船舶动力定位容错控制方法研究
|
摘要
随着人们日益重视对深海的探索和开发，深海装备飞速发展，对船舶动力定位(Dynamic Positioning，DP)系统的依赖性日益提高，使其得到了更广泛的应用，随之而来，对其安全性和可靠性提出了更高的要求，不但要求船舶在进行正常动力定位作业的过程中满足控制性能要求，而且对于某些特殊作业，在出现可接受的故障之后要求仍然能够继续完成作业，甚至满足降低的性能指标，或至少在一定时间内不会发生重大事故。容错控制可提高系统的安全性和可靠性，因此对船舶动力定位进行容错控制是必要的。
目前高等级的船舶动力定位系统皆具有物理冗余和解析冗余。在动力定位系统已具备一定物理冗余度的前提下，通过解析冗余充分利用已有冗余关系来实现船舶动力定位的容错控制，可保证船舶在故障情况下仍能持续动力定位作业，同时应尽可能保持原控制器的控制性能和船舶的定位能力，因此研究基于解析冗余的容错控制方法对于船舶动力定位的容错控制具有十分重要的理论和工程意义。
本文围绕此前沿性课题，对船舶动力定位作业过程中传感器和推进器故障的诊断方法，以及传感器和推进器故障船舶的动力定位容错控制方法展开了深入研究，提出了基于有向图和支持向量机（Support Vector Machine，SVM）的故障诊断方法，以及基于鲁棒滑模虚拟传感器和鲁棒自适应滑模虚拟执行器的容错控制方法。
本文主要完成了以下研究内容：
为了对可能发生的故障进行及时诊断，并对故障船舶进行容错控制，同时，真实反映船舶在容错过程中对环境干扰及控制输入的响应特性，根据国内外已公开发表的文献资料，建立了3自由度船舶运动学和动力学模型，环境载荷模型以及推进系统模型，给出了可用于验证容错控制方法的试验船数学模型。
为了实现船舶动力定位的传感器故障诊断，利用二叉树分类法将多种故障类型的多分类问题转换为多个二分类问题进行分类，利用差值法对样本数据进行特征提取，将提取后的特征向量作为支持向量机输入，实现故障诊断。仿真结果验证了所提方法可快速、准确、有效地实现传感器故障的检测和隔离。
为了实现船舶动力定位的推进器故障诊断，利用有向图相关理论中求解系统结构图的最大匹配算法，得到动力定位船舶及其推进系统中变量与约束间的完全匹配，根据得到的匹配，针对每个推进器的螺距控制和转速控制约束，设计可用于故障诊断的解析冗余关系。提出基于有向图和支持向量机的故障诊断方法，将得到的冗余关系的残差值经过处理后输入支持向量机，使得阈值根据支持向量机学习的结果变化，降低了故障诊断中漏报和误报的概率，在保证了诊断结果完备性的同时，大大提升了故障诊断的分辨率。
为了进行传感器故障情况下的船舶动力定位容错控制，提出一种基于滑模观测器和虚拟传感器技术的控制重构策略。设计了虚拟传感器来跟踪故障船舶的运行状态，虚拟传感器的作用等同于故障传感器，通过虚拟传感器的状态来重构故障后的船舶控制回路。结合滑模观测器解决船舶动力定位系统中存在的模型非线性、建模误差、扰动和参数不确定等问题，设计了一种鲁棒滑模虚拟传感器来改善虚拟传感器的适用范围。仿真结果表明所设计的方法可以较好地完成传感器故障的船舶动力定位容错控制。
为了进行推进器故障情况下的船舶动力定位容错控制，提出一种基于滑模变结构控制、自适应控制和虚拟执行器技术的控制重构策略。在故障船舶与标称控制器之间设计虚拟执行器来重构船舶，虚拟执行器的作用与故障执行器一致，使得重构后的船舶输出仍然保持正常船舶的输出特征，而无需进行标称控制器的重新调整和重构。结合滑模变结构控制和自适应控制技术解决船舶动力定位系统中存在的模型非线性、建模误差、扰动和参数不确定、不确定项上界未知等问题，设计了一种鲁棒自适应滑模虚拟执行器改善虚拟执行器的适用范围和控制性能。仿真结果表明所设计的方法可以较好地完成推进器故障的船舶动力定位容错控制。
本文在物理冗余的基础上，通过解析冗余实现了船舶动力定位的故障诊断和容错控制，从软件层面提高了船舶动力定位的可靠性和安全性，与物理冗余相比提供了更加切实有力的保障。
As the increasing focus on the exploration and development of the ocean, the deep-seaequipment develops rapidly. The dependence on dynamic positioning system is markedcausing its comprehensive appliance, simultaneously, its security and reliability are requiredstrictly. Control performance must be satisfied in normal dynamic positioning operations,even after occurring fault, some special task must have the ability to continue working withdegraded performance, which insures the system far from serious accident in limited time. Itneeds fault-tolerant control for dynamic positioning of ship which can improve security andreliability of the system.
At present, high-level dynamic positioning system of ship all equip physical andanalytical redundancy. With physical redundancy, fault-tolerant control for dynamicpositioning of ship is achieved based on redundancy relationship used by analyticalredundancy, which can ensure durative dynamic positioning operation of ship with fault andhold performance of nominal controller and ability of dynamic positioning of ship. So theresearch of fault-tolerant control method based on analytical redundancy is significative totheory and engineering for dynamic positioning of ship.
This paper focused on this frontier subject. Sensor and thruster fault diagnosis method,and sensor and thruster fault-tolerant control method were researched. The fault diagnosismethod based on oriented graph and Support Vector Machine (SVM) was proposed. Thefault-tolerant control method based on virtual sensor with robust sliding mode and virtualactuator with robust adaptive sliding mode were designed.
Works achieved in this paper are present as follows.
To find the potential fault timely, implement fault-tolerant control for the faulty ship andtruly reflect the ship response characteristics of environmental disturbance and control inputduring the fault-tolerant control process, the3-DOF kinematics and dynamics models of ship,the environmental load model and the propulsion system model were established according tothe literatures. To validate the fault-tolerant control method proposed, the parameters of theship were given.
To achieve sensor fault diagnosis for dynamic positioning of ship, binary treeclassification was used to convert multi-classification problem of various fault type to manydimidiate-classifications. The difference method was used to extract feature from the sampling data, then the feature was as the input of SVM. Simulation shows that the methodproposed can achieve the detection of sensor fault quickly and accurately.
To achieve thruster fault diagnosis for dynamic positioning of ship, maximum matchingalgorithm from oriented graph theory which can get the structural graph of system was usedto get complete matching between variables and constraints of dynamic positioning ship andpropulsion system. According to the matching, analytical redundancy relation based residualswere designed for constraints of pitch and shaft speed control of each thruster. The faultdiagnosis method based on oriented graph and SVM was proposed, residuals of redundancyrelation were as input of SVM after processing, which make the threshold change with theresult of SVM. The method above can reduce the probability of missing and false alarm,which can insure completeness and improve resolution of fault diagnosis greatly.
