptive actuator failure compensation controller usingoutput feedback. IEEE Transactions on Automatic Control,2002,47(3):506-511.
[16] Y. Zhang and J. Jiang. Bibliographical review on reconfigurable fault-tolerant control systems.Annual Reviews in Control,2008,32(2):229-252.
[17] M. Staroswiecki. On fault handling in control systems. International Journal of Control,Automation, and Systems,2008,6(3):296-305.
[18] C. Edwards, S. K. Spurgeon, and R. J. Patton. Sliding mode observers for fault detection andisolation. Automatica,2000,36(4):541-553.
[19] X. G. Yan, C. Edwards, and S. K. Spurgeon. Output feedback sliding mode control fornon-minimum phase systems with non-linear disturbances. International Journal of Control,2004,77(15):1353-1361.
[20] W. Chen and M. Saif. Observer-based strategies for actuator fault detection, isolation andestimation for certain class of uncertain nonlinear systems. IET Control Theory andApplications,2007;6(1):1672-1680.
[21] W. Chen and M. Saif. A sliding mode observer-based strategy for fault detection, isolation,and estimation in a class of Lipschitz nonlinear systems. International Journal of SystemsScience,2007,38(12):943-955.
[22] S. K. Spurgeon. Sliding mode observers: A survey. International Journal of Systems Science,2008,39(8):751-764.
[23] J. Stoustrup and H. H. Niemann. Fault estimation-a standard problem approach. InternationalJournal of Robust and Nonlinear Control,2002,12(8):649-673.
[24] A. Stoorvogel, H. H. Niemann, A. Saberi, and P. Sannuti. Optimal fault signal estimation.International Journal of Robust and Nonlinear Control,2002,12(8):697-727.
[25] E. G. Nobrega, M. O. Abdalla, and K. M. Grigoriadis. Robust fault estimation of uncertainsystems using an LMI-based approach. International Journal of Robust and Nonlinear Control,2008,18(18):1657-1680.
[26] W. Chen and M. Saif. An iterative learning observer-based approach to fault detection andaccommodation in nonlinear systems. Proceedings of the40th IEEE Conference on Decisionand Control, Orlando:IEEE,2001:4469-4474.
[27] W. Chen and M. Saif. An iterative learning observer for fault detection and accommodation innonlinear time-delay systems. International Journal of Robust and Nonlinear Control,2006,16(1):1-19.
[28] B. Shafai, C. T. Pi, and S. Nork. Simultaneous disturbance attenuation and fault detectionusing proportional integral observers. Proceedings of the American Control Conference,Anchorage:IEEE,2002:1647-1649.
[29] D. Koenig and S. Mammar. Design of proportional-integral observer for unknown inputdescriptor systems. IEEE Transactions on Automatic Control,2002,47(12):2057-2062.
[30] Z. Gao and S. X. Ding. Fault estimation and fault-tolerant control for descriptor systems viaproportional, multiple-integral and derivative observer design. IET Control Theory andApplications,2007,1(5):1208-1218.
[31] H. Wang and S. Daley. Actuator fault diagnosis: An adaptive observer-based technique. IEEETransactions on Automatic Control,1996,41(7):1073-1078.
[32] B. Jiang, J. L. Wang, and Y. C. Soh. An adaptive technique for robust diagnosis of faults withindependent effects on system outputs. International Journal of Control,2002,75(11):792-802.
[33] H. Wang and L. Shen. Fault detection and estimation for nonlinear systems with linear outputstructure. International Journal of Adaptive Control and Signal Processing,2005,19(4):267-279.
[34] B. Jiang, M. Staroswiecki, and V. Cocquempot. Fault accommodation for nonlinear dynamicsystems. IEEE Transactions on Automatic Control,2006,51(9):1578-1583.
[35] X. Zhang, M. M. Polycarpou, and T. Parisini. Fault diagnosis of a class of nonlinear uncertainsystems with Lipschitz nonlinearities using adaptive estimation. Automatica,2010,46(2):290-299.
[36] K. Gu, V. L. Kharitonov, and J. Chen. Stability of Time-Delay Systems. Berlin:Springer-Verlag,2003.
[37] E. Fridman and U. Shaked. Delay-dependent stability and H∞control: Constant andtime-varying delays. International Journal of Control,2003,76(1):48-60.
[38] Y. He, M. Wu, J. H. She, and G. P. Liu. Delay-dependent robust stability criteria for uncertainneutral systems with mixed delays. Systems and Control Letters,2004,51(1):57-65.
[39] Q. L. Han. Robust stability for a class of linear systems with time-varying delay and nonlinearperturbations. Computers and Mathematics with Applications,2004,47(8,9):1201-1209.
[40] Y. S. Moon, P. Park, W. H. Kwon, and Y. S. Lee. Delay-dependent robust stabilizationofuncertain state-delayed systems. International Journal of Control,2001,74(14):1447-1455.
[41] S. Xu, J. Lam and Y. Zou. Delay-dependent guaranteed cost control for uncertain systemswith state and input delays. IEE Proceedings Control Theory and Applications,2006,153(3):307-313.
[42] H. Gao and T. Chen. New results on stability of discrete-time systems with time-varying statedelay. IEEE Transactions on Automatic Control,2007,52(2):328-334.
[43] Y. He, Q. G. Wang, C. Lin, and M. Wu. Delay-range-dependent stability for systems withtime-varying delay. Automatica,2007,43(2):371-376.
[44] S. Xu and J. Lam. On equivalence and efficiency of certain stability criteria for time-delaysystems. IEEE Transactions on Automatic Control,2007,52(1):95-101.
[45] B. Yang and H. Fang. Forced consensus in networks of double integrator systems withdelayed input. Automatica,2010,46(3):629-632.
[46] B. Jiang, M. Staroswiecki, and V. Cocquempot. Fault identification for a class of time-delaysystems. Proceedings of the American Control Conference, Anchorage:IEEE,2002:2239-2244.
