潜器水下悬停控制方法研究
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摘要
海洋经济和海洋产业的快速发展,使得对水下潜器的需求日益增长,同时对深潜控制技术提出了更高的要求；“海空联合作战”理念的发展,使潜艇作为重要的现代武器承载平台在空海一体战体系中发挥着无可替代的作用。潜器为了完成既定任务,需要实现多种运动或操纵模态,水下悬停作为潜器特种操纵模态,具有重要的经济和战略意义。国内关于潜器水下悬停操纵控制技术的研究尚处于起步阶段,因而有大量的基础性研究工作需要完成。本文在深入研究潜器操纵运动建模与控制技术发展现状以及水下悬停操纵运动控制特点的基础之上,系统地研究潜器水下悬停运动机理、辨识建模技术以及操纵控制策略。论文主要研究内容如下：
在对潜器近水面悬停运动机理及动力学特性进行详细分析的基础上,基于刚体动力学原理建立了一种易于实验测定并且满足系统准确性要求的潜器悬停运动动力学模型。以某型潜艇为例计算悬停运动水动力参数,对所建立的潜器水下悬停模型进行了仿真验证。同时,全面而系统地对潜器悬停干扰因素进行了机理分析与系统建模,包括初始不均衡量、艇体体积压缩、密度变化干扰、近水面浪涌干扰以及海流在内的水下悬停环境干扰力建模；并对干扰环境下的潜器悬停运动进行了仿真研究。
针对潜器近水面悬停运动的特点,基于微分几何控制理论,提出一种全局稳定的潜器悬停控制策略,将复杂的非线性潜器悬停系统通过适当的静态反馈转化为简单的伪线性系统,利用Lyapunov方法和极点配置法进行了控制器设计。通过静态理想环境条件以及动态干扰环境下对潜器悬停运动控制系统的仿真分析,验证了控制器的有效性。仿真结果表明,所设计的控制策略能够保障系统的鲁棒性,有效克服系统的不确定性,实现潜器悬停控制。
近水面悬停海洋环境复杂多变,为了有效抑制近水面海浪干扰对潜器悬停运动的影响,控制潜器悬停纵倾角度以及深度的波动,基于逆控制的基本原理,提出了一种潜器悬停自适应逆控制策略,构建可变参数网络,利用状态变量反馈调节抑制潜器悬停控制系统未知扰动。仿真分析验证了控制器的有效性,该方法在不影响原系统动态性能的基础上,实现了浪涌干扰抑制消除,具有良好的鲁棒稳定性。
针对潜器悬停控制系统模型中水动力参数的不确定性,以及各运动自由度之间的交叉耦合影响,很难得到原系统的精确逆模型的问题。提出了一种基于数据驱动的潜器悬停逆系统控制方法,探讨了采用基于知识引导的多元统计策略对一类仿射非线性MIMO系统建立α阶逆系统模型的方法,并以某型潜器为研究对象,建立了基于数据驱动的潜器逆控制系统。仿真研究表明,基于数据驱动的解耦控制策略可实现潜器悬停姿态的精确控制。
The development of ocean economy and industry, puts higher requirements on deep dive technology. Submarine, the important platform of modern weapon, has irreplaceable function for "Airsea Battle". The underwater hovering system of which has strategic significance and highly confidential status in international. The domestic study of the underwater hovering control technology is still at an early stage with a large number of basic research to be done. On the base of maneuvering movement model and control technology and hovering manipulate motion control, the paper deeply and systematically study the mechanism underwater hovering movement, modeling techniques and control strategic. The main content of this paper is as follows:
With the basis of detailed analysis of the hovering movement mechanism, hydrodynamic characteristic and the rigid body dynamics theory, a dynamics model of hovering movement has been built. It is easy to be tested and meet the accuracy system requirements. The hydrodynamic parameter of the underwater hovering submarine is calculated. As an example, checking the model built above. At the same time, the interference factor of hovering submarine is completely and systematically analyzed and modeled. Modeling of the under unbalanced initial parameter, volume compression of the submarine, the interference of changing density, near the surface waves and currents and simulating under disturbances condition are included.
To the hovering movement character of the near water submarine and geometry theory, the paper puts forward a globally stable strategy of hovering movement. The nonlinear process is transformed into simply pseudo linear system through appropriately static feedback. Control strategy with Lyapunov and Pole Placement are proposed. Under the simulate analysis of hovering system in static and dynamic environment, the validity of controller is checked. As the validation shows, the designed control strategy can guarantee the robustness of the system, overcome the uncertainty of the system and control hovering movement.
The marine environment for hovering movement near the water is complicated. To effectively restrain the wave interference on hovering movement and control volatility of trim degree and deepness, an adaptive inverse control strategy is proposed. The unknown disturbances on hovering controlling system is restrained by the inverse controlling theory with variable parameter network and adjustment feedback.The simulation results validate the effectiveness of the control strategy. The strategy diminishes the wave interference successfully with good robust stability, leaving the original system not be affected.
Finally, as to the uncertainty of hydrodynamic parameter on hovering movement controlling models and intersectional coupling between freedom motions, the accurate inverse model could hardly be realized. The paper proposed an inverse controlling method based on data-driven control theory. The α-step inverse modeling method to a type of affine nonlinear MIMO system has been built based on multivariate statistical strategy. What's more, an inverse controlling system is built based on data-driven with a type of submarine as research object. The simulation results indicate the decoupling control strategy based on data-driven can precisely control hovering attitude.
在对潜器近水面悬停运动机理及动力学特性进行详细分析的基础上,基于刚体动力学原理建立了一种易于实验测定并且满足系统准确性要求的潜器悬停运动动力学模型。以某型潜艇为例计算悬停运动水动力参数,对所建立的潜器水下悬停模型进行了仿真验证。同时,全面而系统地对潜器悬停干扰因素进行了机理分析与系统建模,包括初始不均衡量、艇体体积压缩、密度变化干扰、近水面浪涌干扰以及海流在内的水下悬停环境干扰力建模；并对干扰环境下的潜器悬停运动进行了仿真研究。
针对潜器近水面悬停运动的特点,基于微分几何控制理论,提出一种全局稳定的潜器悬停控制策略,将复杂的非线性潜器悬停系统通过适当的静态反馈转化为简单的伪线性系统,利用Lyapunov方法和极点配置法进行了控制器设计。通过静态理想环境条件以及动态干扰环境下对潜器悬停运动控制系统的仿真分析,验证了控制器的有效性。仿真结果表明,所设计的控制策略能够保障系统的鲁棒性,有效克服系统的不确定性,实现潜器悬停控制。
近水面悬停海洋环境复杂多变,为了有效抑制近水面海浪干扰对潜器悬停运动的影响,控制潜器悬停纵倾角度以及深度的波动,基于逆控制的基本原理,提出了一种潜器悬停自适应逆控制策略,构建可变参数网络,利用状态变量反馈调节抑制潜器悬停控制系统未知扰动。仿真分析验证了控制器的有效性,该方法在不影响原系统动态性能的基础上,实现了浪涌干扰抑制消除,具有良好的鲁棒稳定性。
针对潜器悬停控制系统模型中水动力参数的不确定性,以及各运动自由度之间的交叉耦合影响,很难得到原系统的精确逆模型的问题。提出了一种基于数据驱动的潜器悬停逆系统控制方法,探讨了采用基于知识引导的多元统计策略对一类仿射非线性MIMO系统建立α阶逆系统模型的方法,并以某型潜器为研究对象,建立了基于数据驱动的潜器逆控制系统。仿真研究表明,基于数据驱动的解耦控制策略可实现潜器悬停姿态的精确控制。
The development of ocean economy and industry, puts higher requirements on deep dive technology. Submarine, the important platform of modern weapon, has irreplaceable function for "Airsea Battle". The underwater hovering system of which has strategic significance and highly confidential status in international. The domestic study of the underwater hovering control technology is still at an early stage with a large number of basic research to be done. On the base of maneuvering movement model and control technology and hovering manipulate motion control, the paper deeply and systematically study the mechanism underwater hovering movement, modeling techniques and control strategic. The main content of this paper is as follows:
With the basis of detailed analysis of the hovering movement mechanism, hydrodynamic characteristic and the rigid body dynamics theory, a dynamics model of hovering movement has been built. It is easy to be tested and meet the accuracy system requirements. The hydrodynamic parameter of the underwater hovering submarine is calculated. As an example, checking the model built above. At the same time, the interference factor of hovering submarine is completely and systematically analyzed and modeled. Modeling of the under unbalanced initial parameter, volume compression of the submarine, the interference of changing density, near the surface waves and currents and simulating under disturbances condition are included.
To the hovering movement character of the near water submarine and geometry theory, the paper puts forward a globally stable strategy of hovering movement. The nonlinear process is transformed into simply pseudo linear system through appropriately static feedback. Control strategy with Lyapunov and Pole Placement are proposed. Under the simulate analysis of hovering system in static and dynamic environment, the validity of controller is checked. As the validation shows, the designed control strategy can guarantee the robustness of the system, overcome the uncertainty of the system and control hovering movement.