To achieve fault-tolerant control for dynamic positioning of ship with sensor fault,reconfiguration strategy based on sliding mode observer and virtual sensor technology wasproposed. Virtual sensor was designed to track the state of faulty ship. Virtual sensor isidentical with faulty sensor, which reconfigured control loop of faulty ship from the state ofvirtual sensor. To solve nonlinear, error, disturbance and parameter uncertainties of systemmodel for dynamic positioning of ship, based on sliding mode observer, virtual sensor withrobustness sliding mode was designed to improve the applicability range of virtual sensor.Simulation result shows that the method proposed can well complete the fault-tolerant controlfor the dynamic positioning ship with sensor fault.
To achieve fault-tolerant control for dynamic positioning of ship with thruster fault,reconfiguration strategy based on sliding mode control, adaptive control and virtual actuatortechnology was proposed. Virtual actuator was designed between faulty ship and nominalcontroller to reconfigure ship. Virtual actuator is identical with faulty actuator, which makesoutput of reconfigured ship hold the same output feature as nominal ship, insteads ofreadjustment and reconfiguration of nominal controller. To solve nonlinear, error, disturbance,parameter uncertainties and unknown boundary of the uncertainties of system model fordynamic positioning of ship, based on sliding mode control and adaptive control, virtualactuator with robust adaptive sliding mode was designed to improve the applicability rangeand control performance of virtual actuator. Simulation result shows that the method proposedcan well complete the fault-tolerant control for the dynamic positioning ship with thrusterfault.
In this paper, with physical redundancy, fault diagnosis and fault-tolerant control fordynamic positioning of ship were achieved by analytical redundancy. Reliability and security of dynamic positioning of ship were improved with standpoint of software, which can providepowerful guarantee compared with physics redundancy indeed.
目前高等级的船舶动力定位系统皆具有物理冗余和解析冗余。在动力定位系统已具备一定物理冗余度的前提下，通过解析冗余充分利用已有冗余关系来实现船舶动力定位的容错控制，可保证船舶在故障情况下仍能持续动力定位作业，同时应尽可能保持原控制器的控制性能和船舶的定位能力，因此研究基于解析冗余的容错控制方法对于船舶动力定位的容错控制具有十分重要的理论和工程意义。
本文围绕此前沿性课题，对船舶动力定位作业过程中传感器和推进器故障的诊断方法，以及传感器和推进器故障船舶的动力定位容错控制方法展开了深入研究，提出了基于有向图和支持向量机（Support Vector Machine，SVM）的故障诊断方法，以及基于鲁棒滑模虚拟传感器和鲁棒自适应滑模虚拟执行器的容错控制方法。
本文主要完成了以下研究内容：
为了对可能发生的故障进行及时诊断，并对故障船舶进行容错控制，同时，真实反映船舶在容错过程中对环境干扰及控制输入的响应特性，根据国内外已公开发表的文献资料，建立了3自由度船舶运动学和动力学模型，环境载荷模型以及推进系统模型，给出了可用于验证容错控制方法的试验船数学模型。
为了实现船舶动力定位的传感器故障诊断，利用二叉树分类法将多种故障类型的多分类问题转换为多个二分类问题进行分类，利用差值法对样本数据进行特征提取，将提取后的特征向量作为支持向量机输入，实现故障诊断。仿真结果验证了所提方法可快速、准确、有效地实现传感器故障的检测和隔离。
为了实现船舶动力定位的推进器故障诊断，利用有向图相关理论中求解系统结构图的最大匹配算法，得到动力定位船舶及其推进系统中变量与约束间的完全匹配，根据得到的匹配，针对每个推进器的螺距控制和转速控制约束，设计可用于故障诊断的解析冗余关系。提出基于有向图和支持向量机的故障诊断方法，将得到的冗余关系的残差值经过处理后输入支持向量机，使得阈值根据支持向量机学习的结果变化，降低了故障诊断中漏报和误报的概率，在保证了诊断结果完备性的同时，大大提升了故障诊断的分辨率。
为了进行传感器故障情况下的船舶动力定位容错控制，提出一种基于滑模观测器和虚拟传感器技术的控制重构策略。设计了虚拟传感器来跟踪故障船舶的运行状态，虚拟传感器的作用等同于故障传感器，通过虚拟传感器的状态来重构故障后的船舶控制回路。结合滑模观测器解决船舶动力定位系统中存在的模型非线性、建模误差、扰动和参数不确定等问题，设计了一种鲁棒滑模虚拟传感器来改善虚拟传感器的适用范围。仿真结果表明所设计的方法可以较好地完成传感器故障的船舶动力定位容错控制。
为了进行推进器故障情况下的船舶动力定位容错控制，提出一种基于滑模变结构控制、自适应控制和虚拟执行器技术的控制重构策略。在故障船舶与标称控制器之间设计虚拟执行器来重构船舶，虚拟执行器的作用与故障执行器一致，使得重构后的船舶输出仍然保持正常船舶的输出特征，而无需进行标称控制器的重新调整和重构。结合滑模变结构控制和自适应控制技术解决船舶动力定位系统中存在的模型非线性、建模误差、扰动和参数不确定、不确定项上界未知等问题，设计了一种鲁棒自适应滑模虚拟执行器改善虚拟执行器的适用范围和控制性能。仿真结果表明所设计的方法可以较好地完成推进器故障的船舶动力定位容错控制。
本文在物理冗余的基础上，通过解析冗余实现了船舶动力定位的故障诊断和容错控制，从软件层面提高了船舶动力定位的可靠性和安全性，与物理冗余相比提供了更加切实有力的保障。
As the increasing focus on the exploration and development of the ocean, the deep-seaequipment develops rapidly. The dependence on dynamic positioning system is markedcausing its comprehensive appliance, simultaneously, its security and reliability are requiredstrictly. Control performance must be satisfied in normal dynamic positioning operations,even after occurring fault, some special task must have the ability to continue working withdegraded performance, which insures the system far from serious accident in limited time. Itneeds fault-tolerant control for dynamic positioning of ship which can improve security andreliability of the system.
At present, high-level dynamic positioning system of ship all equip physical andanalytical redundancy. With physical redundancy, fault-tolerant control for dynamicpositioning of ship is achieved based on redundancy relationship used by analyticalredundancy, which can ensure durative dynamic positioning operation of ship with fault andhold performance of nominal controller and ability of dynamic positioning of ship. So theresearch of fault-tolerant control method based on analytical redundancy is significative totheory and engineering for dynamic positioning of ship.
This paper focused on this frontier subject. Sensor and thruster fault diagnosis method,and sensor and thruster fault-tolerant control method were researched. The fault diagnosismethod based on oriented graph and Support Vector Machine (SVM) was proposed. Thefault-tolerant control method based on virtual sensor with robust sliding mode and virtualactuator with robust adaptive sliding mode were designed.
Works achieved in this paper are present as follows.
To find the potential fault timely, implement fault-tolerant control for the faulty ship andtruly reflect the ship response characteristics of environmental disturbance and control inputduring the fault-tolerant control process, the3-DOF kinematics and dynamics models of ship,the environmental load model and the propulsion system model were established according tothe literatures. To validate the fault-tolerant control method proposed, the parameters of theship were given.
To achieve sensor fault diagnosis for dynamic positioning of ship, binary treeclassification was used to convert multi-classification problem of various fault type to manydimidiate-classifications. The difference method was used to extract feature from the sampling data, then the feature was as the input of SVM. Simulation shows that the methodproposed can achieve the detection of sensor fault quickly and accurately.