[47] S. K. Nguang, P. Shi, and S. Ding. Delay-dependent fault estimation for uncertain time-delaynonlinear systems: An LMI approach. International Journal of Robust and Nonlinear Control,2006,16(18):913-933.
[48] Z. Gao and S. X. Ding. State and disturbance estimator for time-delay systems withapplication to fault estimation and signal compensation. IEEE Transactions on SignalProcessing,2007,55(12):5541-5551.
[49] H. Wang and J. Lam. Robust fault detection for uncertain discrete-time systems. Journal ofGuidance, Control, and Dynamics,2002,25(2):291-301.
[50] P. Zhang, S. X. Ding, G. Z. Wang, and D. H. Zhou. Fault detection of linear discrete-timeperiodic systems. IEEE Transactions on Automatic Control,2005,50(2):239-244.
[51] H. Fang, H. Ye and M. Zhong. Fault diagnosis of networked control systems. Annual Reviewsin Control,2007,31(1):55-68.
[52] M. Zhong, H. Ye, S. X. Ding, and G. Wang. Observer-based fast rate fault detection for a classof multirate sampled-data systems. IEEE Transactions on Automatic Control,2007,52(3):520-525.
[53] L. Guo, L. Yin, H. Wang, and T. Chai. Entropy optimization filtering for fault isolation ofnonlinear non-gaussian stochastic systems. IEEE Transactions on Automatic Control,2009,54(4):804-810.
[54] A. Ingimundarson, J. M. Bravo, V. Puig, T. Alamo, and P. Guerra1. Robust fault detectionusing zonotope-based set-membership. International Journal of Adaptive Control and SignalProcessing,2009,23(4):311-330.
[55] H. Wang and G. H. Yang. Simultaneous fault detection and control for uncertain lineardiscrete-time systems. IET Control Theory and Applications2009,3(5):583-594.
[56] P. Zhang and S. X. Ding. Influence of sampling period on a class of optimal fault-detectionperformance. IEEE Transactions on Automatic Control,2009,54(6):1396-1402.
[57] S. Longhi and A. Monteriù. Fault detection for linear periodic systems using a geometricapproach. IEEE Transactions on Automatic Control,2009,54(7):1637-1643.
[58] M. Simandl and I. Puncochar. Active fault detection and control: Unified formulation andoptimal design. Automatica,2009,45(9):2052-2059.
[59] P. Zhang and S. X. Ding. Influence of sampling period on a class of optimal fault-detectionperformance. IEEE Transactions on Automatic Control,2009,54(6):1396-1402.
[60] M. Zhong, S. X. Ding, and E. L. Ding. Optimal fault detection for linear discrete time-varyingsystems. Automatica.2010,46(8):1395-1400.
[61] M. Saif. Robust discrete time observer with application to fault diagnosis. IEE ProceedingsControl Theory and Applications,1998,145(3):353-357.
[62] B. Jiang and F. N. Chowdhury. Fault estimation and accommodation for linear MIMOdiscrete-time systems. IEEE Transactions on Control Systems Technology,2005,13(3):493-499.
[63] J. L. Chang. Applying discrete-time proportional integral observers for state and disturbanceestimations. IEEE Transactions on Automatic Control,2006,51(5):814-818.
[64] Z. Gao, T. Breikin, and H. Wang. Discrete-time proportional and integral observer andobserver-based controller for systems with both unknown input and output disturbances.Optimal Control Applications and Methods,2008,29(3):171-189.
[65] D. Theilliol, H. Noura, and J.-C. Ponsart. Fault diagnosis and accommodation of a three-tanksystem based on analytical redundancy. ISA Transactions,2002,41(3):365-382.
[66] R. J. Patton. Fault-tolerant control: the1997situation. Proceeding of IFAC Symposium onFault Detection Supervision Safety for Processes (SAFEPROCESS), Hull:IFAC,1997:1033-1055.
[67] M. M. Polycarpou and A. J. Helmicki. Automated fault detection and automated faultdetection and accommodation: A learning systems approach. IEEE Transactions on Systems,Man, and Cybernetics,1995,25(11):1447-1458.
[68] M. Staroswieck, H. Yang, and B. Jiang. Progressive accommodation of parametric faults inlinear quadratic control. Automatica,2007,43(12):2070-2076.
[69] G. G. Yen and L.-W. Ho. Online multiple-model-based fault diagnosis and accommodation.IEEE Transactions on Industrial Electronics,2003,50(2):296-312.
[70] D. Theilliol, H. Noura, and D. Sauter. Fault-tolerant control method for actuator andcomponent faults. Proceedings of the37th IEEE Conference on Decision and Control,Tampa:IEEE,1998:604-609.
[71] D. Theilliol, H. Noura, and J.-C. Ponsart. Fault diagnosis and accommodation of a three-tanksystem based on analytical redundancy. ISA Transactions,2002,41(3):365-382.
[72]俞立.鲁棒控制--线性矩阵不等式处理方法.北南:清华南学出版社,2002.
[73] M. Grant and S. Boyd. CVX: Matlab software for disciplined convex programming, version1.21. http://cvxr.com/cvx, July2010.
[74] M. Grant and S. Boyd. Graph implementations for nonsmooth convex programs. RecentAdvances in Learning and Control (a tribute to M. Vidyasagar), V. Blondel, S. Boyd, and H.Kimura, editors, pages95--110, Lecture Notes in Control and Information Sciences, Springer,2008. http://stanford.edu/~boyd/graph_dcp.html.
[75] K. Zhang, B. Jiang, and V. Cocquempot. Adaptive observer-based fast fault estimation.International Journal of Control, Automation, and Systems,2008,6(3):320-326.
[76] L. Xie. Output feedback H∞control of systems with parameter uncertainty. InternationalJournal of Control,1996,63(4):741-750.
[77] M. Corless and J. Tu. State and input estimation for a class of uncertain systems. Automatica,1998,34(6):757-764.
[78] H. Alwi and C. Edwards. Robust sensor fault estimation for tolerant control of a civil aircraftusing sliding modes. Proceedings of the American Control Conference. Minneapolis: IEEE,2006:5704-5709.