The marine environment for hovering movement near the water is complicated. To effectively restrain the wave interference on hovering movement and control volatility of trim degree and deepness, an adaptive inverse control strategy is proposed. The unknown disturbances on hovering controlling system is restrained by the inverse controlling theory with variable parameter network and adjustment feedback.The simulation results validate the effectiveness of the control strategy. The strategy diminishes the wave interference successfully with good robust stability, leaving the original system not be affected.
Finally, as to the uncertainty of hydrodynamic parameter on hovering movement controlling models and intersectional coupling between freedom motions, the accurate inverse model could hardly be realized. The paper proposed an inverse controlling method based on data-driven control theory. The α-step inverse modeling method to a type of affine nonlinear MIMO system has been built based on multivariate statistical strategy. What's more, an inverse controlling system is built based on data-driven with a type of submarine as research object. The simulation results indicate the decoupling control strategy based on data-driven can precisely control hovering attitude.
引文
[1]Blidberg D R.Autonomous underwater vehicle:a tool for the ocean. Unmanned System, 1991,9(2):10-15P
[2]W. F. Klepsen et al. A study of the Impact of SSN 688 Class Submarine Design on a Generalized Advanced Casualtyship Control Training Device[R]. (AD764086), June 1973
[3]Harry F. Hemond, Amy V. Mueller, Michael Hemond. Field Testing of Lake Water Chemistry with a Portable and an AUV-based Mass Spectrometer Original Research.Journal of the American Society for Mass Spectrometry.2008,19(10): 1403-1410P
[4]Richard A. Stankey. "Trident Ship Control" System Development Program[R]. (AD-A045603),1975
[5]Giacomo Marani, Song K. Choi, Junku Yuh. Underwater autonomous manipulation for intervention missions AUVs Original Research.Ocean Engineering.2009,36(1): 15-23P
[6]J.G. Bellingham. Platforms:Autonomous Underwater Vehicles.Encyclopedia of Ocean Sciences.2009:473-484P
[7]潘国良.潜艇悬停及其发展综述.中国造船工程学会2006年船舶通讯导航学术会议.2006：216-221页
[8]1995.10-49 ABS.Guide for thrusters and dynamic positioning systems,1994:128-140P
[9]董志荣.论悬停潜艇攻击.光电与控制.2003,10(4)：1-4,9页
[10]董志荣.悬停潜艇目标定位与跟踪.情报指挥控制系统与仿真技术.2003.5：20-27页.
[11]朱德宝.对潜艇悬停技术及战术运用的思考.海军学术研究.2004(4)：23-25.
[12]Jin-Kyu Choi, Tetsuya Shiraishi, Toshinari Tanaka, Hayato Kondo. Safe operation of an autonomous underwater towed vehicle:Towed force monitoring and control Original Research. Automation in Construction, In Press, Corrected Proof, Available online 8 May 2011
[13]施生达.潜艇操纵性.北京：国防工业出版社,1995
[14]潘国良.潜艇水下悬停操纵原理研究.研究报告,707研究所九江分部,2004
[15]船舶水动力学词典[M].中国造船编辑部译.上海：中国造船编辑部,1981
[16]Richard R J, Stoten D P. Depth Control of a Submersible Vehicles. ISP.1981,28(318): 30-39P
[17]孙元泉,马运义等.潜艇和深潜器的现代操纵理论与应用.国防工业出版社,2001
[18]CREPEL J I, BO RIS A G.航向及深度控制系统设计的新趋势.第3th潜艇国际会议录,1991.
[19]杨惠民.国外核潜艇技术综述.潜艇.1986(1)：115-121页
[20]Smallwood D A, Whitcomb L L.Model-Based Dynamic Positioning of Underwater Robotic Vehicles:Theory and Experiment. Journal of Oceanic Engineering,2004,29(1):169-185P.
[21]H.R.叶费姆也夫.潜艇理论基础.北京：国防工业出版社,1975
[22]施生达.潜艇原理.武汉：海军工程大学出版社,1990
[23]潘国良.舰船操纵控制技术应用与分析.声学与电子工程,2005(增刊)：6-9
[24]R.K.Lea, Allen, S.L.Merry.A comparative study of control techniques for an underwater flight vehicle.Int.J.System Science,1990(9):947-964P
[25]Michael G.Daughan. Seawolf Submarine Ship Control System:A Case Study of a Fault-Tolerant Design[J]. Naval Engineers Journal. Feb.1994.
[26]AD 272 913.弹道导弹潜艇的先进船控操纵台.美国通用动力公司,1961.
[27]P.巴里诶.潜艇悬停时自动定深装里的设计与制造.法国航海与航空技术协会(ATHA),1970,N0.70：327-345P.
[28]施生达.关于潜艇操纵及其自动化技术的近期发展问题探讨.海军工程大学,2001.
[29]王淑英.潜艇操纵控制系统自动化发展研究.“十五”科研发展计划参考资料,中国舰船研究院.1999.
[30]陈训铨.潜艇操纵自动化的现状及发展.舰船操纵自动化技术专题文,2001.
[31]王学峰.常规潜艇水下悬停操纵及战术思考.潜艇42支队,2001.
[32]工崇挥.潜艇悬停技术研究.舰船工程研究,2007(2)：24-28页.
[33]Fjellstad Ola-Erik,Fossen Thor I.Position and Attitude Tracking of AUV's:A Quaternion Feedback A pproach.Journal of Oceanic Engineering,1994,19(4):512-518P.
[34]何卫华.潜器自动操纵控制系统的基本原理及其现状.舰船科学技术,2005,27(3)20-24页.
[35]龙建军,吴白海,肖体兵.小型潜器悬停控制的建模与辨识.机床与液压,2008,36(8)：201-203页.
[36]Eduardo Liceaga-Castro, Jesus Liceaga-Castro, Carlos E. Ugalde-Loo, Eva M. Navarro-Lopez. Efficient multivariable submarine depth-control system design Original Research. Ocean Engineering.2008,35(17-18):1747-1758P.
[37]Przemysaw Herman. Modified set-point controller for underwater vehicles Original Research. Mathematics and Computers in Simulation.2010,80(12):2317-2328P.
[38]Ji-Hong Li, Pan-Mook Lee. Design of an adaptive nonlinear controller for depth control of an autonomous underwater vehicle Original Research.Ocean Engineering.2005,32(17-18):2165-2181P.
[39]C. Silvestre, A. Pascoal. Control of the INFANTE AUV using gain scheduled static output feedback Original Research.Control Engineering Practice.2004, 12(12):1501-1509P.
[40]Li-Jun Zhang, Xue Qi, Yong-Jie Pang. Adaptive output feedback control based on DRFNN for AUV Original Research.Ocean Engineering.2009,36(9-10):716-722P.
[41]熊瑛,许建,何树阳.基于PID的潜器悬停控制仿真研究.舰船科学技术.2010,32(5)：107-110页.
[42]俞科云,戴余良,施生达.潜艇水下悬停运动控制仿真研究.中国舰船研究.2010,5(2)：18-21页.
[43]R.P. Kumar, C.S. Kumar, D. Sen, A. Dasgupta. Discrete time-delay control of an autonomous underwater vehicle:Theory and experimental results Original Research.Ocean Engineering,2009,36(1):74-81P.
[44]C. Silvestre, A. Pascoal. Depth control of the INFANTE AUV using gain-scheduled reduced order output feedback Original Research.Control Engineering Practice.2007,15(7):883-895P.
[45]Ming-Yong LIU, Wen-Bai LI, Xuan PEI. Convex Optimization Algorithms for Cooperative Localization in Autonomous Underwater Vehicles.Acta Automatica Sinica, Volume 36, Issue 5, May 2010,704-71 OP.
[46]Francisco Periago, Jorge Tiago. A local existence result for an optimal control problem modeling the manoeuvring of an underwater vehicle.Nonlinear Analysis:Real World Applications, Volume 11, Issue 4, August 2010,2573-2583P.
[47]熊瑛.基于智能控制的潜艇操纵运动仿真研究.中国舰船研究院,2011.
[48]肖永利,张琛,吴庆宪.QFT在水下潜器控制系统设计中的应用.上海交通大学学报,1999,33(4)：446-449页.
[49]Francisco Curado Teixeira, Antonio Pedro Aguiar, Antonio Pascoal. Nonlinear adaptive control of an underwater towed vehicle Original Research. Ocean Engineering.2010,37(13):1193-1220.
[50]A.Isidori, A.J.Krener, C.Gori-Gigogi and S.Monaco.Nonlinear decoupling via feedback: A differential geometory approach, IEEE Trans. Automat. Contr,1981,26(3): 331-345P.
[51]Bin Xu, Shunmugham R. Pandian, Norimitsu Sakagami, Fred Petry.Neuro-fuzzy control of underwater vehicle-manipulator systems.Journal of the Franklin Institute, Volume 349, Issue 3, April 2012,1125-1138P.
[52]Myeong-Jo Son, Tae-wan Kim.Torpedo evasion simulation of underwater vehicle using fuzzy-logic-based tactical decision making in script tactics manager.Expert Systems with Applications, Volume 39, Issue 9, July 2012,7995-8012P.
[53]Pradeep R. Nambisan, Sahjendra N. Singh.Multi-variable adaptive back-stepping control of submersibles using SDU decomposition.Ocean Engineering, Volume 36, Issue 2, February 2009,158-167P.