To achieve thruster fault diagnosis for dynamic positioning of ship, maximum matchingalgorithm from oriented graph theory which can get the structural graph of system was usedto get complete matching between variables and constraints of dynamic positioning ship andpropulsion system. According to the matching, analytical redundancy relation based residualswere designed for constraints of pitch and shaft speed control of each thruster. The faultdiagnosis method based on oriented graph and SVM was proposed, residuals of redundancyrelation were as input of SVM after processing, which make the threshold change with theresult of SVM. The method above can reduce the probability of missing and false alarm,which can insure completeness and improve resolution of fault diagnosis greatly.
To achieve fault-tolerant control for dynamic positioning of ship with sensor fault,reconfiguration strategy based on sliding mode observer and virtual sensor technology wasproposed. Virtual sensor was designed to track the state of faulty ship. Virtual sensor isidentical with faulty sensor, which reconfigured control loop of faulty ship from the state ofvirtual sensor. To solve nonlinear, error, disturbance and parameter uncertainties of systemmodel for dynamic positioning of ship, based on sliding mode observer, virtual sensor withrobustness sliding mode was designed to improve the applicability range of virtual sensor.Simulation result shows that the method proposed can well complete the fault-tolerant controlfor the dynamic positioning ship with sensor fault.
To achieve fault-tolerant control for dynamic positioning of ship with thruster fault,reconfiguration strategy based on sliding mode control, adaptive control and virtual actuatortechnology was proposed. Virtual actuator was designed between faulty ship and nominalcontroller to reconfigure ship. Virtual actuator is identical with faulty actuator, which makesoutput of reconfigured ship hold the same output feature as nominal ship, insteads ofreadjustment and reconfiguration of nominal controller. To solve nonlinear, error, disturbance,parameter uncertainties and unknown boundary of the uncertainties of system model fordynamic positioning of ship, based on sliding mode control and adaptive control, virtualactuator with robust adaptive sliding mode was designed to improve the applicability rangeand control performance of virtual actuator. Simulation result shows that the method proposedcan well complete the fault-tolerant control for the dynamic positioning ship with thrusterfault.
In this paper, with physical redundancy, fault diagnosis and fault-tolerant control fordynamic positioning of ship were achieved by analytical redundancy. Reliability and security of dynamic positioning of ship were improved with standpoint of software, which can providepowerful guarantee compared with physics redundancy indeed.
引文
[1] M.J.摩根著，耿惠彬译.近海船舶的动力定位.国防工业出版社，1984.
[2]中国船级社.钢质海船入级规范.中国船级社，2010：8-15页
[3]卫卫，李春璘，王鹏，陈根.动力定位DP-3附加标志在钻井平台上的设计与应用.船舶，2009，4：34-41页
[4]耿煮.IMO动力定位系统规范介绍.中国造船，2008，49(2).
[5] Analysis of Station Keeping Incident Data1994-2003. IMCA,2006,1.
[6]罗小元.几类非线性系统鲁棒故障诊断及容错控制研究.燕山大学博士学位论文，2005.
[7] Thomas Steffen. Control Reconfiguration of Dynamical Systems. Spring,2005.
[8] Mogens Blanke, Michel Kinnaert, Jan Lunze and Marcel Staroswiecki. Diagnosis andFault-Tolerant Control. Spring2ndEdition,2006.
[9] Halim Alwi. Fault Tolerant Sliding Mode Control Schemes with AerospaceApplications. Doctor of science thesis, University of Leicester,2008.
[10] Youmin Zhang and Jin Jiang. Bibliographical review on reconfigurable fault-tolerantcontrol systems. Annual Reviews in Control,2008,32:229-252P.
[11]周东华，叶银忠.现代故障诊断与容错控制[M].北京：清华大学出版社，2000.
[12]王德军.故障诊断与容错控制方法研究.吉林大学博士学位论文，2004.
[13] J. Chen and J. Patton. Robust model-based fault diagnosis for dynamic systems.Boston: Kluwer Academic,1999.
[14] R.V. Beard. Failure accommodation in linear systems through self-reorganization.Report MVT-71-1, Man Vehicle Lab, MIT, Cambridge, Massachusetts,1971.
[15] R.K. Mehra and J. Peschon. An innovation approach to fault detection and diagnosis indynamics. Automatica,1971,7(3):637-640P.
[16] Zhang Xiaodong. Fault diagnosis and fault-tolerant control for nonlinear systems.Ph.D,2002.
[17]李令莱，周东华.基于解析模型的非线性系统鲁棒故障诊断方法综述.信息与控制，2004，33(4)：451-462页.
[18] M. Saif, Y. Guan. A New Approach to Robust Fault detection and Identification. IEEETransaction on Aerospace and Electronic Systems,1993,29(3):684-695P.
[19] J. Chen, R.J. Patton and H.Y. Zhang. Design of Unknown Input Observer and RobustFault Detection Filters. International Journal of Control,1996,63(1):84-105P.
[20] J. Chen and R.J. Patton. Optimal Filtering and Robust Fault Diagnosis of StochasticSystems with Unknown Disturbances. IEE proceedings of Control Theory Application,1996,143(1):31-36P.
[21] F. Caliskan, C.M. Hajiyev. Aircraft Sensor Fault Diagnosis Based on Kalman FilterInnovation Sequence. Proceedings of37thConference on Decision&Control. Tampa,USA,1998:1313-1314P.
[22] E.C. Larson, B.E.P. Jr, B.R. Clark. Model-Based Sensor and Actuator Fault Detectionand Isolation. Proceedings of the American Control Conference, Anchorage,2002:4214-4219P.
[23] C.De Persis and A. Isidori. A geometric approach to nonlinear fault detection andisolation. IEEE Trans. on Automatic Control,2002,46(6):853-865P.
[24] D. Juricic, M. Zele. Robust Detection of Sensor Faults by Means of A Statistical Test.Automatica,2002,38:737-742P.
[25]胡昌华，许化龙.控制系统故障诊断与容错控制的分析和设计.北京：国防工业出版社，2000.
[26] J.Q. Zhang, Y. Yan. A Wavelet-Based Approach to Abrupt Fault Detection andDiagnosis of Sensors. IEEE Transactions on Instrumentation and Measurement,2001,50(5):1389-1396P.
[27]吕柏权.一种基于小波网络的故障检测方法.控制理论与应用，1998，15(5)：802-805页
[28] Kumamaru K, Hu J, Inoue K and Soderstrom T. Robust Fault detection using index ofKullback discrimination information. Proceeding of IFAC World Congress, SanFrancisco, USA,1996,205-210P.
[29] Pazzani M J. Failure driven learning of fault diagnosis heuristics. IEEE Tran. onSystems. Man and Cybernetics,1987,17(3):380-384P.
[30]黄洪钟.模糊机械科学与技术.机械工程学报，1996，32(3)：1-8页
[31] Sauter D, Mary N, Sirou F and Thieltgen A. Fault Diagnosis in systems using fuzzylogic. Proceeding of3rdIEEE Conference on Control Applications, Glasgow, UK,883-888P.
[32] Schneider H. and Frank P M. Fuzzy logic based threshold adaption for fault detectionin robots. Proceeding of3rdIEEE Conference on Control Applications, Glasgow, UK,1127-1132P.