[79] Y. Y. Cao and P. M. Frank. Analysis and synthesis of nonlinear time-delay systems via fuzzycontrol approach. IEEE Transactions on Fuzzy Systems,2000,8(2):200-211.
[80] C. Lin, Q. G. Wang, and T. H. Lee. Stabilization of uncertain fuzzy time-delay systems viavariable structure control approach. IEEE Transactions on Fuzzy Systems,2005,13(6):787-798.
[81] F. Liao, J. L. Wang, and G.-H. Yang. Reliable robust flight tracking control: An LMI approach.IEEE Transactions on Control Systems Technology,2002,10(1):76-89.
[82] J. D. Boskovic, and R. K. Mehra. Multiple model adaptive flight control scheme foraccommodation of actuator failures. Journal of Guidance, Control, and Dynamics,2002,25(4):712-724.
[83] G. Tao, S. Chen, and S. M. Joshi. An adaptive actuator failure compensation controller usingoutput feedback. IEEE Transactions on Automatic Control,2002,47(3):506-511.
[84] Y. Zhang and J. Jiang. Fault tolerant control system design with explicit consideration ofperformance degradation. IEEE Transactions on Aerospace and Electronic Systems,2003,39(3):838-848.
[85] G. Tao, S. Chen, X. Tang, and S. M. Joshi. Adaptive Control of Systems with ActuatorFailures. London: Springer Verlag,2004.
[86] D. Ye and G.-H. Yang. Adaptive fault-tolerant tracking control against actuator faults withapplication to flight control. IEEE Transactions on Control Systems Technology,2006,14(6):1088-1096.
[87] C. Edwards, T. Lombaerts, and H. Smaili. Fault Tolerant Flight Control: A BenchmarkChallenge. Berlin Heidelberg: Springer Verlag,2010.
[88] K. Vijayaraghavan, R. Rajamani, and J. Bokor. Quantitative fault estimation for a class ofnon-linear systems. International Journal of Control,2007,80(1):64-74.
[89] K. Zhang, B. Jiang, and P. Shi. Fast fault estimation and accommodation for dynamicalsystems. IET Control Theory and Applications,2009,3(2):189-199.
[90] G. Garcia and J. Bernussou. Pole assignment for uncertain systems in a specified disk by statefeedback. IEEE Transactions on Automatic Control,1995,40(1):184-190.
[91] P. Gahinet and P. Apkarian. A linear matrix inequality approach to H∞control. InternationalJournal of Robust and Nonlinear Control,1994,4(4):421-448.
[92] K. Zhou and J. C. Doyle. Essentials of Robust Control. New Jersey: Prentice Hall,1998.
[93] M. C. de Oliveira, J. C. Geromel, and J. Bernussou. Extended H2and H∞normcharacterizations and controller parametrizations for discrete-time systems. InternationalJournal of Control,2002,75(9):666-679.
[94] W. Xie. Multi-objective H∞/α-stability controller synthesis of LTI systems. IET ControlTheory and Applications,2008,2(1):51-55.
[95] X. Du and G.-H. Yang. New characterisations of positive realness and static output feedbackcontrol of discrete-time systems. International Journal of Control,2009,82(8):1485-1495.
[96] J. Lam and S. Zhou. Dynamic output feedback H∞control of discrete-time fuzzy systems: Afuzzy-basis-dependent Lyapunov function approach. International Journal of Systems Science,2007,38(1):25-37.
[97] J. Dong and G.-H. Yang. Dynamic output feedback control synthesis for continuous-time T-Sfuzzy systems via a switched fuzzy control scheme. IEEE Transactions on Systems, Man, andCybernetics-Part B: Cybernetics,2008,38(4):1166-1175.
[98] Y. M. Zhang and J. Jiang. Integrated active fault-tolerant control using IMM approach. IEEETransactions on Aerospace and Electronic Systems,2001,37(4):1221-1235.
[99] D. Huang and S. K. Nguang. Robust H∞static output feedback control of fuzzy systems: AnILMI approach. IEEE Transactions on Systems, Man, and Cybernetics Part B: Cybernetics,2006,36(1):216-222.
[100] Y.-Y. Cao and Y.-X. Sun. Static output feedback simultaneous stabilization: ILMI approach.International Journal of Control,1998,70(5):803-814.
[101] C. A. R. Crusius and A. Trofino. Sufficient LMI conditions for output feedback controlproblems. IEEE Transactions on Automatic Control,1999,44(5):1053-1057.
[102] W. Chang, J. B. Park, Y. H. Joo, and G. Chen. Static output-feedback fuzzy controller forchen's chaotic system with uncertainties. Information Sciences,2003,151:227-244.
[103] J.-C. Lo and M.-L. Lin. Robust H∞nonlinear control via fuzzy static output feedback. IEEETransactions on Circuits and Systems I: Fundamental Theory and Applications,2003,50(11):1494-1502.
[104] S. K. Mudge and R. J. Patton. Analysis of the technique of robust eigenstructure assignmentwith application to aircraft control. IEE Proceedings-D Control Theory and Applications,1988,135(4):275-281.
[105] T. Takagi and M. Sugeno. Fuzzy identification of systems and its application to modeling andcontrol. IEEE Transactions on Systems, Man, and Cybernetics,1985,15(1):116-132.
[106] X. J. Ma, Z. Q. Sun, and Y. Y. He. Analysis and design of fuzzy controller and fuzzy observer.IEEE Transactions on Fuzzy Systems,1998,6(1):41-51.
[107] K. Tanaka and H. O. Wang, Fuzzy Control Systems Design and Analysis: An Linear MatrixInequality Approach. New York:Wiley,2001.
[108] H. Zhang and Y. Quan. Modeling, identification, and control of a class of nonlinear systems.IEEE Transactions on Fuzzy Systems,2001,9(2):349–354.
[109] X.-J. Ma and Z.-Q. Sun. Analysis and design of fuzzy reduced-dimensional observer andfuzzy functional observer. Fuzzy Sets and Systems,2001,120(1):35-63.