[54]A. Bagheri, T. Karimi, N. Amanifard.Tracking performance control of a cable communicated underwater vehicle using adaptive neural network controllers.Applied Soft Computing, Volume 10, Issue 3, June 2010,908-918P.
[55]Longxin Lin, Haibin Xie, Daibing Zhang, Lincheng Shen. Supervised Neural Qlearning based Motion Control for Bionic Underwater Robots.Journal of Bionic Engineering, Volume 7, Supplement, September 2010, S177-S184P
[56]潘瑛.远程自主式水下航行器分离与近水而运动操纵性研究.西北工业大学.2004.
[57]Song Feijun, Smith Samuel M. Design of sliding mode fuzzy controllers for an autonomous underwater vehicle without system model. Oceans Conference Record (IEEE),2000,2:835-840P.
[58]Guo J, Chiu F C, Huang C C. Design of a sliding mode fuzzy controller for the guidance and control of an autonomous underwater vehicle. Ocean Engineering,2003, 30(16):2137-2155P.
[59]Salgado-Jimenez T, Jouvencel B. Using a high order sliding modes for diving control a torpedo autonomous underwater vehicle.Oceans Conference Record (IEEE),2003, 2:934-939P.
[60]Wallace M. Bessa, Max S. Dutra, Edwin Kreuzer. An adaptive fuzzy sliding mode controller for remotely operated underwater vehicles Original Research. Robotics and Autonomous Systems.2010,58(1):16-26P.
[61]Cristi R, Papoulias F A, Healey A J.Adaptive sliding mode control of autonomous underwater vehicles in the dive plate.IEEE, Oceanic Eng,1990,15(3):245-250P.
[62]Ming-jun Zhang, Zhen-zhong Chu Adaptive sliding mode control based on local recurrent neural networks for underwater robot Ocean Engineering, Volume 45, May 2012,56-62P.
[63]J. Javadi-Moghaddam, A. Bagheri.An adaptive neuro-fuzzy sliding mode based genetic algorithm control system for under water remotely operated vehicle.Expert Systems with Applications, Volume 37, Issue 1, January 2010,647-660P
[64]赵国良,杨玉红.潜艇垂直面机动的多变量控制.中国造船,1989,(4)：107-116页.
[65]牟军,许汉珍.潜艇操纵运动的变结构控制.华中理工大学学报,1997,6.
[66]牟军.潜艇操纵运动的变结构控制系统研究.华中理工大学博士学论文,1997.
[67]J.Javadi-Moghaddam, A.Bagheri. An adaptive neuro-fuzzy sliding mode based genetic algorithm control system for under water remotely operated vehicle. Expert Systems with Applications,2010,37(1):647-660P.
[68]严卫生,张福斌,高剑.新型远程自主水下航行器侧向滑模变结构控制.鱼雷技术,2007,15(3)：19-21页.
[69]Lionel Lapierre. Robust diving control of an AUV Original Research.Ocean Engineering, 2009,36(1):92-104P.
[70]Mugdha S. Naik, Sahjendra N. Singh. State-dependent Riccati equation-based robust dive plane control of AUV with control constraints Original Research. Ocean Engineering.2007,34(11-12):1711-1723P.
[71]Jan Petrich, Daniel J. Stilwell. Robust control for an autonomous underwater vehicle that suppresses pitch and yaw coupling riginal Research. Ocean engineering. 2011,38(1):197-204P.
[72]Jonghui Han, Jonghoon Park, Wan Kyun Chung. Robust coordinated motion control of an underwater vehicle-manipulator system with minimizing restoring moments Original Research.Ocean Engineering.2011,38(10):1197-1206P.
[73]熊华胜,边信黔,施小成.自治水下机器人深度的鲁棒H∞控制仿真.计算机仿真,2007,24(3)：156-159页.
[74]West Michael E, Yuh Junku, Syrmos Vassilis L. A Nonlinear H-infinity Controller for Autonomous Underwater Vehicles.IEEE International Conference on Intelligent Robots and Systems,2003,1:583-588P.
[75]汪伟,边信黔,王大海.AUV深度的模糊神经网络滑模控制.机器人.2003,25(3)：209-212页.
[76]Tairen Sun, Hailong Pei, Yongping Pan, Caihong Zhang.Robust wavelet network control for a class of autonomous vehicles to track environmental contour line.Neurocomputing, Volume 74, Issue 17, October 2011,2886-2892P.
[77]Dai-Jin LI, Kai LUO, Yu-Wen ZHANG, Jian-Jun DANG.Studies on Fixed-depth Control of Supercavitating Vehicles.Acta Automatica Sinica, Volume 36, Issue 3, March 2010,421-426P.
[78]Zool H. Ismail, Matthew W. Dunnigan.A region boundary-based control scheme for an autonomous underwater vehicle. Ocean Engineering, Volume 38, Issues 17-18, December 2011,2270-2280 P.
[79]Shi-bo FAN, Lian LIAN, Ping REN, Guo-liang HUANG.Oblique towing test and maneuver simulation at low speed and large drift angle for deep sea open-framed remotely operated vehicle. Journal of Hydrodynamics, Ser. B, Volume 24, Issue 2, April 2012,280-286P.
[80]Alejandro Donaire, Tristan Perez.Dynamic positioning of marine craft using a port-Hamiltonian framework.Automatica, Volume 48, Issue 5, May 2012,851-856P.
[81]Campa Giampiero, Sharma Manu, Calise Anthony J, Innocenti Mario.Neural network augmentation of linear controllers with application to underwater vehicles. Proceedings of the American Control Conference,2000,1:75-79P.
[82]郭存良.6-DOF并联机器人动力学建模非线性解耦及控制.燕山大学硕士学位论文.2000：10-28页.
[83]Shao Zhiyu, Fang Dongyang, Feng Shunshan. Mathematical Simulation on Self-tuning Fuzzy Controller for Small Cylindrical Object Navigating near Free-surface Original Research.Procedia Engineering.2011,12:191-196P.
[84]Pepijn W.J. van de Ven, Tor A. Johansen, Asgeir J. Srensen, Colin Flanagan, Daniel Toal. Neural network augmented identification of underwater vehicle models Original Research.Control Engineering Practice.2007,15(6):715-725P.
[85]K. Ishaque, S.S. Abdullah, S.M. Ayob, Z. Salam. A simplified approach to design fuzzy logic controller for an underwater vehicle Original Research. Ocean Engineering.2011,38(1):271-284P.
[86]Longxin Lin, Haibin Xie, Daibing Zhang, Lincheng Shen. Supervised Neural Q_learning based Motion Control for Bionic Underwater Robots Original Research. Journal of Bionic Engineering.2010,7(1):S177-S184P.
[87]苏玉民,潜艇原理.哈尔滨：哈尔滨工程大学出版社.2005.
[88]何成等.潜艇悬停数学模型的理论探索.四川兵工学报.2009.30(2)：64-66.
[89]Nur Afande Ali Hussain, Mohd Rizal Arshad, Rosmiwati Mohd-Mokhtar.Underwater glider modelling and analysis for net buoyancy, depth and pitch angle control.Ocean Engineering, Volume 38, Issue 16, November 2011,1782-1791P.
[90]Xiaoming Wang, Jianzhong Shang, Zirong Luo, Li Tang, Xiangpo Zhang, Juan Li.Reviews of power systems and environmental energy conversion for unmanned underwater vehicles.Renewable and Sustainable Energy Reviews, Volume 16, Issue 4, May 2012,1958-1970P.
[91]C.S. Chin, S.H. Lum.Rapid modeling and control systems prototyping of a marine robotic vehicle with model uncertainties using xPC Target system.Ocean Engineering, Volume 38, Issues 17-18, December 2011,2128-2141P.
[92]Diana M. Ovalle, Javier Garcia, Francisco Periago.Analysis and numerical simulation of a nonlinear mathematical model for testing the manoeuvrability capabilities of a submarine.Nonlinear Analysis:Real World Applications, Volume 12, Issue 3, June 2011,1654-1669P.
[93]P. Jagadeesh, K. Murali, V.G. Idichandy. Experimental investigation of hydrodynamic force coefficients over AUV hull form Original Research.Ocean Engineering. 2009,36(1):113-118P.
[94]A. Alvarez, V. Bertram, L. Gualdesi. Hull hydrodynamic optimization of autonomous underwater vehicles operating at snorkeling depth Original Research.Ocean Engineering.2009,36(1):105-112P.
[95]O. Saout, P. Ananthakrishnan Hydrodynamic and dynamic analysis to determine the directional stability of an underwater vehicle near a free surface Original Research. Applied Ocean Research.2011,33(2):158-167P.
[96]Jan Petrich, Daniel J. Stilwell.Model simplification for AUV pitch-axis control design.Ocean Engineering, Volume 37, Issue 7, May 2010, ages 638-651P.
[97]郝英泽,何斌.海水密度变化对潜器悬停垂向运动的影响仿真研究[J].船海工程,2008,37(2)：117-119页.
[98]施生达,戴余良.潜器水下悬停运动数学模型.武汉：海军工程大学,2006.
[99]李殿璞.船舶运动与建模.哈尔滨：哈尔滨工程大学出版社.1999：102-131页.