[33] Vachkov G. Identification for fuzzy rule based system for fault diagnosis in chemicalplants. Proceeding IFAC Symp. on On-line Fault Detection and Supervision in theChemical Process Industries, Newark, Delaware, USA,315-318P.
[34]闻新，周露.神经网络故障诊断技术的可实现性.导弹与航天运载技术，2000，(2)：17-22页
[35] H. Wang. Actuator fault diagnosis for nonlinear dynamic systems. Trans. of theInstitute of Measurement and Control,1995,17(2):63-71P.
[36] H. Wang. Fault detection and diagnosis for unknown nonlinear systems: a generalizedframework via neural networks. In: Proceedings of the IEEE Intemational Conferenceon Intelligent Proceessing Systems,1997:1506-1510P.
[37] M.M. Polycarpou and A.J. Helmicki. Automated fault detection and accommodation: alearning systems approach. IEEE Transactions on Systems, Man and Cybernetics,1995,25(11):1447-1458P.
[38] A. Niederlinski. A Heuristic Approach to the Design of Interacting MultivariableSystems. Automatica,1971,7:691-701P.
[39] Joshi, S.M. Design of failure-accommodation multiloop LQG-type controller. IEEETransactions on Automatic Control,1987,32(8):740-741P.
[40] Caglayan, A.K., Allen, S.M.,&Wehmuller, K. Evaluation of a second generationreconfiguration strategy for aircraft flight control systems subjected to actuatorfailure/surface damage. In Proceedings of the IEEE National Aerospace andElectronics Conference,1988,5:520-529P.
[41] Lopez-Toribio, C.J., Patton, R.J.,&Daley, S. Takagi-Sugeno fuzzy fault-tolerantcontrol of an induction motor. Neural Computing and Applications,2000,19(1):19-28P.
[42] Shin, J.Y., Wu, N.E.,&Belcastro, C. Adaptive linear parameter varying controlsynthesis for actuator. Journal of Guidance, Control, and Dynamics,2004,27(4):787–794P.
[43] Morse, W.D. and Ossman, K.A. Model following reconfigurable flight control systemsfor the AFTI/F-16. Journal of Guidance, Control, and Dynamics,1990,13(6):969-976P.
[44] Tao, Joshi, S.M. Ma and X. Adaptive state feedback and tracking control of systemswith actuator failures,2001,46(1):78-95P.
[45] Maybeck, P.S. Stevens and R.D. Reconfigurable flight control via multiple modeladaptive control methods. IEEE Transactions on Aerospace and Electronic Systems,1991,27(3):470-479P.
[46] Konstantopoulos, I.K. and Antsaklis, P.J. An optimization approach to controlreconfiguration. Dynamics and Control,1999,9(3):255-270P.
[47] Doman, D.B. Ngo and A.D. Dynamic inversion-based adaptive/reconfigurable control of theX-33on ascent. Journal of Guidance, Control, and Dynamics,2002,25(2):275-284P.
[48] Yang, Z. Stoustrup and J. Robust reconfigurable control for parametric and additivefaults with FDI uncertainties. In Proceedings of the39thIEEE conference on decisionand control,2000:4132-4137P.
[49] Kale, M.M.,&Chipperfield, A.J. Stabilized mpc formulations for robustreconfigurable flight control. Control Engineering Practice,2005,13(6):771-788P.
[50] Niksefat, N.,&Sepehri, N. A QFT fault-tolerant control for electro-hydraulic positioningsystems. IEEE Transactions on Control Systems Technology,2002,10(4):626-632P.
[51] Liao, F., Wang, J.L.,&Yang, G.H. Reliable robust flight tracking control: An LMIapproach. IEEE Transactions on Control Systems Technology,2002,10(1):76-89P.
[52] Hess, R.A.,&Wells, S.R. Sliding mode control applied to reconfigurable flight controldesign. Journal of Guidance, Control, and Dynamics,2003,26(3):452-462P.
[53] Campos-Delgado, D.U.,&Zhou, K. Reconfigurable fault-tolerant control using GIMCstructure. IEEE Transactions on Automatic Control,2003,48(5):832-839P.
[54] M. Vidyasagar and N. Viswanadham. Reliable stabilization using a multi-controllerconfiguration. Automatica,1985,21(4):599-602P.
[55] A.N. Gundes. Controller design for reliable stabilization. In: Proc. of12thIFAC WorldCongress,1993,4:1-4P.
[56] N. Sebe and T. Kitamori. Control systems possessing reliability to control. In: Proc. of12thIFAC World Congress,1993,4:1-4P.
[57] P.T. Kabamba and C. Yang. Simultaneous controller design for linear time-invariantsystems. IEEE. Trans. On Automatic Control,1991,36(1):106-111P.
[58]葛建华，孙优贤，周春辉.故障系统容错能力判别的研究.信息与控制，1989，18(4)：8-11页
[59] Y.Z. Ye. Fault tolerant pole assignment for multivariable systems using a fixed statefeedback.控制理论与应用，1993，10(2)：212-218页
[60] J. Bao, W.Z. Zhang and P.L. Lee. Decentralized fault-tolerant control system design forunstable processes. Chemical Engineering Science,2003,58:5045-5054P.
[61] I. Kaminer，et al. A velocity algorithm for the implementation of gain-scheduledcontrollers. Automatica,1995,31(8):1185-1192P.
[62] Kwong, et al. Expert supervision of fuzzy learning systems for fault tolerant aircraftcontrol. In: Proceedings of the IEEE,1995,83(3):466-483P.
[63] R.R. Huber and B. McCulloch. Self-repairing flight control system. SAE Tech. PaperSeries,1984:1-20P.
[64]胡寿松，程炯.动态系统的鲁棒容错控制方法.自动化学报，1991，17(3)：280-287页
[65]王子栋，孙翔，孙金生，王执铨.不确定线性系统的鲁棒容错控制设计.航空学报，1996，17(1)：112-115页
[66]黄献青，瞿坦，陈锦江.离散时间系统容错控制.控制理论与应用，1996，13(1)：36-40页
[67] Z.D. Wang, B. Huang and H. Unbehauen. Robust reliable control for a class ofuncertain nonlinear systems. Automatica,1999,35(6):955-963P.
[68] Mogens Blanke. Diagnosis and Fault-tolerant Control for Ship Station Keeping.Proceedings of the13thMediterranean Conference on Control and AutomationLimassol, Cyprus,2005,1379-1384P.
[69] R. Izadi-Zamanabadi and M. Blanke. A ship propulsion system as a benchmark forfault-tolerant control. Control Engineering Practice,1999,7(2):227-239P.
[70] M. Blanke, R. Izadi-Zamanabadi and T.F. Loostma. Fault monitoring andreconfigurable control for a ship propulsion plant. Journal of Adaptive Control andSignal Processing,1998,671-688P.
[71] T.F. Lootsma. Observer-based Fault Detection and Isolation for Nonlinear Systems.PhD thesis, Aalborg University, Department of Control Engineering,2001.
[72] Claudio Bonivento, Andrea Paoli and Lorenzo Marconi. Fault-tolerant control of theship propulsion system benchmark. Control Engineering Practice,2003,11:483-492P.