[110] Y. Y. Cao and P. M. Frank. Stability analysis and synthesis of nonlinear time-delay systems vialinear Takagi-Sugeno fuzzy models. Fuzzy Sets and Systems,2001,124(2):213-229.
[111] S. K. Nguang and P. Shi. H∞fuzzy output feedback control design for nonlinear systems: AnLMI approach. IEEE Transactions on Fuzzy Systems,2003,11(3):331-340.
[112] H.-N. Wu. Reliable LQ fuzzy control for continuous-time nonlinear systems with actuatorfaults. IEEE Transactions on Systems, Man, and Cybernetics-Part B: Cybernetics,2004,34(4):1743-1752.
[113] A. Sala, T. M. Guerra, and R.t Babuska. Perspectives of fuzzy systems and control. Fuzzy Setsand Systems,2005,156(3):432-444.
[114] H. Zhang and D. Liu. Fuzzy Modeling and Fuzzy Control. Boston: Birkhuser,2006.
[115] G. Feng. A survey on analysis and design of model-based fuzzy control systems. IEEETransactions on Fuzzy Systems,2006,14(5):676-697.
[116] H. H. Choi. LMI-based nonlinear fuzzy observer-controller design for uncertain MIMOnonlinear systems. IEEE Transactions on Fuzzy Systems,2007,15(5):956-971.
[117] H. Zhang and Y. Wang and D. Liu. Delay-dependent guaranteed cost control for uncertainstochastic fuzzy systems with multiple time delays. IEEE Transactions on Systems, Man, andCybernetics--Part B: Cybernetics,2008,38(1):126-140.
[118] C.-S. Tseng. A novel approach to H∞decentralized fuzzy-observer-based fuzzy controldesign for nonlinear interconnected systems. IEEE Transactions on Fuzzy Systems,2008,16(5):1337-1350.
[119] J. Dong and G.-H. Yang. Dynamic output feedback H∞control synthesis for discrete-timeT-S fuzzy systems via switching fuzzy controllers. Fuzzy Sets and Systems,2009,160(4):482-499.
[120] R. J. Patton, J. Chen, and C. J. Lopez-Toribio. Fuzzy observers for non-linear dynamicsystems fault diagnosis. Proceedings of the IEEE Conference on Decision and Control,Tampa:IEEE,1998:84-89.
[121] C. J. Lopez-Toribio and R. J. Patton. Takagi-Sugeno fuzzy fault-tolerant control for anon-linear system. Proceedings of the IEEE Conference on Decision and Control,Phoenix:IEEE,1999:4368-4373.
[122] S. K. Nguang, P. Shi, and S. X. Ding. Fault detection for uncertain fuzzy systems: An LMIapproach. IEEE Transactions on Fuzzy Systems,2007,15(6):1251-1262.
[123] L. Wu and D. W. C. Ho. Fuzzy filter design for Ito stochastic systems with application tosensor fault detection. IEEE Transactions on Fuzzy Systems,2009,17(1):233-242.
[124] H. Gao, Y. Zhao, and T. Chen. H∞fuzzy control of nonlinear systems under unreliablecommunication links. IEEE Transactions on Fuzzy Systems,2009,17(2):265-273.
[125] Y. Zheng, H. Fang, and H. O. Wang. Takagi–Sugeno fuzzy-model-based fault detection fornetworked control systems with markov delays. IEEE Transactions on Systems, Man, andCybernetics-Part B: Cybernetics,2006,36(4):924-929.
[126] J. Li, H. O. Wang, D. Niemann, and K. Tanaka. Dynamic parallel distributed compensation forTakagi-Sugeno fuzzy systems: An LMI approach. Information Sciences,2000,123(3-4):201-221.
[127] H. Gao and T. Chen. Stabilization of nonlinear systems under variable sampling: A fuzzycontrol approach. IEEE Transactions on Fuzzy Systems,2007,15(5):972-983
[128] J. Dong and G.-H. Yang. Static output feedback H∞control of a class of nonlineardiscrete-time systems. Fuzzy Sets and Systems,2009,160(19):2844-2859.
[129] K. Tanaka and M. Sano. A robust stabilization problem of fuzzy control systems anditsapplication to backing up control of a truck-trailer. IEEE Transactions on Fuzzy Systems,1994,2(2):119-134.
[130] G. Feng and J. Ma. Quadratic stabilization of uncertain discrete-time fuzzy dynamic systems.IEEE Transactions on Circuits and Systems I: Fundamental Theory and Applications,2001,48(11):1337-1344.
[131]杨一栋.直升机飞行控制.北南:国防工业出版社,2007.
[132]曹义华.直升机飞行力学.北南:北南南南南南南学出版社,2005.
[133]黄一敏,孙传伟,高正.直升机飞行控制系统的快速原型设计.飞行力学,2003,20(1):5-9.
[134]葛金来.三自由度直升机实验系统的控制策略研究.[硕士学位论文].济南：山东南学,2010.
[135] Quanser Inc.3-DOF Helicopter Reference Manual. Docunment Number644/Revision2.11,Canada: Quanser Inc,2007.
[2] J. Chen and R. J. Patton. Robust Model-based Fault Diagnosis for Dynamic Systems. Boston:Kluwer Academic Publishers,1999.
[3]周东华,叶银忠.现代故障诊断与容错控制.北南:清华南学出版社,2000.
[4]胡昌华,许华龙.控制系统故障诊断与容错控制的分析和设计.北南:国防工业出版社,2000.
[5]王仲生.智能容错技术及应用.北南:国防工业出版社,2002.
[6] M. Blanke, M. Kinnaert, J. Lunze, and M. Staroswiecki. Diagnosis and Fault-TolerantControl. Berlin Heidelberg: Springer Verlag,2006.
[7] S. X. Ding. Model-based Fault Diagnosis Techniques: Design Schemes, Algorithms, andTools. Berlin Heidelberg: Springer Verlag,2008.
[8]姜斌,冒泽慧,杨浩,张友民.控制系统的故障诊断与故障调节.北南:国防工业出版社,2009.