[100]Orhan K. Babaoglu. "Designing Automatic control system for a submarine", AD-A203925,1988.
[101]赵小军,林莉,李明,万国龙.基于模糊控制的潜器悬停系统.舰船科学技术,2007,29(4)：114-116页.
[102]王科俊,姚绪梁,金鸿章.海洋运动体控制原理.哈尔滨：哈尔滨工程大学出版社,2005：260-272页.
[103]吕同富,康兆敏,方秀男.数值计算方法.北京：清华大学出版社.2008.
[104]CB/Z171-80潜艇下潜系统设计规则.
[105]周松辰.徐亦凡.潜艇运动数学模型的分析.潜艇学术研究,1996(1)；46-48.
[106]徐亦凡.潜艇操纵原理与方法.北京：兵器工业出版社,2002.
[107]郝英泽,何斌.海水密度变化对潜艇悬停垂向运动的影响仿真研究.船海工程.2008.37(2)：117-119页.
[108]宋保维,杜晓旭,胡海豹,王鹏.近水面悬停远航程AUV受波浪的影响.西北工业大学学报.2007,25(4)：482-486页.
[109]季鲁慧.潜艇运动多变量控制系统研究.哈尔滨船舶工程学院硕士论文.1989：66-70页.
[110]H.H叶费姆也夫.潜艇理论基础.国防工业出版社,1975.
[111]Lee C M, Newman J N.First-and second-order wave effects on a submerged spheroid.J.S.R.1991,35(3):183-190P.
[112]缪泉明,冯学知,孙伯起.圆柱体在近水面的波浪力计算.中国船舶科学研究中心科技报告,1992.
[113]冯学知,孙伯起,缪泉明.潜艇近水面波浪扰动力研究.中国船舶科学研究中心科技报告,1996.
[114]PAPOULIAS F. A. PAPADIMITRIOU H. A. Nonlinear studies of dynamic stability of submarines in the dive plane. Journal of ship research,1995(39):347-356P.
[115]闵耀元,闫学琳.波浪中潜艇近水面操纵控制规律.719所科技报告,2000.
[116]王鹢,王文武,孙枫,王国夫.干扰力作用下潜艇近水面运动的仿真.系统仿真学报,2003,15(1)：84-87页.
[117]邱大洪.波浪理论及其在工程上的应用.北京：高等教育出版社,1985：74-90页.
[118]金鸿章.长峰波随机海浪的实时仿真和频谱分析.船舶工程,1987,2(1)：24-30页.
[119]冯学知,蒋强强,缪泉明,匡晓峰.潜体波浪中近水面不同潜深和航向时运动和波浪力计算.船舶力学,2002,6(2)：1-14页.
[120]Howze J.W.Necessary and sufficient condition for decoupling using feedback. IEEE Trans.Automat Control,1973(18):44-46P.
[121]Battilotti S.Noninteraction via measurement feedback for nonlinear systems with relative degree, IEEE Transactions on Automatic Control,1999(44):774-778P.
[122]段海富等.非线性系统解耦控制理论在飞控中的应用.电光与控制.2001(4)：30-34页.
[123]S. Mohammed, P. Poignet, P. Fraisse, D. Guiraud.Toward lower limbs movement restoration with input-output feedback linearization and model predictive control through functional electrical stimulation.Control Engineering Practice, Volume 20, Issue 2, February 2012,182-195P.
[124]李永刚,宋轶民,张策.基于现代微分几何的机器人研究现状.中国机械工程.2007,18(2)：238-243页.
[125]苏柏泉.微分几何方法在潜器操纵运动中的研究.哈尔滨工程大学硕士学位论 文.2006：29-50页.
[126]Shukai Li, Jianxiong Zhang, Wansheng Tang.Robust output feedback control for uncertain complex delayed dynamical networks.Computers & Mathematics with Applications, Volume 62, Issue 1, July 2011,497-505P.
[127]Chyun-Chau Fuh, Hsun-Heng Tsai, Wei-Hann Yao. Combining a feedback linearization controller with a disturbance observer to control a chaotic system under external excitation.Communications in Nonlinear Science and Numerical Simulation, Volume 17, Issue 3, March 2012,1423-1429P.]
[128]陈省身,陈维桓.微分几何讲义.北京：北京大学出版社,1983：143-152页.
[129]Isidori A.Nonlinear Control Systems.New York:Springer Press,1989:234-281P.
[130]J.J.E. Slotine, W.Li.Applied Nonlinear Control. Englewood Cliffs, NJ:Prentice-Hall, 1991:23-48P.
[131]Wen Tong, Fang Jiancheng.A feedback linearization control for the nonlinear 5-DOF flywheel suspended by the permanent magnet biased hybrid magnetic bearings.Acta Astronautica, Volume 79, October-November 2012,131-139P.
[132]R.K.Lea, Allen, S.L.Merry.A comparative study of control techniques for an underwater flight vehicle.Int.J.System Science,1990(9):947-964P.
[133]冯俊梅,连琏,葛彤.潜艇操纵控制方法的现状与发展.海洋工程,2005,23(1)：114-122页.
[134]Cristi R, Papoulias F A, Healey A J.Adaptive sliding mode control of autonomous underwater vehicles in the dive plate.IEEE, Oceanic Eng,1990,15(3):245-250P
[135]Yuxin Su, Chunhong Zheng.Global finite-time inverse tracking control of robot manipulators.Robotics and Computer-Integrated Manufacturing, Volume 27, Issue 3, June 2011.550-557P.
[136]Jing Na, Xuemei Ren, Guido Herrmann, Zhi Qiao.Adaptive neural dynamic surface control for servo systems with unknown dead-zone.Control Engineering Practice, Volume 19, Issue 11, November 2011,1328-1343P.
[137]Hanlei Wang, Yongchun Xie.Adaptive inverse dynamics control of robots with uncertain kinematics and dynamics.Automatica, Volume 45, Issue 9, September 2009, 2114-2119P.
[138]华克强,朱齐丹.逆系统理论在水下机器人控制中的应用.哈尔滨船舶工程学院学报,1990,11(1)：50-60页.
[139]Asma Atig, Fabrice Druaux, Dimitri Lefebvre, Kamel Abderrahim, Ridha Ben Abdennour.Adaptive control design using stability analysis and tracking errors dynamics for nonlinear square MIMO systems.Engineering Applications of Artificial Intelligence, In Press, Corrected Proof, Available online 30 August 2011.
[140]吴热冰,李春文.一般非线性系统的构造性逆系统方法.控制理论与应用,2003,20(3)：345-351页.
[141]B.Widrow, E. Walach.刘树堂,韩崇昭译.自适应逆控制.西安交通大学出版社,2000：163-172页.
[142]B.Widrow, E.Walach.Adaptive inverse control.Upper saddle river, NJ:Prentice Hall, 1996:1-158P.
[143]Mou Chen, Shuzhi Sam Ge, Beibei Ren.Adaptive tracking control of uncertain MIMO nonlinear systems with input constraints.Automatica, Volume 47, Issue 3, March 2011, 452-465P.
[144]V. Nekoukar, A. Erfanian.Adaptive fuzzy terminal sliding mode control for a class of MIMO uncertain nonlinear systems.Fuzzy Sets and Systems, Volume 179, Issue 1,16 September 2011,34-49P.
[145]DAI Xian-zhong, HE Dan.ANN generalized inversion for the linearization and decoupling control of nonlinear systems.IEEE Proceedings Control Theory Applications,2003,150(3):267-277P.
[146]戴先中.多变量非线性系统的神经网络逆控制方法.科学出版社,2005：43-52页
[147]戴先中,刘军,冯纯伯.连续非线性系统的神经网络a阶逆系统控制方法.自动化学报,1998,24(4)：463-468页.
[148]李春文,冯元琨.多变量非线性控制的逆系统方法.清华大学出版社,1991：168-175页.
[149]侯忠生,许建新.数据驱动控制理论及方法的回顾和展望.自动化学报.2009,35(6)：650-667页.
[150]Yuanqing Xia, Wen Xie, Bo Liu, Xiaoyun Wang.Data-driven predictive control for networked control systems.Information Sciences, In Press, Corrected Proof, Available online 16 February 2012.
[151]Yiming Wan, Hao Ye.Data-driven diagnosis of sensor precision degradation in the presence of control.Journal of Process Control, Volume 22, Issue 1, January 2012, 26-40P.
[152]K. Yamuna Rani.Sensitivity Compensating Control:Data-driven model based adaptive approachJournal of Process Control, Volume 21, Issue 9, October 2011,1265-1286P.
[153]Chang-Chun Pan, Cheng-I Sun, Shi-Shang Jang, David Shan-Hill Wong, Gen-Ke Yang.A MIMO R2R control using data-driven gain scheduling. Control Engineering Practice, Volume 19, Issue 11, November 2011,1344-1353P.
[154]Andrew Kusiak, Zijun Zhang.Control of wind turbine power and vibration with a data-driven approach.Renewable Energy, Volume 43, July 2012,73-82P.
[155]D. Lauri, J.A. Rossiter, J. Sanchis, M. Martinez.Data-driven latent-variable model-based predictive control for continuous processes Journal of Process Control, Volume 20, Issue 10, December 2010,1207-1219P.