[73] Tako F. Lootsma, Roozbeh Izadi-Zamanabadi and Henk Nijmeijer. A GEOMETRICAPPROACH TO DIAGNOSIS APPLIED TO A SHIP PROPULSION PROBLEM.IFAC15thTriennial World Congress, Barcelona, Spain,2002.
[74] Sudha Thavamani. Fault Tolerant Control of a Ship Propulsion System. Doctor ofscience thesis. State University of New York,2006.
[75] Haibo Chen, Torgeir Moan and Harry Verhoeven. Effect of DGPS failure on dynamicpositioning of mobile drilling units in the North Sea. Accident Analysis and Prevention,2009,41:1164-1171P.
[76]刘潇，冯舒.动力定位系统故障模式与后果分析中的关键点.中国海洋平台，2012，27(4)：6-9页
[77]王宏健，边信黔，丁福光，韩桂萍.船舶动力定位系统级故障诊断技术.中国造船，2003，44(2)：67-73页
[78]丁福光，王宏健，边信黔，韩桂萍.分布式系统级故障诊断算法在船舶动力定位系统中的应用.船舶工程，2002(4)：34-37页
[79]汤天浩.基于混合神经网络的容错控制方法在船舶系统中的应用.上海海运学院硕士学位论文，2003.
[80]李少红.工作母船主推进系统故障诊断技术研究.哈尔滨工程大学硕士学位论文，2009.
[81] Morten Breivik. Nonlinear Maneuvering Control of Underactuated Ships. Master ofScience Thesis. Norwegian University of Science and Technology,2003.
[82] Ivar-Andre Flakstad Ihle. Observer design for synchronization of vessels withunreliable position measurements. Master of Science Thesis. Norwegian University ofScience and Technology,2003.
[83] Blanke, M., Izadi-Zamanabadi, R., R gh, S. and Lunau, C. Fault-tolerant controlsystems–a holistic view. Control Engineering Practice,1997,5(5):694-702P.
[84] Blanke, M., Izadi-Zamanabadi, R., Lootsma and T.F.. Fault monitoring andreconfigurable control for a ship propulsion plant. International Journal of AdaptiveControl and Signal Processing,1998,12(8):671-688P.
[85] Blanke, M., Lootsma and T.F.. Adaptive observer for diesel fault detection in a shippropulsion benchmark. Proceedings of European Control Conference,1999.
[86] yvind Notland Smogeli. Control of Marine Propellers. PhD thesis. NorwegianUniversity of Science and Technology,2006.
[87]谢保川，刘福太.支持向量机在模拟电路故障诊断中的应用.计算机仿真，2006，23(10)：167-170页
[88] Shih-Wei Lin, Zne-Jung Lee, Shih-Chieh Chen, et al. Parameter determination ofsupport vector machine and feature selection using simulated annealing approach.Applied Soft Computing,2008,8:1505-1512P.
[89]邓乃杨，田英杰.支持向量机——理论算法与拓展.北京：科学出版社，2009.
[90]董春曦，饶鲜，杨绍全，徐松涛.支持向量机参数选择方法研究.系统工程与电子技术，2004，26(8)：1117-1120页
[91]王鹏，朱小燕.基于RBF核的SVM的模型选择及其应用.计算机工程与应用，2003，24：72-73页
[92]林升梁，刘志.基于RBF核函数的支持向量机参数选择.浙江工业大学学报，2007，35(2)：163-167页
[93] Sebastian Küchler, Christoph Pregizer, Johannes Karl Eberharter, Klaus Schneider andOliver Sawodny. Real-Time Estimation of a Ship’s Attitude. American ControlConference,2011,2411-2415P.
[94] P.A. Samara, G.N. Fouskitakis, J.S. Sakellariou and S.D. Fassois. AIRCRAFTANGLE-OF-ATTACK VIRTUAL SENSOR DESIGN VIA A FUNCTIONALPOOLING NARX METHODOLOGY. In: European Control Conference, Universityof Cambridge,2003.
[95] C. latorre, B. Tranchero.“Neural net-based virtual sensors in flight control systems”.15thIFAC Symposium on Automatic Control in Aerospace,2001,416-421P.
[96] M. Oosterom, R. Babuska.“Virtual sensor for fault detection and isolation in flightcontrol systems–fuzzy modeling approach”. Preceedings of the39thIEEE Conferenceon Decision and Control,2000,3:2645-2650P.
[97]张明光，姜一达.虚拟传感器重组方法的主动容错控制研究.PROCESSAUTOMATION INSTRUMENTATION，2010，31(6)：24-26页
[98]鲍晟，冯勇，孙黎霞.非线性不确定系统的鲁棒滑模观测器设计.哈尔滨工业大学学报，2004，36(5)：613-616页
[99]张袅娜，冯勇，邱东.非线性不确定系统的鲁棒滑模观测器设计.控制理论与应用，2007，24(5)：715-718页
[100]刘云峰，刘华峰.非线性不确定系统的滑模观测器设计.上海航天，2009(1)：15-19页
[101] Chee Pin Tan, Christopher Edwards. Sliding mode observers for detection andreconstruction of sensor faults. Automatica,2002,38:1815-1821P.
[102] Chee Pin Tan and Christopher Edwards. Sliding mode observers for robust detectionand reconstruction of actuator and sensor faults. INTERNATIONAL JOURNAL OFROBUST AND NONLINEAR CONTROL,2003,13:443-463P.
[103] Christopher Edwards and Chee Pin Tan. Sensor fault tolerant control using slidingmode observers. Control Engineering Practice,2006,14:897-908P.
[104] Xing-Gang Yan and Christopher Edwards. Nonlinear robust fault reconstruction andestimation using a sliding mode observer. Automatica,2007,43:1605-1614P.
[105] T.I. Fossen. Marine Control Systems–Guidance, Navigation and Control of Ships,Rigs and Underwater Vehicles. Norway: Marine Cybernetics,2002.
[106] Lunze J and Steffen T. Control reconfiguration by means of a virtual actuator.International Federation of Automatic Control,2003,131-136P.
[107] Richter Jan H, Schlage Thorsten and Lunze Jan. Control reconfiguration of athermofluid process by means of a virtual actuator. The Institution of Engineering andTechnology,2007,1:1606-1620P.
[108] Lunze Jan and Steffen Thomas. Control reconfiguration after actuator failures usingdisturbance decoupling methods. Automatic Control,2006,51:1590-1600P.
[109]孙建华，刘春生，张绍杰.一类不确定性系统的重构容错控制.系统工程与电子技术，2010，32(6)：1286-1291页
[110]刘金琨.滑模变结构控制MATLAB仿真.北京：清华大学出版社，2005.
[111] Xiaoyu Zhang, Hongye Su, Lingfei Xiao and Jian Chu. Robust Sliding Mode ControlBased on Integral Sliding Surfaces. American Control Conference,2005:4074-4077P.
[112] J Fei and C Batur. A class of adaptive sliding mode controller withproportional-integral sliding surface. Proceedings of the Institution of MechanicalEngineers,2009:989-999P.
[113] Salah Laghrouche, Franck Plestan and Alain Glumineau. Higher order sliding modecontrol based on integral sliding mode. Automatica,2007,43:531-537P.
[114] Meysar Zeinali, Leila Notash. Adaptive sliding mode control with uncertaintyestimator for robot manipulators. Mechanism and Machine Theory,2010,45:80-90P.