[9]周东华,胡艳艳.动态系统的故障诊断技术.自动化学报,2009,35(6):748-758.
[10]杨光红,王恒,李霄剑.基于模型的线性控制系统故障诊断方法.北南:科学出版社,2010.
[11] S. X. Ding. Integrated design of feedback controllers and fault detectors. Annual Reviews inControl,2009,33(2):124-135.
[12] I. Hwang, S. Kim, Y. Kim, and C. E. Seah. A survey of fault detection, isolation, andreconfiguration methods. IEEE Transactions on Control Systems Technology,2010,18(3):636-653.
[13] M. Blanke, M. Staroswiecki, and N. E. Wu. Concepts and methods in fault-tolerant control.Proceedings of the2001American Control Conference, Arlington:IEEE,2001:2606-2620.
[14] G.-H. Yang, J. L. Wang, and Y. C. Soh. Reliable H2controller design for linear systems.Automatica,2001,37(5):717-725.
[15] G. Tao, S. Chen, and S. M. Joshi. An adaptive actuator failure compensation controller usingoutput feedback. IEEE Transactions on Automatic Control,2002,47(3):506-511.
[16] Y. Zhang and J. Jiang. Bibliographical review on reconfigurable fault-tolerant control systems.Annual Reviews in Control,2008,32(2):229-252.
[17] M. Staroswiecki. On fault handling in control systems. International Journal of Control,Automation, and Systems,2008,6(3):296-305.
[18] C. Edwards, S. K. Spurgeon, and R. J. Patton. Sliding mode observers for fault detection andisolation. Automatica,2000,36(4):541-553.
[19] X. G. Yan, C. Edwards, and S. K. Spurgeon. Output feedback sliding mode control fornon-minimum phase systems with non-linear disturbances. International Journal of Control,2004,77(15):1353-1361.
[20] W. Chen and M. Saif. Observer-based strategies for actuator fault detection, isolation andestimation for certain class of uncertain nonlinear systems. IET Control Theory andApplications,2007;6(1):1672-1680.
[21] W. Chen and M. Saif. A sliding mode observer-based strategy for fault detection, isolation,and estimation in a class of Lipschitz nonlinear systems. International Journal of SystemsScience,2007,38(12):943-955.
[22] S. K. Spurgeon. Sliding mode observers: A survey. International Journal of Systems Science,2008,39(8):751-764.
[23] J. Stoustrup and H. H. Niemann. Fault estimation-a standard problem approach. InternationalJournal of Robust and Nonlinear Control,2002,12(8):649-673.
[24] A. Stoorvogel, H. H. Niemann, A. Saberi, and P. Sannuti. Optimal fault signal estimation.International Journal of Robust and Nonlinear Control,2002,12(8):697-727.
[25] E. G. Nobrega, M. O. Abdalla, and K. M. Grigoriadis. Robust fault estimation of uncertainsystems using an LMI-based approach. International Journal of Robust and Nonlinear Control,2008,18(18):1657-1680.
[26] W. Chen and M. Saif. An iterative learning observer-based approach to fault detection andaccommodation in nonlinear systems. Proceedings of the40th IEEE Conference on Decisionand Control, Orlando:IEEE,2001:4469-4474.
[27] W. Chen and M. Saif. An iterative learning observer for fault detection and accommodation innonlinear time-delay systems. International Journal of Robust and Nonlinear Control,2006,16(1):1-19.
[28] B. Shafai, C. T. Pi, and S. Nork. Simultaneous disturbance attenuation and fault detectionusing proportional integral observers. Proceedings of the American Control Conference,Anchorage:IEEE,2002:1647-1649.
[29] D. Koenig and S. Mammar. Design of proportional-integral observer for unknown inputdescriptor systems. IEEE Transactions on Automatic Control,2002,47(12):2057-2062.
[30] Z. Gao and S. X. Ding. Fault estimation and fault-tolerant control for descriptor systems viaproportional, multiple-integral and derivative observer design. IET Control Theory andApplications,2007,1(5):1208-1218.
[31] H. Wang and S. Daley. Actuator fault diagnosis: An adaptive observer-based technique. IEEETransactions on Automatic Control,1996,41(7):1073-1078.
[32] B. Jiang, J. L. Wang, and Y. C. Soh. An adaptive technique for robust diagnosis of faults withindependent effects on system outputs. International Journal of Control,2002,75(11):792-802.
[33] H. Wang and L. Shen. Fault detection and estimation for nonlinear systems with linear outputstructure. International Journal of Adaptive Control and Signal Processing,2005,19(4):267-279.
[34] B. Jiang, M. Staroswiecki, and V. Cocquempot. Fault accommodation for nonlinear dynamicsystems. IEEE Transactions on Automatic Control,2006,51(9):1578-1583.
[35] X. Zhang, M. M. Polycarpou, and T. Parisini. Fault diagnosis of a class of nonlinear uncertainsystems with Lipschitz nonlinearities using adaptive estimation. Automatica,2010,46(2):290-299.
[36] K. Gu, V. L. Kharitonov, and J. Chen. Stability of Time-Delay Systems. Berlin:Springer-Verlag,2003.
[37] E. Fridman and U. Shaked. Delay-dependent stability and H∞control: Constant andtime-varying delays. International Journal of Control,2003,76(1):48-60.
[38] Y. He, M. Wu, J. H. She, and G. P. Liu. Delay-dependent robust stability criteria for uncertainneutral systems with mixed delays. Systems and Control Letters,2004,51(1):57-65.
[39] Q. L. Han. Robust stability for a class of linear systems with time-varying delay and nonlinearperturbations. Computers and Mathematics with Applications,2004,47(8,9):1201-1209.
[40] Y. S. Moon, P. Park, W. H. Kwon, and Y. S. Lee. Delay-dependent robust stabilizationofuncertain state-delayed systems. International Journal of Control,2001,74(14):1447-1455.
[41] S. Xu, J. Lam and Y. Zou. Delay-dependent guaranteed cost control for uncertain systemswith state and input delays. IEE Proceedings Control Theory and Applications,2006,153(3):307-313.