[156]Hou Zhong-Sheng. The Parameter Identification, Adaptive Control and Model Free Learning Adaptive Control for Nonlinear Systems[Ph. D. dissertation], Northeastern University, China,1994.
[157]Hou Zhong-Sheng. Nonparametric Models and Its Adaptive Control Theory. Beijing: Science Press,1999.
[158]Uchiyama M. Formulation of high-speed motion pattern of a mechanical arm by trial. Transactions of the Society for instrumentation and Control Engineering, 1978,14(6):706-712P.
[159]Hou Z S, Xu J X, Yan J W. An iterative learning approach for density control of freeway traffic flow via ramp metering.Transportation Research,Part C:Emerging Technologies,2008,16(1):71-97P.
[160]Hyo-Sung A, Chen YQ, Moore K L. Iterative learning control:brief survey and categorization. IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews,2007,37(6):1099-1121P.
[161]许建新,侯忠生.学习控制的现状与展望.自动化学报.2005,31(6)：943-955页.
[162]Spall J C. Multivariate stochastic approximation using a simultaneous perturbation gradient approximation. IEEE Transactions on Automatic Control.1992,37(3): 332-341P.
[163]Spall J C, Cristion J A. Model-free control of general discrete-time systems. In:Proceedings of the 32nd IEEE Conference on Decision and Control.San Antonio,USA:IEEE,1993.2792-2797P.
[164]Werbos P J. Advanced forecasting methods for global crisis warning and models of intelligence. General Systems Yearbook,1977,22:25-38P.
[165]Lee J M, Lee J H. Approximate dynamic programming based approaches for input-output data-driven control of nonlinear processes. Automatica,2005,41(7): 1281-1288P.
[166]Guardabassi G O, Savaresi S M. Virtual reference directn design method:an off-line approach to data-based control system design. IEEE Transactions on Automatic Control,2000,45(5):954-959P.
[167]Campi M C, Savaresi S M. Direct nonlinear control de sign:the virtual reference feedback tuning (VRFT) approach. IEEE Transactions on Automatic Control, 2006,51(1):15-27P.
[168]Previdi F, Schauer T, Savaresi S M, Hunt K J. Data-driven control design for neuroprotheses:a virtual reference feed back tuning (VRFT) approach. IEEE Transactions on Control Systems Technolog,2004,12(1):176-182P.
[169]Hjalmarsson H, Gunnarsson S,Gevers M. A convergent iterative restricted complexity control design scheme. In:Proceedings of the 33rd IEEE Conference on Decision and Control. Lake Buena Vista, USA:IEEE,1994.1735-1740P.
[170]Graham A E, Young A J, Xie S Q.Rapid tuning of controllers by IFT for profile cutting machines.Mechatronics,2007,17(2-3):121-128P.
[171]Precup R E, Preitl S, Rudas I J, Tomescu M L, Tar J K. Design and experiments for a class of fuzzy controlled servo systems. IEEE/ASME Transactions on Mechatronics, 2008,13(1):22-35P.
[172]Schaal S, Atkeson C G. Robot juggling:implementation of memory-based learning. IEEE Control Systems Magazine,1994,14(1):57-71P.
[173]Pan T H, Li S Y. A hierarchical search and updating database strategy for lazy learning. International Journal of Innovative Computing, Information and Control,2008,4(6): 1383-1392P.
[174]王成红,宋苏,孙长银.关于“基于数据的控制”的几点思考,技术报告,国家自然科学基金委员会第33期双清论坛“基于数据驭动的控制决策调度与故障诊断”学术研讨会,北京,2008.
[175]侯忠生,许建新.数据驱动控制理论及方法的现状和展望,技术报告,国家自然科学基金委员会第33期双清论坛“基于数据驱动的控制、决策、调度与故障诊断”学术研讨会北京.2008.
[176]Karimi A, Miskovic L, Bonvin D. Convergence analysis of an iterative correlation-based controller tuning method. In Proceedings of the 15th IF AC World Congress.Barcelona,Spain:IFAC,2002.1546-1551 P.
[177]Miskovic L, Karixni A, Bonvin D, Levers M. Correlation based tuning of decoupling multivariable controllers. Automatica,2007,43(9):1481-1494P.
[178]Safonov M G, Tsao T C. The unfalsified control concept:a direct path from experiment to controller. Feedback Control, Nonlinear Systems, and Complexity. Berlin: SpringerVerlag,1995.196-214P.
[179]van Helvoort J, de Jager B, Steinbuch M. Direct data-driven recursive controller unfalsification with analytic update. Automatica,2007,43(12):2034-2046P.
[180]van Helvoort J, de Jager B, Steinbuch M. Data-driven multivariable controller design using ellipsoidal unfalsified control. Systems and Control Letters,2008,57(9): 759-762P.
[181]Der-Chiang Li, Chiao-Wen Liu.A class possibility based kernel to increase classification accuracy for small data sets using support vector machines.Expert Systems with Applications, Volume 37, Issue 4, April 2010,3104-3110P.
[182]戴先中,孟正大等.神经网络α阶逆系统控制方法在机器人解耦控制中的应用[J].机器人,2001,23(4)：363-367页.
[183]陈小红,侯春海等.逆系统方法的径向基函数网络实现.控制与决策,1998,13(2)：146-150页.
[184]Zeng-Zhou Jia, Yu Huang etc. Robotic Manipul-ators Decoupling Control Based on ANN a th-order Inverse System Method. Proceedings of the Fourth International Conference on Machine Learning and Cybernetics. Guangzhou,2005.
[185]Mohsen Behzad, Keyvan Asghari, Morteza Eazi, Maziar Palhang.Generalization performance of support vector machines and neural networks in runoff modeling.Expert Systems with Applications, Volume 36, Issue 4, May 2009,7624-7629P
[186]李春文,冯元琨.多变量非线性控制的逆系统方法.北京：清华大学出版社,1991.
[187]Isidori A. Nonlinear Control Systems. New York:Springer Press,1989:234-281P.
[188]Suykens J.A.K., Vandewalle J., Chaos control using least squares support vector machines, International Journal of Circuit Theory and Applications, Special Issue on Communications, Information Processing and Control using Chaos, vol.27, no.6, Nov. 1999:605-615P.
[189]Suykens J.A.K., Vandewalle J., Recurrent least squares support vector machines, IEEE Transactions on Circuits and Systems-I, vol.47, no.7, Jul.2000:1109-1114P.
[190]宋夫华,李平.基于支持向量机α阶逆系统方法的非线性内模控制.自动化学报,2007,33(7)：778-781页.
[191]张浩然,韩正之等.基于支持向量机的未知非线性系统辨识与控制.上海交通大学学报.2003,37(6)：927-930页.
[192]刘陆洲,肖建,刘杰.一种新型神经网络广义逆系统.控制与决策.2009,24(9)：1390-1393页.
[2]W. F. Klepsen et al. A study of the Impact of SSN 688 Class Submarine Design on a Generalized Advanced Casualtyship Control Training Device[R]. (AD764086), June 1973
[3]Harry F. Hemond, Amy V. Mueller, Michael Hemond. Field Testing of Lake Water Chemistry with a Portable and an AUV-based Mass Spectrometer Original Research.Journal of the American Society for Mass Spectrometry.2008,19(10): 1403-1410P
[4]Richard A. Stankey. "Trident Ship Control" System Development Program[R]. (AD-A045603),1975
[5]Giacomo Marani, Song K. Choi, Junku Yuh. Underwater autonomous manipulation for intervention missions AUVs Original Research.Ocean Engineering.2009,36(1): 15-23P
[6]J.G. Bellingham. Platforms:Autonomous Underwater Vehicles.Encyclopedia of Ocean Sciences.2009:473-484P
[7]潘国良.潜艇悬停及其发展综述.中国造船工程学会2006年船舶通讯导航学术会议.2006：216-221页
[8]1995.10-49 ABS.Guide for thrusters and dynamic positioning systems,1994:128-140P
[9]董志荣.论悬停潜艇攻击.光电与控制.2003,10(4)：1-4,9页
[10]董志荣.悬停潜艇目标定位与跟踪.情报指挥控制系统与仿真技术.2003.5：20-27页.
[11]朱德宝.对潜艇悬停技术及战术运用的思考.海军学术研究.2004(4)：23-25.
[12]Jin-Kyu Choi, Tetsuya Shiraishi, Toshinari Tanaka, Hayato Kondo. Safe operation of an autonomous underwater towed vehicle:Towed force monitoring and control Original Research. Automation in Construction, In Press, Corrected Proof, Available online 8 May 2011
[13]施生达.潜艇操纵性.北京：国防工业出版社,1995
[14]潘国良.潜艇水下悬停操纵原理研究.研究报告,707研究所九江分部,2004
[15]船舶水动力学词典[M].中国造船编辑部译.上海：中国造船编辑部,1981
[16]Richard R J, Stoten D P. Depth Control of a Submersible Vehicles. ISP.1981,28(318): 30-39P
[17]孙元泉,马运义等.潜艇和深潜器的现代操纵理论与应用.国防工业出版社,2001
[18]CREPEL J I, BO RIS A G.航向及深度控制系统设计的新趋势.第3th潜艇国际会议录,1991.