[115] Antonio Loria, Thor I. Fossen and Elena Panteley. A Separation Principle for DynamicPositioning of Ships: Theoretical and Experimental Results. IEEE TRANSACTIONSON CONTROL SYSTEMS TECHNOLOGY,2000,8(2):332-343P.
[116] Anders Robertsson and Rolf Johansson. Comments on “Nonlinear Output FeedbackControl of Dynamically Positioned Ships Using Vectorial Observer Backstepping”.IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY,1998,6(3):439-441P.
[117] K.D. Do. Global Robust and Adaptive Output Feedback Dynamic Positioning ofSurface Ships. IEEE International Conference on Robotics and Automation,2007:4271-4276P.
[118] Thor I.Fossen, Jann Peter Strand. Passive nonlinear observer design for ships usingLyapunov methods: full-scale experiments with a supply vessel. Automatica,1999(35):3-16P.
[119]李萌.船舶动力定位系统非线性估计滤波器的研究.哈尔滨工程大学硕士学位论文，2009.
[120]姜锋.船舶动力定位系统非线性观测器设计.大连海事大学硕士学位论文，2011.
[2]中国船级社.钢质海船入级规范.中国船级社，2010：8-15页
[3]卫卫，李春璘，王鹏，陈根.动力定位DP-3附加标志在钻井平台上的设计与应用.船舶，2009，4：34-41页
[4]耿煮.IMO动力定位系统规范介绍.中国造船，2008，49(2).
[5] Analysis of Station Keeping Incident Data1994-2003. IMCA,2006,1.
[6]罗小元.几类非线性系统鲁棒故障诊断及容错控制研究.燕山大学博士学位论文，2005.
[7] Thomas Steffen. Control Reconfiguration of Dynamical Systems. Spring,2005.
[8] Mogens Blanke, Michel Kinnaert, Jan Lunze and Marcel Staroswiecki. Diagnosis andFault-Tolerant Control. Spring2ndEdition,2006.
[9] Halim Alwi. Fault Tolerant Sliding Mode Control Schemes with AerospaceApplications. Doctor of science thesis, University of Leicester,2008.
[10] Youmin Zhang and Jin Jiang. Bibliographical review on reconfigurable fault-tolerantcontrol systems. Annual Reviews in Control,2008,32:229-252P.
[11]周东华，叶银忠.现代故障诊断与容错控制[M].北京：清华大学出版社，2000.
[12]王德军.故障诊断与容错控制方法研究.吉林大学博士学位论文，2004.
[13] J. Chen and J. Patton. Robust model-based fault diagnosis for dynamic systems.Boston: Kluwer Academic,1999.
[14] R.V. Beard. Failure accommodation in linear systems through self-reorganization.Report MVT-71-1, Man Vehicle Lab, MIT, Cambridge, Massachusetts,1971.
[15] R.K. Mehra and J. Peschon. An innovation approach to fault detection and diagnosis indynamics. Automatica,1971,7(3):637-640P.
[16] Zhang Xiaodong. Fault diagnosis and fault-tolerant control for nonlinear systems.Ph.D,2002.
[17]李令莱，周东华.基于解析模型的非线性系统鲁棒故障诊断方法综述.信息与控制，2004，33(4)：451-462页.
[18] M. Saif, Y. Guan. A New Approach to Robust Fault detection and Identification. IEEETransaction on Aerospace and Electronic Systems,1993,29(3):684-695P.
[19] J. Chen, R.J. Patton and H.Y. Zhang. Design of Unknown Input Observer and RobustFault Detection Filters. International Journal of Control,1996,63(1):84-105P.
[20] J. Chen and R.J. Patton. Optimal Filtering and Robust Fault Diagnosis of StochasticSystems with Unknown Disturbances. IEE proceedings of Control Theory Application,1996,143(1):31-36P.
[21] F. Caliskan, C.M. Hajiyev. Aircraft Sensor Fault Diagnosis Based on Kalman FilterInnovation Sequence. Proceedings of37thConference on Decision&Control. Tampa,USA,1998:1313-1314P.
[22] E.C. Larson, B.E.P. Jr, B.R. Clark. Model-Based Sensor and Actuator Fault Detectionand Isolation. Proceedings of the American Control Conference, Anchorage,2002:4214-4219P.
[23] C.De Persis and A. Isidori. A geometric approach to nonlinear fault detection andisolation. IEEE Trans. on Automatic Control,2002,46(6):853-865P.
[24] D. Juricic, M. Zele. Robust Detection of Sensor Faults by Means of A Statistical Test.Automatica,2002,38:737-742P.
[25]胡昌华，许化龙.控制系统故障诊断与容错控制的分析和设计.北京：国防工业出版社，2000.
[26] J.Q. Zhang, Y. Yan. A Wavelet-Based Approach to Abrupt Fault Detection andDiagnosis of Sensors. IEEE Transactions on Instrumentation and Measurement,2001,50(5):1389-1396P.
[27]吕柏权.一种基于小波网络的故障检测方法.控制理论与应用，1998，15(5)：802-805页
[28] Kumamaru K, Hu J, Inoue K and Soderstrom T. Robust Fault detection using index ofKullback discrimination information. Proceeding of IFAC World Congress, SanFrancisco, USA,1996,205-210P.
[29] Pazzani M J. Failure driven learning of fault diagnosis heuristics. IEEE Tran. onSystems. Man and Cybernetics,1987,17(3):380-384P.
[30]黄洪钟.模糊机械科学与技术.机械工程学报，1996，32(3)：1-8页
[31] Sauter D, Mary N, Sirou F and Thieltgen A. Fault Diagnosis in systems using fuzzylogic. Proceeding of3rdIEEE Conference on Control Applications, Glasgow, UK,883-888P.
[32] Schneider H. and Frank P M. Fuzzy logic based threshold adaption for fault detectionin robots. Proceeding of3rdIEEE Conference on Control Applications, Glasgow, UK,1127-1132P.
[33] Vachkov G. Identification for fuzzy rule based system for fault diagnosis in chemicalplants. Proceeding IFAC Symp. on On-line Fault Detection and Supervision in theChemical Process Industries, Newark, Delaware, USA,315-318P.
[34]闻新，周露.神经网络故障诊断技术的可实现性.导弹与航天运载技术，2000，(2)：17-22页
[35] H. Wang. Actuator fault diagnosis for nonlinear dynamic systems. Trans. of theInstitute of Measurement and Control,1995,17(2):63-71P.
[36] H. Wang. Fault detection and diagnosis for unknown nonlinear systems: a generalizedframework via neural networks. In: Proceedings of the IEEE Intemational Conferenceon Intelligent Proceessing Systems,1997:1506-1510P.
[37] M.M. Polycarpou and A.J. Helmicki. Automated fault detection and accommodation: alearning systems approach. IEEE Transactions on Systems, Man and Cybernetics,1995,25(11):1447-1458P.
[38] A. Niederlinski. A Heuristic Approach to the Design of Interacting MultivariableSystems. Automatica,1971,7:691-701P.
[39] Joshi, S.M. Design of failure-accommodation multiloop LQG-type controller. IEEETransactions on Automatic Control,1987,32(8):740-741P.