[42] H. Gao and T. Chen. New results on stability of discrete-time systems with time-varying statedelay. IEEE Transactions on Automatic Control,2007,52(2):328-334.
[43] Y. He, Q. G. Wang, C. Lin, and M. Wu. Delay-range-dependent stability for systems withtime-varying delay. Automatica,2007,43(2):371-376.
[44] S. Xu and J. Lam. On equivalence and efficiency of certain stability criteria for time-delaysystems. IEEE Transactions on Automatic Control,2007,52(1):95-101.
[45] B. Yang and H. Fang. Forced consensus in networks of double integrator systems withdelayed input. Automatica,2010,46(3):629-632.
[46] B. Jiang, M. Staroswiecki, and V. Cocquempot. Fault identification for a class of time-delaysystems. Proceedings of the American Control Conference, Anchorage:IEEE,2002:2239-2244.
[47] S. K. Nguang, P. Shi, and S. Ding. Delay-dependent fault estimation for uncertain time-delaynonlinear systems: An LMI approach. International Journal of Robust and Nonlinear Control,2006,16(18):913-933.
[48] Z. Gao and S. X. Ding. State and disturbance estimator for time-delay systems withapplication to fault estimation and signal compensation. IEEE Transactions on SignalProcessing,2007,55(12):5541-5551.
[49] H. Wang and J. Lam. Robust fault detection for uncertain discrete-time systems. Journal ofGuidance, Control, and Dynamics,2002,25(2):291-301.
[50] P. Zhang, S. X. Ding, G. Z. Wang, and D. H. Zhou. Fault detection of linear discrete-timeperiodic systems. IEEE Transactions on Automatic Control,2005,50(2):239-244.
[51] H. Fang, H. Ye and M. Zhong. Fault diagnosis of networked control systems. Annual Reviewsin Control,2007,31(1):55-68.
[52] M. Zhong, H. Ye, S. X. Ding, and G. Wang. Observer-based fast rate fault detection for a classof multirate sampled-data systems. IEEE Transactions on Automatic Control,2007,52(3):520-525.
[53] L. Guo, L. Yin, H. Wang, and T. Chai. Entropy optimization filtering for fault isolation ofnonlinear non-gaussian stochastic systems. IEEE Transactions on Automatic Control,2009,54(4):804-810.
[54] A. Ingimundarson, J. M. Bravo, V. Puig, T. Alamo, and P. Guerra1. Robust fault detectionusing zonotope-based set-membership. International Journal of Adaptive Control and SignalProcessing,2009,23(4):311-330.
[55] H. Wang and G. H. Yang. Simultaneous fault detection and control for uncertain lineardiscrete-time systems. IET Control Theory and Applications2009,3(5):583-594.
[56] P. Zhang and S. X. Ding. Influence of sampling period on a class of optimal fault-detectionperformance. IEEE Transactions on Automatic Control,2009,54(6):1396-1402.
[57] S. Longhi and A. Monteriù. Fault detection for linear periodic systems using a geometricapproach. IEEE Transactions on Automatic Control,2009,54(7):1637-1643.
[58] M. Simandl and I. Puncochar. Active fault detection and control: Unified formulation andoptimal design. Automatica,2009,45(9):2052-2059.
[59] P. Zhang and S. X. Ding. Influence of sampling period on a class of optimal fault-detectionperformance. IEEE Transactions on Automatic Control,2009,54(6):1396-1402.
[60] M. Zhong, S. X. Ding, and E. L. Ding. Optimal fault detection for linear discrete time-varyingsystems. Automatica.2010,46(8):1395-1400.
[61] M. Saif. Robust discrete time observer with application to fault diagnosis. IEE ProceedingsControl Theory and Applications,1998,145(3):353-357.
[62] B. Jiang and F. N. Chowdhury. Fault estimation and accommodation for linear MIMOdiscrete-time systems. IEEE Transactions on Control Systems Technology,2005,13(3):493-499.
[63] J. L. Chang. Applying discrete-time proportional integral observers for state and disturbanceestimations. IEEE Transactions on Automatic Control,2006,51(5):814-818.
[64] Z. Gao, T. Breikin, and H. Wang. Discrete-time proportional and integral observer andobserver-based controller for systems with both unknown input and output disturbances.Optimal Control Applications and Methods,2008,29(3):171-189.
[65] D. Theilliol, H. Noura, and J.-C. Ponsart. Fault diagnosis and accommodation of a three-tanksystem based on analytical redundancy. ISA Transactions,2002,41(3):365-382.
[66] R. J. Patton. Fault-tolerant control: the1997situation. Proceeding of IFAC Symposium onFault Detection Supervision Safety for Processes (SAFEPROCESS), Hull:IFAC,1997:1033-1055.
[67] M. M. Polycarpou and A. J. Helmicki. Automated fault detection and automated faultdetection and accommodation: A learning systems approach. IEEE Transactions on Systems,Man, and Cybernetics,1995,25(11):1447-1458.
[68] M. Staroswieck, H. Yang, and B. Jiang. Progressive accommodation of parametric faults inlinear quadratic control. Automatica,2007,43(12):2070-2076.
[69] G. G. Yen and L.-W. Ho. Online multiple-model-based fault diagnosis and accommodation.IEEE Transactions on Industrial Electronics,2003,50(2):296-312.
[70] D. Theilliol, H. Noura, and D. Sauter. Fault-tolerant control method for actuator andcomponent faults. Proceedings of the37th IEEE Conference on Decision and Control,Tampa:IEEE,1998:604-609.
[71] D. Theilliol, H. Noura, and J.-C. Ponsart. Fault diagnosis and accommodation of a three-tanksystem based on analytical redundancy. ISA Transactions,2002,41(3):365-382.
[72]俞立.鲁棒控制--线性矩阵不等式处理方法.北南:清华南学出版社,2002.
[73] M. Grant and S. Boyd. CVX: Matlab software for disciplined convex programming, version1.21. http://cvxr.com/cvx, July2010.