[19]杨惠民.国外核潜艇技术综述.潜艇.1986(1)：115-121页
[20]Smallwood D A, Whitcomb L L.Model-Based Dynamic Positioning of Underwater Robotic Vehicles:Theory and Experiment. Journal of Oceanic Engineering,2004,29(1):169-185P.
[21]H.R.叶费姆也夫.潜艇理论基础.北京：国防工业出版社,1975
[22]施生达.潜艇原理.武汉：海军工程大学出版社,1990
[23]潘国良.舰船操纵控制技术应用与分析.声学与电子工程,2005(增刊)：6-9
[24]R.K.Lea, Allen, S.L.Merry.A comparative study of control techniques for an underwater flight vehicle.Int.J.System Science,1990(9):947-964P
[25]Michael G.Daughan. Seawolf Submarine Ship Control System:A Case Study of a Fault-Tolerant Design[J]. Naval Engineers Journal. Feb.1994.
[26]AD 272 913.弹道导弹潜艇的先进船控操纵台.美国通用动力公司,1961.
[27]P.巴里诶.潜艇悬停时自动定深装里的设计与制造.法国航海与航空技术协会(ATHA),1970,N0.70：327-345P.
[28]施生达.关于潜艇操纵及其自动化技术的近期发展问题探讨.海军工程大学,2001.
[29]王淑英.潜艇操纵控制系统自动化发展研究.“十五”科研发展计划参考资料,中国舰船研究院.1999.
[30]陈训铨.潜艇操纵自动化的现状及发展.舰船操纵自动化技术专题文,2001.
[31]王学峰.常规潜艇水下悬停操纵及战术思考.潜艇42支队,2001.
[32]工崇挥.潜艇悬停技术研究.舰船工程研究,2007(2)：24-28页.
[33]Fjellstad Ola-Erik,Fossen Thor I.Position and Attitude Tracking of AUV's:A Quaternion Feedback A pproach.Journal of Oceanic Engineering,1994,19(4):512-518P.
[34]何卫华.潜器自动操纵控制系统的基本原理及其现状.舰船科学技术,2005,27(3)20-24页.
[35]龙建军,吴白海,肖体兵.小型潜器悬停控制的建模与辨识.机床与液压,2008,36(8)：201-203页.
[36]Eduardo Liceaga-Castro, Jesus Liceaga-Castro, Carlos E. Ugalde-Loo, Eva M. Navarro-Lopez. Efficient multivariable submarine depth-control system design Original Research. Ocean Engineering.2008,35(17-18):1747-1758P.
[37]Przemysaw Herman. Modified set-point controller for underwater vehicles Original Research. Mathematics and Computers in Simulation.2010,80(12):2317-2328P.
[38]Ji-Hong Li, Pan-Mook Lee. Design of an adaptive nonlinear controller for depth control of an autonomous underwater vehicle Original Research.Ocean Engineering.2005,32(17-18):2165-2181P.
[39]C. Silvestre, A. Pascoal. Control of the INFANTE AUV using gain scheduled static output feedback Original Research.Control Engineering Practice.2004, 12(12):1501-1509P.
[40]Li-Jun Zhang, Xue Qi, Yong-Jie Pang. Adaptive output feedback control based on DRFNN for AUV Original Research.Ocean Engineering.2009,36(9-10):716-722P.
[41]熊瑛,许建,何树阳.基于PID的潜器悬停控制仿真研究.舰船科学技术.2010,32(5)：107-110页.
[42]俞科云,戴余良,施生达.潜艇水下悬停运动控制仿真研究.中国舰船研究.2010,5(2)：18-21页.
[43]R.P. Kumar, C.S. Kumar, D. Sen, A. Dasgupta. Discrete time-delay control of an autonomous underwater vehicle:Theory and experimental results Original Research.Ocean Engineering,2009,36(1):74-81P.
[44]C. Silvestre, A. Pascoal. Depth control of the INFANTE AUV using gain-scheduled reduced order output feedback Original Research.Control Engineering Practice.2007,15(7):883-895P.
[45]Ming-Yong LIU, Wen-Bai LI, Xuan PEI. Convex Optimization Algorithms for Cooperative Localization in Autonomous Underwater Vehicles.Acta Automatica Sinica, Volume 36, Issue 5, May 2010,704-71 OP.
[46]Francisco Periago, Jorge Tiago. A local existence result for an optimal control problem modeling the manoeuvring of an underwater vehicle.Nonlinear Analysis:Real World Applications, Volume 11, Issue 4, August 2010,2573-2583P.
[47]熊瑛.基于智能控制的潜艇操纵运动仿真研究.中国舰船研究院,2011.
[48]肖永利,张琛,吴庆宪.QFT在水下潜器控制系统设计中的应用.上海交通大学学报,1999,33(4)：446-449页.
[49]Francisco Curado Teixeira, Antonio Pedro Aguiar, Antonio Pascoal. Nonlinear adaptive control of an underwater towed vehicle Original Research. Ocean Engineering.2010,37(13):1193-1220.
[50]A.Isidori, A.J.Krener, C.Gori-Gigogi and S.Monaco.Nonlinear decoupling via feedback: A differential geometory approach, IEEE Trans. Automat. Contr,1981,26(3): 331-345P.
[51]Bin Xu, Shunmugham R. Pandian, Norimitsu Sakagami, Fred Petry.Neuro-fuzzy control of underwater vehicle-manipulator systems.Journal of the Franklin Institute, Volume 349, Issue 3, April 2012,1125-1138P.
[52]Myeong-Jo Son, Tae-wan Kim.Torpedo evasion simulation of underwater vehicle using fuzzy-logic-based tactical decision making in script tactics manager.Expert Systems with Applications, Volume 39, Issue 9, July 2012,7995-8012P.
[53]Pradeep R. Nambisan, Sahjendra N. Singh.Multi-variable adaptive back-stepping control of submersibles using SDU decomposition.Ocean Engineering, Volume 36, Issue 2, February 2009,158-167P.
[54]A. Bagheri, T. Karimi, N. Amanifard.Tracking performance control of a cable communicated underwater vehicle using adaptive neural network controllers.Applied Soft Computing, Volume 10, Issue 3, June 2010,908-918P.
[55]Longxin Lin, Haibin Xie, Daibing Zhang, Lincheng Shen. Supervised Neural Qlearning based Motion Control for Bionic Underwater Robots.Journal of Bionic Engineering, Volume 7, Supplement, September 2010, S177-S184P
[56]潘瑛.远程自主式水下航行器分离与近水而运动操纵性研究.西北工业大学.2004.
[57]Song Feijun, Smith Samuel M. Design of sliding mode fuzzy controllers for an autonomous underwater vehicle without system model. Oceans Conference Record (IEEE),2000,2:835-840P.
[58]Guo J, Chiu F C, Huang C C. Design of a sliding mode fuzzy controller for the guidance and control of an autonomous underwater vehicle. Ocean Engineering,2003, 30(16):2137-2155P.
[59]Salgado-Jimenez T, Jouvencel B. Using a high order sliding modes for diving control a torpedo autonomous underwater vehicle.Oceans Conference Record (IEEE),2003, 2:934-939P.
[60]Wallace M. Bessa, Max S. Dutra, Edwin Kreuzer. An adaptive fuzzy sliding mode controller for remotely operated underwater vehicles Original Research. Robotics and Autonomous Systems.2010,58(1):16-26P.
[61]Cristi R, Papoulias F A, Healey A J.Adaptive sliding mode control of autonomous underwater vehicles in the dive plate.IEEE, Oceanic Eng,1990,15(3):245-250P.
[62]Ming-jun Zhang, Zhen-zhong Chu Adaptive sliding mode control based on local recurrent neural networks for underwater robot Ocean Engineering, Volume 45, May 2012,56-62P.
[63]J. Javadi-Moghaddam, A. Bagheri.An adaptive neuro-fuzzy sliding mode based genetic algorithm control system for under water remotely operated vehicle.Expert Systems with Applications, Volume 37, Issue 1, January 2010,647-660P
[64]赵国良,杨玉红.潜艇垂直面机动的多变量控制.中国造船,1989,(4)：107-116页.
[65]牟军,许汉珍.潜艇操纵运动的变结构控制.华中理工大学学报,1997,6.
[66]牟军.潜艇操纵运动的变结构控制系统研究.华中理工大学博士学论文,1997.
[67]J.Javadi-Moghaddam, A.Bagheri. An adaptive neuro-fuzzy sliding mode based genetic algorithm control system for under water remotely operated vehicle. Expert Systems with Applications,2010,37(1):647-660P.
[68]严卫生,张福斌,高剑.新型远程自主水下航行器侧向滑模变结构控制.鱼雷技术,2007,15(3)：19-21页.
[69]Lionel Lapierre. Robust diving control of an AUV Original Research.Ocean Engineering, 2009,36(1):92-104P.
[70]Mugdha S. Naik, Sahjendra N. Singh. State-dependent Riccati equation-based robust dive plane control of AUV with control constraints Original Research. Ocean Engineering.2007,34(11-12):1711-1723P.
[71]Jan Petrich, Daniel J. Stilwell. Robust control for an autonomous underwater vehicle that suppresses pitch and yaw coupling riginal Research. Ocean engineering. 2011,38(1):197-204P.