[40] Caglayan, A.K., Allen, S.M.,&Wehmuller, K. Evaluation of a second generationreconfiguration strategy for aircraft flight control systems subjected to actuatorfailure/surface damage. In Proceedings of the IEEE National Aerospace andElectronics Conference,1988,5:520-529P.
[41] Lopez-Toribio, C.J., Patton, R.J.,&Daley, S. Takagi-Sugeno fuzzy fault-tolerantcontrol of an induction motor. Neural Computing and Applications,2000,19(1):19-28P.
[42] Shin, J.Y., Wu, N.E.,&Belcastro, C. Adaptive linear parameter varying controlsynthesis for actuator. Journal of Guidance, Control, and Dynamics,2004,27(4):787–794P.
[43] Morse, W.D. and Ossman, K.A. Model following reconfigurable flight control systemsfor the AFTI/F-16. Journal of Guidance, Control, and Dynamics,1990,13(6):969-976P.
[44] Tao, Joshi, S.M. Ma and X. Adaptive state feedback and tracking control of systemswith actuator failures,2001,46(1):78-95P.
[45] Maybeck, P.S. Stevens and R.D. Reconfigurable flight control via multiple modeladaptive control methods. IEEE Transactions on Aerospace and Electronic Systems,1991,27(3):470-479P.
[46] Konstantopoulos, I.K. and Antsaklis, P.J. An optimization approach to controlreconfiguration. Dynamics and Control,1999,9(3):255-270P.
[47] Doman, D.B. Ngo and A.D. Dynamic inversion-based adaptive/reconfigurable control of theX-33on ascent. Journal of Guidance, Control, and Dynamics,2002,25(2):275-284P.
[48] Yang, Z. Stoustrup and J. Robust reconfigurable control for parametric and additivefaults with FDI uncertainties. In Proceedings of the39thIEEE conference on decisionand control,2000:4132-4137P.
[49] Kale, M.M.,&Chipperfield, A.J. Stabilized mpc formulations for robustreconfigurable flight control. Control Engineering Practice,2005,13(6):771-788P.
[50] Niksefat, N.,&Sepehri, N. A QFT fault-tolerant control for electro-hydraulic positioningsystems. IEEE Transactions on Control Systems Technology,2002,10(4):626-632P.
[51] Liao, F., Wang, J.L.,&Yang, G.H. Reliable robust flight tracking control: An LMIapproach. IEEE Transactions on Control Systems Technology,2002,10(1):76-89P.
[52] Hess, R.A.,&Wells, S.R. Sliding mode control applied to reconfigurable flight controldesign. Journal of Guidance, Control, and Dynamics,2003,26(3):452-462P.
[53] Campos-Delgado, D.U.,&Zhou, K. Reconfigurable fault-tolerant control using GIMCstructure. IEEE Transactions on Automatic Control,2003,48(5):832-839P.
[54] M. Vidyasagar and N. Viswanadham. Reliable stabilization using a multi-controllerconfiguration. Automatica,1985,21(4):599-602P.
[55] A.N. Gundes. Controller design for reliable stabilization. In: Proc. of12thIFAC WorldCongress,1993,4:1-4P.
[56] N. Sebe and T. Kitamori. Control systems possessing reliability to control. In: Proc. of12thIFAC World Congress,1993,4:1-4P.
[57] P.T. Kabamba and C. Yang. Simultaneous controller design for linear time-invariantsystems. IEEE. Trans. On Automatic Control,1991,36(1):106-111P.
[58]葛建华，孙优贤，周春辉.故障系统容错能力判别的研究.信息与控制，1989，18(4)：8-11页
[59] Y.Z. Ye. Fault tolerant pole assignment for multivariable systems using a fixed statefeedback.控制理论与应用，1993，10(2)：212-218页
[60] J. Bao, W.Z. Zhang and P.L. Lee. Decentralized fault-tolerant control system design forunstable processes. Chemical Engineering Science,2003,58:5045-5054P.
[61] I. Kaminer，et al. A velocity algorithm for the implementation of gain-scheduledcontrollers. Automatica,1995,31(8):1185-1192P.
[62] Kwong, et al. Expert supervision of fuzzy learning systems for fault tolerant aircraftcontrol. In: Proceedings of the IEEE,1995,83(3):466-483P.
[63] R.R. Huber and B. McCulloch. Self-repairing flight control system. SAE Tech. PaperSeries,1984:1-20P.
[64]胡寿松，程炯.动态系统的鲁棒容错控制方法.自动化学报，1991，17(3)：280-287页
[65]王子栋，孙翔，孙金生，王执铨.不确定线性系统的鲁棒容错控制设计.航空学报，1996，17(1)：112-115页
[66]黄献青，瞿坦，陈锦江.离散时间系统容错控制.控制理论与应用，1996，13(1)：36-40页
[67] Z.D. Wang, B. Huang and H. Unbehauen. Robust reliable control for a class ofuncertain nonlinear systems. Automatica,1999,35(6):955-963P.
[68] Mogens Blanke. Diagnosis and Fault-tolerant Control for Ship Station Keeping.Proceedings of the13thMediterranean Conference on Control and AutomationLimassol, Cyprus,2005,1379-1384P.
[69] R. Izadi-Zamanabadi and M. Blanke. A ship propulsion system as a benchmark forfault-tolerant control. Control Engineering Practice,1999,7(2):227-239P.
[70] M. Blanke, R. Izadi-Zamanabadi and T.F. Loostma. Fault monitoring andreconfigurable control for a ship propulsion plant. Journal of Adaptive Control andSignal Processing,1998,671-688P.
[71] T.F. Lootsma. Observer-based Fault Detection and Isolation for Nonlinear Systems.PhD thesis, Aalborg University, Department of Control Engineering,2001.
[72] Claudio Bonivento, Andrea Paoli and Lorenzo Marconi. Fault-tolerant control of theship propulsion system benchmark. Control Engineering Practice,2003,11:483-492P.
[73] Tako F. Lootsma, Roozbeh Izadi-Zamanabadi and Henk Nijmeijer. A GEOMETRICAPPROACH TO DIAGNOSIS APPLIED TO A SHIP PROPULSION PROBLEM.IFAC15thTriennial World Congress, Barcelona, Spain,2002.
[74] Sudha Thavamani. Fault Tolerant Control of a Ship Propulsion System. Doctor ofscience thesis. State University of New York,2006.
[75] Haibo Chen, Torgeir Moan and Harry Verhoeven. Effect of DGPS failure on dynamicpositioning of mobile drilling units in the North Sea. Accident Analysis and Prevention,2009,41:1164-1171P.
[76]刘潇，冯舒.动力定位系统故障模式与后果分析中的关键点.中国海洋平台，2012，27(4)：6-9页
[77]王宏健，边信黔，丁福光，韩桂萍.船舶动力定位系统级故障诊断技术.中国造船，2003，44(2)：67-73页
[78]丁福光，王宏健，边信黔，韩桂萍.分布式系统级故障诊断算法在船舶动力定位系统中的应用.船舶工程，2002(4)：34-37页
[79]汤天浩.基于混合神经网络的容错控制方法在船舶系统中的应用.上海海运学院硕士学位论文，2003.
[80]李少红.工作母船主推进系统故障诊断技术研究.哈尔滨工程大学硕士学位论文，2009.
[81] Morten Breivik. Nonlinear Maneuvering Control of Underactuated Ships. Master ofScience Thesis. Norwegian University of Science and Technology,2003.