[74] M. Grant and S. Boyd. Graph implementations for nonsmooth convex programs. RecentAdvances in Learning and Control (a tribute to M. Vidyasagar), V. Blondel, S. Boyd, and H.Kimura, editors, pages95--110, Lecture Notes in Control and Information Sciences, Springer,2008. http://stanford.edu/~boyd/graph_dcp.html.
[75] K. Zhang, B. Jiang, and V. Cocquempot. Adaptive observer-based fast fault estimation.International Journal of Control, Automation, and Systems,2008,6(3):320-326.
[76] L. Xie. Output feedback H∞control of systems with parameter uncertainty. InternationalJournal of Control,1996,63(4):741-750.
[77] M. Corless and J. Tu. State and input estimation for a class of uncertain systems. Automatica,1998,34(6):757-764.
[78] H. Alwi and C. Edwards. Robust sensor fault estimation for tolerant control of a civil aircraftusing sliding modes. Proceedings of the American Control Conference. Minneapolis: IEEE,2006:5704-5709.
[79] Y. Y. Cao and P. M. Frank. Analysis and synthesis of nonlinear time-delay systems via fuzzycontrol approach. IEEE Transactions on Fuzzy Systems,2000,8(2):200-211.
[80] C. Lin, Q. G. Wang, and T. H. Lee. Stabilization of uncertain fuzzy time-delay systems viavariable structure control approach. IEEE Transactions on Fuzzy Systems,2005,13(6):787-798.
[81] F. Liao, J. L. Wang, and G.-H. Yang. Reliable robust flight tracking control: An LMI approach.IEEE Transactions on Control Systems Technology,2002,10(1):76-89.
[82] J. D. Boskovic, and R. K. Mehra. Multiple model adaptive flight control scheme foraccommodation of actuator failures. Journal of Guidance, Control, and Dynamics,2002,25(4):712-724.
[83] G. Tao, S. Chen, and S. M. Joshi. An adaptive actuator failure compensation controller usingoutput feedback. IEEE Transactions on Automatic Control,2002,47(3):506-511.
[84] Y. Zhang and J. Jiang. Fault tolerant control system design with explicit consideration ofperformance degradation. IEEE Transactions on Aerospace and Electronic Systems,2003,39(3):838-848.
[85] G. Tao, S. Chen, X. Tang, and S. M. Joshi. Adaptive Control of Systems with ActuatorFailures. London: Springer Verlag,2004.
[86] D. Ye and G.-H. Yang. Adaptive fault-tolerant tracking control against actuator faults withapplication to flight control. IEEE Transactions on Control Systems Technology,2006,14(6):1088-1096.
[87] C. Edwards, T. Lombaerts, and H. Smaili. Fault Tolerant Flight Control: A BenchmarkChallenge. Berlin Heidelberg: Springer Verlag,2010.
[88] K. Vijayaraghavan, R. Rajamani, and J. Bokor. Quantitative fault estimation for a class ofnon-linear systems. International Journal of Control,2007,80(1):64-74.
[89] K. Zhang, B. Jiang, and P. Shi. Fast fault estimation and accommodation for dynamicalsystems. IET Control Theory and Applications,2009,3(2):189-199.
[90] G. Garcia and J. Bernussou. Pole assignment for uncertain systems in a specified disk by statefeedback. IEEE Transactions on Automatic Control,1995,40(1):184-190.
[91] P. Gahinet and P. Apkarian. A linear matrix inequality approach to H∞control. InternationalJournal of Robust and Nonlinear Control,1994,4(4):421-448.
[92] K. Zhou and J. C. Doyle. Essentials of Robust Control. New Jersey: Prentice Hall,1998.
[93] M. C. de Oliveira, J. C. Geromel, and J. Bernussou. Extended H2and H∞normcharacterizations and controller parametrizations for discrete-time systems. InternationalJournal of Control,2002,75(9):666-679.
[94] W. Xie. Multi-objective H∞/α-stability controller synthesis of LTI systems. IET ControlTheory and Applications,2008,2(1):51-55.
[95] X. Du and G.-H. Yang. New characterisations of positive realness and static output feedbackcontrol of discrete-time systems. International Journal of Control,2009,82(8):1485-1495.
[96] J. Lam and S. Zhou. Dynamic output feedback H∞control of discrete-time fuzzy systems: Afuzzy-basis-dependent Lyapunov function approach. International Journal of Systems Science,2007,38(1):25-37.
[97] J. Dong and G.-H. Yang. Dynamic output feedback control synthesis for continuous-time T-Sfuzzy systems via a switched fuzzy control scheme. IEEE Transactions on Systems, Man, andCybernetics-Part B: Cybernetics,2008,38(4):1166-1175.
[98] Y. M. Zhang and J. Jiang. Integrated active fault-tolerant control using IMM approach. IEEETransactions on Aerospace and Electronic Systems,2001,37(4):1221-1235.
[99] D. Huang and S. K. Nguang. Robust H∞static output feedback control of fuzzy systems: AnILMI approach. IEEE Transactions on Systems, Man, and Cybernetics Part B: Cybernetics,2006,36(1):216-222.
[100] Y.-Y. Cao and Y.-X. Sun. Static output feedback simultaneous stabilization: ILMI approach.International Journal of Control,1998,70(5):803-814.
[101] C. A. R. Crusius and A. Trofino. Sufficient LMI conditions for output feedback controlproblems. IEEE Transactions on Automatic Control,1999,44(5):1053-1057.
[102] W. Chang, J. B. Park, Y. H. Joo, and G. Chen. Static output-feedback fuzzy controller forchen's chaotic system with uncertainties. Information Sciences,2003,151:227-244.
[103] J.-C. Lo and M.-L. Lin. Robust H∞nonlinear control via fuzzy static output feedback. IEEETransactions on Circuits and Systems I: Fundamental Theory and Applications,2003,50(11):1494-1502.
[104] S. K. Mudge and R. J. Patton. Analysis of the technique of robust eigenstructure assignmentwith application to aircraft control. IEE Proceedings-D Control Theory and Applications,1988,135(4):275-281.