[72]Jonghui Han, Jonghoon Park, Wan Kyun Chung. Robust coordinated motion control of an underwater vehicle-manipulator system with minimizing restoring moments Original Research.Ocean Engineering.2011,38(10):1197-1206P.
[73]熊华胜,边信黔,施小成.自治水下机器人深度的鲁棒H∞控制仿真.计算机仿真,2007,24(3)：156-159页.
[74]West Michael E, Yuh Junku, Syrmos Vassilis L. A Nonlinear H-infinity Controller for Autonomous Underwater Vehicles.IEEE International Conference on Intelligent Robots and Systems,2003,1:583-588P.
[75]汪伟,边信黔,王大海.AUV深度的模糊神经网络滑模控制.机器人.2003,25(3)：209-212页.
[76]Tairen Sun, Hailong Pei, Yongping Pan, Caihong Zhang.Robust wavelet network control for a class of autonomous vehicles to track environmental contour line.Neurocomputing, Volume 74, Issue 17, October 2011,2886-2892P.
[77]Dai-Jin LI, Kai LUO, Yu-Wen ZHANG, Jian-Jun DANG.Studies on Fixed-depth Control of Supercavitating Vehicles.Acta Automatica Sinica, Volume 36, Issue 3, March 2010,421-426P.
[78]Zool H. Ismail, Matthew W. Dunnigan.A region boundary-based control scheme for an autonomous underwater vehicle. Ocean Engineering, Volume 38, Issues 17-18, December 2011,2270-2280 P.
[79]Shi-bo FAN, Lian LIAN, Ping REN, Guo-liang HUANG.Oblique towing test and maneuver simulation at low speed and large drift angle for deep sea open-framed remotely operated vehicle. Journal of Hydrodynamics, Ser. B, Volume 24, Issue 2, April 2012,280-286P.
[80]Alejandro Donaire, Tristan Perez.Dynamic positioning of marine craft using a port-Hamiltonian framework.Automatica, Volume 48, Issue 5, May 2012,851-856P.
[81]Campa Giampiero, Sharma Manu, Calise Anthony J, Innocenti Mario.Neural network augmentation of linear controllers with application to underwater vehicles. Proceedings of the American Control Conference,2000,1:75-79P.
[82]郭存良.6-DOF并联机器人动力学建模非线性解耦及控制.燕山大学硕士学位论文.2000：10-28页.
[83]Shao Zhiyu, Fang Dongyang, Feng Shunshan. Mathematical Simulation on Self-tuning Fuzzy Controller for Small Cylindrical Object Navigating near Free-surface Original Research.Procedia Engineering.2011,12:191-196P.
[84]Pepijn W.J. van de Ven, Tor A. Johansen, Asgeir J. Srensen, Colin Flanagan, Daniel Toal. Neural network augmented identification of underwater vehicle models Original Research.Control Engineering Practice.2007,15(6):715-725P.
[85]K. Ishaque, S.S. Abdullah, S.M. Ayob, Z. Salam. A simplified approach to design fuzzy logic controller for an underwater vehicle Original Research. Ocean Engineering.2011,38(1):271-284P.
[86]Longxin Lin, Haibin Xie, Daibing Zhang, Lincheng Shen. Supervised Neural Q_learning based Motion Control for Bionic Underwater Robots Original Research. Journal of Bionic Engineering.2010,7(1):S177-S184P.
[87]苏玉民,潜艇原理.哈尔滨：哈尔滨工程大学出版社.2005.
[88]何成等.潜艇悬停数学模型的理论探索.四川兵工学报.2009.30(2)：64-66.
[89]Nur Afande Ali Hussain, Mohd Rizal Arshad, Rosmiwati Mohd-Mokhtar.Underwater glider modelling and analysis for net buoyancy, depth and pitch angle control.Ocean Engineering, Volume 38, Issue 16, November 2011,1782-1791P.
[90]Xiaoming Wang, Jianzhong Shang, Zirong Luo, Li Tang, Xiangpo Zhang, Juan Li.Reviews of power systems and environmental energy conversion for unmanned underwater vehicles.Renewable and Sustainable Energy Reviews, Volume 16, Issue 4, May 2012,1958-1970P.
[91]C.S. Chin, S.H. Lum.Rapid modeling and control systems prototyping of a marine robotic vehicle with model uncertainties using xPC Target system.Ocean Engineering, Volume 38, Issues 17-18, December 2011,2128-2141P.
[92]Diana M. Ovalle, Javier Garcia, Francisco Periago.Analysis and numerical simulation of a nonlinear mathematical model for testing the manoeuvrability capabilities of a submarine.Nonlinear Analysis:Real World Applications, Volume 12, Issue 3, June 2011,1654-1669P.
[93]P. Jagadeesh, K. Murali, V.G. Idichandy. Experimental investigation of hydrodynamic force coefficients over AUV hull form Original Research.Ocean Engineering. 2009,36(1):113-118P.
[94]A. Alvarez, V. Bertram, L. Gualdesi. Hull hydrodynamic optimization of autonomous underwater vehicles operating at snorkeling depth Original Research.Ocean Engineering.2009,36(1):105-112P.
[95]O. Saout, P. Ananthakrishnan Hydrodynamic and dynamic analysis to determine the directional stability of an underwater vehicle near a free surface Original Research. Applied Ocean Research.2011,33(2):158-167P.
[96]Jan Petrich, Daniel J. Stilwell.Model simplification for AUV pitch-axis control design.Ocean Engineering, Volume 37, Issue 7, May 2010, ages 638-651P.
[97]郝英泽,何斌.海水密度变化对潜器悬停垂向运动的影响仿真研究[J].船海工程,2008,37(2)：117-119页.
[98]施生达,戴余良.潜器水下悬停运动数学模型.武汉：海军工程大学,2006.
[99]李殿璞.船舶运动与建模.哈尔滨：哈尔滨工程大学出版社.1999：102-131页.
[100]Orhan K. Babaoglu. "Designing Automatic control system for a submarine", AD-A203925,1988.
[101]赵小军,林莉,李明,万国龙.基于模糊控制的潜器悬停系统.舰船科学技术,2007,29(4)：114-116页.
[102]王科俊,姚绪梁,金鸿章.海洋运动体控制原理.哈尔滨：哈尔滨工程大学出版社,2005：260-272页.
[103]吕同富,康兆敏,方秀男.数值计算方法.北京：清华大学出版社.2008.
[104]CB/Z171-80潜艇下潜系统设计规则.
[105]周松辰.徐亦凡.潜艇运动数学模型的分析.潜艇学术研究,1996(1)；46-48.
[106]徐亦凡.潜艇操纵原理与方法.北京：兵器工业出版社,2002.
[107]郝英泽,何斌.海水密度变化对潜艇悬停垂向运动的影响仿真研究.船海工程.2008.37(2)：117-119页.
[108]宋保维,杜晓旭,胡海豹,王鹏.近水面悬停远航程AUV受波浪的影响.西北工业大学学报.2007,25(4)：482-486页.
[109]季鲁慧.潜艇运动多变量控制系统研究.哈尔滨船舶工程学院硕士论文.1989：66-70页.
[110]H.H叶费姆也夫.潜艇理论基础.国防工业出版社,1975.
[111]Lee C M, Newman J N.First-and second-order wave effects on a submerged spheroid.J.S.R.1991,35(3):183-190P.
[112]缪泉明,冯学知,孙伯起.圆柱体在近水面的波浪力计算.中国船舶科学研究中心科技报告,1992.
[113]冯学知,孙伯起,缪泉明.潜艇近水面波浪扰动力研究.中国船舶科学研究中心科技报告,1996.
[114]PAPOULIAS F. A. PAPADIMITRIOU H. A. Nonlinear studies of dynamic stability of submarines in the dive plane. Journal of ship research,1995(39):347-356P.
[115]闵耀元,闫学琳.波浪中潜艇近水面操纵控制规律.719所科技报告,2000.
[116]王鹢,王文武,孙枫,王国夫.干扰力作用下潜艇近水面运动的仿真.系统仿真学报,2003,15(1)：84-87页.
[117]邱大洪.波浪理论及其在工程上的应用.北京：高等教育出版社,1985：74-90页.
[118]金鸿章.长峰波随机海浪的实时仿真和频谱分析.船舶工程,1987,2(1)：24-30页.
[119]冯学知,蒋强强,缪泉明,匡晓峰.潜体波浪中近水面不同潜深和航向时运动和波浪力计算.船舶力学,2002,6(2)：1-14页.
[120]Howze J.W.Necessary and sufficient condition for decoupling using feedback. IEEE Trans.Automat Control,1973(18):44-46P.
[121]Battilotti S.Noninteraction via measurement feedback for nonlinear systems with relative degree, IEEE Transactions on Automatic Control,1999(44):774-778P.
[122]段海富等.非线性系统解耦控制理论在飞控中的应用.电光与控制.2001(4)：30-34页.
[123]S. Mohammed, P. Poignet, P. Fraisse, D. Guiraud.Toward lower limbs movement restoration with input-output feedback linearization and model predictive control through functional electrical stimulation.Control Engineering Practice, Volume 20, Issue 2, February 2012,182-195P.