[82] Ivar-Andre Flakstad Ihle. Observer design for synchronization of vessels withunreliable position measurements. Master of Science Thesis. Norwegian University ofScience and Technology,2003.
[83] Blanke, M., Izadi-Zamanabadi, R., R gh, S. and Lunau, C. Fault-tolerant controlsystems–a holistic view. Control Engineering Practice,1997,5(5):694-702P.
[84] Blanke, M., Izadi-Zamanabadi, R., Lootsma and T.F.. Fault monitoring andreconfigurable control for a ship propulsion plant. International Journal of AdaptiveControl and Signal Processing,1998,12(8):671-688P.
[85] Blanke, M., Lootsma and T.F.. Adaptive observer for diesel fault detection in a shippropulsion benchmark. Proceedings of European Control Conference,1999.
[86] yvind Notland Smogeli. Control of Marine Propellers. PhD thesis. NorwegianUniversity of Science and Technology,2006.
[87]谢保川，刘福太.支持向量机在模拟电路故障诊断中的应用.计算机仿真，2006，23(10)：167-170页
[88] Shih-Wei Lin, Zne-Jung Lee, Shih-Chieh Chen, et al. Parameter determination ofsupport vector machine and feature selection using simulated annealing approach.Applied Soft Computing,2008,8:1505-1512P.
[89]邓乃杨，田英杰.支持向量机——理论算法与拓展.北京：科学出版社，2009.
[90]董春曦，饶鲜，杨绍全，徐松涛.支持向量机参数选择方法研究.系统工程与电子技术，2004，26(8)：1117-1120页
[91]王鹏，朱小燕.基于RBF核的SVM的模型选择及其应用.计算机工程与应用，2003，24：72-73页
[92]林升梁，刘志.基于RBF核函数的支持向量机参数选择.浙江工业大学学报，2007，35(2)：163-167页
[93] Sebastian Küchler, Christoph Pregizer, Johannes Karl Eberharter, Klaus Schneider andOliver Sawodny. Real-Time Estimation of a Ship’s Attitude. American ControlConference,2011,2411-2415P.
[94] P.A. Samara, G.N. Fouskitakis, J.S. Sakellariou and S.D. Fassois. AIRCRAFTANGLE-OF-ATTACK VIRTUAL SENSOR DESIGN VIA A FUNCTIONALPOOLING NARX METHODOLOGY. In: European Control Conference, Universityof Cambridge,2003.
[95] C. latorre, B. Tranchero.“Neural net-based virtual sensors in flight control systems”.15thIFAC Symposium on Automatic Control in Aerospace,2001,416-421P.
[96] M. Oosterom, R. Babuska.“Virtual sensor for fault detection and isolation in flightcontrol systems–fuzzy modeling approach”. Preceedings of the39thIEEE Conferenceon Decision and Control,2000,3:2645-2650P.
[97]张明光，姜一达.虚拟传感器重组方法的主动容错控制研究.PROCESSAUTOMATION INSTRUMENTATION，2010，31(6)：24-26页
[98]鲍晟，冯勇，孙黎霞.非线性不确定系统的鲁棒滑模观测器设计.哈尔滨工业大学学报，2004，36(5)：613-616页
[99]张袅娜，冯勇，邱东.非线性不确定系统的鲁棒滑模观测器设计.控制理论与应用，2007，24(5)：715-718页
[100]刘云峰，刘华峰.非线性不确定系统的滑模观测器设计.上海航天，2009(1)：15-19页
[101] Chee Pin Tan, Christopher Edwards. Sliding mode observers for detection andreconstruction of sensor faults. Automatica,2002,38:1815-1821P.
[102] Chee Pin Tan and Christopher Edwards. Sliding mode observers for robust detectionand reconstruction of actuator and sensor faults. INTERNATIONAL JOURNAL OFROBUST AND NONLINEAR CONTROL,2003,13:443-463P.
[103] Christopher Edwards and Chee Pin Tan. Sensor fault tolerant control using slidingmode observers. Control Engineering Practice,2006,14:897-908P.
[104] Xing-Gang Yan and Christopher Edwards. Nonlinear robust fault reconstruction andestimation using a sliding mode observer. Automatica,2007,43:1605-1614P.
[105] T.I. Fossen. Marine Control Systems–Guidance, Navigation and Control of Ships,Rigs and Underwater Vehicles. Norway: Marine Cybernetics,2002.
[106] Lunze J and Steffen T. Control reconfiguration by means of a virtual actuator.International Federation of Automatic Control,2003,131-136P.
[107] Richter Jan H, Schlage Thorsten and Lunze Jan. Control reconfiguration of athermofluid process by means of a virtual actuator. The Institution of Engineering andTechnology,2007,1:1606-1620P.
[108] Lunze Jan and Steffen Thomas. Control reconfiguration after actuator failures usingdisturbance decoupling methods. Automatic Control,2006,51:1590-1600P.
[109]孙建华，刘春生，张绍杰.一类不确定性系统的重构容错控制.系统工程与电子技术，2010，32(6)：1286-1291页
[110]刘金琨.滑模变结构控制MATLAB仿真.北京：清华大学出版社，2005.
[111] Xiaoyu Zhang, Hongye Su, Lingfei Xiao and Jian Chu. Robust Sliding Mode ControlBased on Integral Sliding Surfaces. American Control Conference,2005:4074-4077P.
[112] J Fei and C Batur. A class of adaptive sliding mode controller withproportional-integral sliding surface. Proceedings of the Institution of MechanicalEngineers,2009:989-999P.
[113] Salah Laghrouche, Franck Plestan and Alain Glumineau. Higher order sliding modecontrol based on integral sliding mode. Automatica,2007,43:531-537P.
[114] Meysar Zeinali, Leila Notash. Adaptive sliding mode control with uncertaintyestimator for robot manipulators. Mechanism and Machine Theory,2010,45:80-90P.
[115] Antonio Loria, Thor I. Fossen and Elena Panteley. A Separation Principle for DynamicPositioning of Ships: Theoretical and Experimental Results. IEEE TRANSACTIONSON CONTROL SYSTEMS TECHNOLOGY,2000,8(2):332-343P.
[116] Anders Robertsson and Rolf Johansson. Comments on “Nonlinear Output FeedbackControl of Dynamically Positioned Ships Using Vectorial Observer Backstepping”.IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY,1998,6(3):439-441P.
[117] K.D. Do. Global Robust and Adaptive Output Feedback Dynamic Positioning ofSurface Ships. IEEE International Conference on Robotics and Automation,2007:4271-4276P.
[118] Thor I.Fossen, Jann Peter Strand. Passive nonlinear observer design for ships usingLyapunov methods: full-scale experiments with a supply vessel. Automatica,1999(35):3-16P.
[119]李萌.船舶动力定位系统非线性估计滤波器的研究.哈尔滨工程大学硕士学位论文，2009.
[120]姜锋.船舶动力定位系统非线性观测器设计.大连海事大学硕士学位论文，2011.
© 2004-2018 中国地质图书馆版权所有 京ICP备05064691号 京公网安备11010802017129号 地址：北京市海淀区学院路29号 邮编：100083 电话：办公室：(+86 10)66554848；文献借阅、咨询服务、科技查新：66554700 |