[105] T. Takagi and M. Sugeno. Fuzzy identification of systems and its application to modeling andcontrol. IEEE Transactions on Systems, Man, and Cybernetics,1985,15(1):116-132.
[106] X. J. Ma, Z. Q. Sun, and Y. Y. He. Analysis and design of fuzzy controller and fuzzy observer.IEEE Transactions on Fuzzy Systems,1998,6(1):41-51.
[107] K. Tanaka and H. O. Wang, Fuzzy Control Systems Design and Analysis: An Linear MatrixInequality Approach. New York:Wiley,2001.
[108] H. Zhang and Y. Quan. Modeling, identification, and control of a class of nonlinear systems.IEEE Transactions on Fuzzy Systems,2001,9(2):349–354.
[109] X.-J. Ma and Z.-Q. Sun. Analysis and design of fuzzy reduced-dimensional observer andfuzzy functional observer. Fuzzy Sets and Systems,2001,120(1):35-63.
[110] Y. Y. Cao and P. M. Frank. Stability analysis and synthesis of nonlinear time-delay systems vialinear Takagi-Sugeno fuzzy models. Fuzzy Sets and Systems,2001,124(2):213-229.
[111] S. K. Nguang and P. Shi. H∞fuzzy output feedback control design for nonlinear systems: AnLMI approach. IEEE Transactions on Fuzzy Systems,2003,11(3):331-340.
[112] H.-N. Wu. Reliable LQ fuzzy control for continuous-time nonlinear systems with actuatorfaults. IEEE Transactions on Systems, Man, and Cybernetics-Part B: Cybernetics,2004,34(4):1743-1752.
[113] A. Sala, T. M. Guerra, and R.t Babuska. Perspectives of fuzzy systems and control. Fuzzy Setsand Systems,2005,156(3):432-444.
[114] H. Zhang and D. Liu. Fuzzy Modeling and Fuzzy Control. Boston: Birkhuser,2006.
[115] G. Feng. A survey on analysis and design of model-based fuzzy control systems. IEEETransactions on Fuzzy Systems,2006,14(5):676-697.
[116] H. H. Choi. LMI-based nonlinear fuzzy observer-controller design for uncertain MIMOnonlinear systems. IEEE Transactions on Fuzzy Systems,2007,15(5):956-971.
[117] H. Zhang and Y. Wang and D. Liu. Delay-dependent guaranteed cost control for uncertainstochastic fuzzy systems with multiple time delays. IEEE Transactions on Systems, Man, andCybernetics--Part B: Cybernetics,2008,38(1):126-140.
[118] C.-S. Tseng. A novel approach to H∞decentralized fuzzy-observer-based fuzzy controldesign for nonlinear interconnected systems. IEEE Transactions on Fuzzy Systems,2008,16(5):1337-1350.
[119] J. Dong and G.-H. Yang. Dynamic output feedback H∞control synthesis for discrete-timeT-S fuzzy systems via switching fuzzy controllers. Fuzzy Sets and Systems,2009,160(4):482-499.
[120] R. J. Patton, J. Chen, and C. J. Lopez-Toribio. Fuzzy observers for non-linear dynamicsystems fault diagnosis. Proceedings of the IEEE Conference on Decision and Control,Tampa:IEEE,1998:84-89.
[121] C. J. Lopez-Toribio and R. J. Patton. Takagi-Sugeno fuzzy fault-tolerant control for anon-linear system. Proceedings of the IEEE Conference on Decision and Control,Phoenix:IEEE,1999:4368-4373.
[122] S. K. Nguang, P. Shi, and S. X. Ding. Fault detection for uncertain fuzzy systems: An LMIapproach. IEEE Transactions on Fuzzy Systems,2007,15(6):1251-1262.
[123] L. Wu and D. W. C. Ho. Fuzzy filter design for Ito stochastic systems with application tosensor fault detection. IEEE Transactions on Fuzzy Systems,2009,17(1):233-242.
[124] H. Gao, Y. Zhao, and T. Chen. H∞fuzzy control of nonlinear systems under unreliablecommunication links. IEEE Transactions on Fuzzy Systems,2009,17(2):265-273.
[125] Y. Zheng, H. Fang, and H. O. Wang. Takagi–Sugeno fuzzy-model-based fault detection fornetworked control systems with markov delays. IEEE Transactions on Systems, Man, andCybernetics-Part B: Cybernetics,2006,36(4):924-929.
[126] J. Li, H. O. Wang, D. Niemann, and K. Tanaka. Dynamic parallel distributed compensation forTakagi-Sugeno fuzzy systems: An LMI approach. Information Sciences,2000,123(3-4):201-221.
[127] H. Gao and T. Chen. Stabilization of nonlinear systems under variable sampling: A fuzzycontrol approach. IEEE Transactions on Fuzzy Systems,2007,15(5):972-983
[128] J. Dong and G.-H. Yang. Static output feedback H∞control of a class of nonlineardiscrete-time systems. Fuzzy Sets and Systems,2009,160(19):2844-2859.
[129] K. Tanaka and M. Sano. A robust stabilization problem of fuzzy control systems anditsapplication to backing up control of a truck-trailer. IEEE Transactions on Fuzzy Systems,1994,2(2):119-134.
[130] G. Feng and J. Ma. Quadratic stabilization of uncertain discrete-time fuzzy dynamic systems.IEEE Transactions on Circuits and Systems I: Fundamental Theory and Applications,2001,48(11):1337-1344.
[131]杨一栋.直升机飞行控制.北南:国防工业出版社,2007.
[132]曹义华.直升机飞行力学.北南:北南南南南南南学出版社,2005.
[133]黄一敏,孙传伟,高正.直升机飞行控制系统的快速原型设计.飞行力学,2003,20(1):5-9.
[134]葛金来.三自由度直升机实验系统的控制策略研究.[硕士学位论文].济南：山东南学,2010.
[135] Quanser Inc.3-DOF Helicopter Reference Manual. Docunment Number644/Revision2.11,Canada: Quanser Inc,2007.