[124]李永刚,宋轶民,张策.基于现代微分几何的机器人研究现状.中国机械工程.2007,18(2)：238-243页.
[125]苏柏泉.微分几何方法在潜器操纵运动中的研究.哈尔滨工程大学硕士学位论 文.2006：29-50页.
[126]Shukai Li, Jianxiong Zhang, Wansheng Tang.Robust output feedback control for uncertain complex delayed dynamical networks.Computers & Mathematics with Applications, Volume 62, Issue 1, July 2011,497-505P.
[127]Chyun-Chau Fuh, Hsun-Heng Tsai, Wei-Hann Yao. Combining a feedback linearization controller with a disturbance observer to control a chaotic system under external excitation.Communications in Nonlinear Science and Numerical Simulation, Volume 17, Issue 3, March 2012,1423-1429P.]
[128]陈省身,陈维桓.微分几何讲义.北京：北京大学出版社,1983：143-152页.
[129]Isidori A.Nonlinear Control Systems.New York:Springer Press,1989:234-281P.
[130]J.J.E. Slotine, W.Li.Applied Nonlinear Control. Englewood Cliffs, NJ:Prentice-Hall, 1991:23-48P.
[131]Wen Tong, Fang Jiancheng.A feedback linearization control for the nonlinear 5-DOF flywheel suspended by the permanent magnet biased hybrid magnetic bearings.Acta Astronautica, Volume 79, October-November 2012,131-139P.
[132]R.K.Lea, Allen, S.L.Merry.A comparative study of control techniques for an underwater flight vehicle.Int.J.System Science,1990(9):947-964P.
[133]冯俊梅,连琏,葛彤.潜艇操纵控制方法的现状与发展.海洋工程,2005,23(1)：114-122页.
[134]Cristi R, Papoulias F A, Healey A J.Adaptive sliding mode control of autonomous underwater vehicles in the dive plate.IEEE, Oceanic Eng,1990,15(3):245-250P
[135]Yuxin Su, Chunhong Zheng.Global finite-time inverse tracking control of robot manipulators.Robotics and Computer-Integrated Manufacturing, Volume 27, Issue 3, June 2011.550-557P.
[136]Jing Na, Xuemei Ren, Guido Herrmann, Zhi Qiao.Adaptive neural dynamic surface control for servo systems with unknown dead-zone.Control Engineering Practice, Volume 19, Issue 11, November 2011,1328-1343P.
[137]Hanlei Wang, Yongchun Xie.Adaptive inverse dynamics control of robots with uncertain kinematics and dynamics.Automatica, Volume 45, Issue 9, September 2009, 2114-2119P.
[138]华克强,朱齐丹.逆系统理论在水下机器人控制中的应用.哈尔滨船舶工程学院学报,1990,11(1)：50-60页.
[139]Asma Atig, Fabrice Druaux, Dimitri Lefebvre, Kamel Abderrahim, Ridha Ben Abdennour.Adaptive control design using stability analysis and tracking errors dynamics for nonlinear square MIMO systems.Engineering Applications of Artificial Intelligence, In Press, Corrected Proof, Available online 30 August 2011.
[140]吴热冰,李春文.一般非线性系统的构造性逆系统方法.控制理论与应用,2003,20(3)：345-351页.
[141]B.Widrow, E. Walach.刘树堂,韩崇昭译.自适应逆控制.西安交通大学出版社,2000：163-172页.
[142]B.Widrow, E.Walach.Adaptive inverse control.Upper saddle river, NJ:Prentice Hall, 1996:1-158P.
[143]Mou Chen, Shuzhi Sam Ge, Beibei Ren.Adaptive tracking control of uncertain MIMO nonlinear systems with input constraints.Automatica, Volume 47, Issue 3, March 2011, 452-465P.
[144]V. Nekoukar, A. Erfanian.Adaptive fuzzy terminal sliding mode control for a class of MIMO uncertain nonlinear systems.Fuzzy Sets and Systems, Volume 179, Issue 1,16 September 2011,34-49P.
[145]DAI Xian-zhong, HE Dan.ANN generalized inversion for the linearization and decoupling control of nonlinear systems.IEEE Proceedings Control Theory Applications,2003,150(3):267-277P.
[146]戴先中.多变量非线性系统的神经网络逆控制方法.科学出版社,2005：43-52页
[147]戴先中,刘军,冯纯伯.连续非线性系统的神经网络a阶逆系统控制方法.自动化学报,1998,24(4)：463-468页.
[148]李春文,冯元琨.多变量非线性控制的逆系统方法.清华大学出版社,1991：168-175页.
[149]侯忠生,许建新.数据驱动控制理论及方法的回顾和展望.自动化学报.2009,35(6)：650-667页.
[150]Yuanqing Xia, Wen Xie, Bo Liu, Xiaoyun Wang.Data-driven predictive control for networked control systems.Information Sciences, In Press, Corrected Proof, Available online 16 February 2012.
[151]Yiming Wan, Hao Ye.Data-driven diagnosis of sensor precision degradation in the presence of control.Journal of Process Control, Volume 22, Issue 1, January 2012, 26-40P.
[152]K. Yamuna Rani.Sensitivity Compensating Control:Data-driven model based adaptive approachJournal of Process Control, Volume 21, Issue 9, October 2011,1265-1286P.
[153]Chang-Chun Pan, Cheng-I Sun, Shi-Shang Jang, David Shan-Hill Wong, Gen-Ke Yang.A MIMO R2R control using data-driven gain scheduling. Control Engineering Practice, Volume 19, Issue 11, November 2011,1344-1353P.
[154]Andrew Kusiak, Zijun Zhang.Control of wind turbine power and vibration with a data-driven approach.Renewable Energy, Volume 43, July 2012,73-82P.
[155]D. Lauri, J.A. Rossiter, J. Sanchis, M. Martinez.Data-driven latent-variable model-based predictive control for continuous processes Journal of Process Control, Volume 20, Issue 10, December 2010,1207-1219P.
[156]Hou Zhong-Sheng. The Parameter Identification, Adaptive Control and Model Free Learning Adaptive Control for Nonlinear Systems[Ph. D. dissertation], Northeastern University, China,1994.
[157]Hou Zhong-Sheng. Nonparametric Models and Its Adaptive Control Theory. Beijing: Science Press,1999.
[158]Uchiyama M. Formulation of high-speed motion pattern of a mechanical arm by trial. Transactions of the Society for instrumentation and Control Engineering, 1978,14(6):706-712P.
[159]Hou Z S, Xu J X, Yan J W. An iterative learning approach for density control of freeway traffic flow via ramp metering.Transportation Research,Part C:Emerging Technologies,2008,16(1):71-97P.
[160]Hyo-Sung A, Chen YQ, Moore K L. Iterative learning control:brief survey and categorization. IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews,2007,37(6):1099-1121P.
[161]许建新,侯忠生.学习控制的现状与展望.自动化学报.2005,31(6)：943-955页.
[162]Spall J C. Multivariate stochastic approximation using a simultaneous perturbation gradient approximation. IEEE Transactions on Automatic Control.1992,37(3): 332-341P.
[163]Spall J C, Cristion J A. Model-free control of general discrete-time systems. In:Proceedings of the 32nd IEEE Conference on Decision and Control.San Antonio,USA:IEEE,1993.2792-2797P.
[164]Werbos P J. Advanced forecasting methods for global crisis warning and models of intelligence. General Systems Yearbook,1977,22:25-38P.
[165]Lee J M, Lee J H. Approximate dynamic programming based approaches for input-output data-driven control of nonlinear processes. Automatica,2005,41(7): 1281-1288P.
[166]Guardabassi G O, Savaresi S M. Virtual reference directn design method:an off-line approach to data-based control system design. IEEE Transactions on Automatic Control,2000,45(5):954-959P.
[167]Campi M C, Savaresi S M. Direct nonlinear control de sign:the virtual reference feedback tuning (VRFT) approach. IEEE Transactions on Automatic Control, 2006,51(1):15-27P.
[168]Previdi F, Schauer T, Savaresi S M, Hunt K J. Data-driven control design for neuroprotheses:a virtual reference feed back tuning (VRFT) approach. IEEE Transactions on Control Systems Technolog,2004,12(1):176-182P.
[169]Hjalmarsson H, Gunnarsson S,Gevers M. A convergent iterative restricted complexity control design scheme. In:Proceedings of the 33rd IEEE Conference on Decision and Control. Lake Buena Vista, USA:IEEE,1994.1735-1740P.
[170]Graham A E, Young A J, Xie S Q.Rapid tuning of controllers by IFT for profile cutting machines.Mechatronics,2007,17(2-3):121-128P.
[171]Precup R E, Preitl S, Rudas I J, Tomescu M L, Tar J K. Design and experiments for a class of fuzzy controlled servo systems. IEEE/ASME Transactions on Mechatronics, 2008,13(1):22-35P.
[172]Schaal S, Atkeson C G. Robot juggling:implementation of memory-based learning. IEEE Control Systems Magazine,1994,14(1):57-71P.
[173]Pan T H, Li S Y. A hierarchical search and updating database strategy for lazy learning. International Journal of Innovative Computing, Information and Control,2008,4(6): 1383-1392P.
[174]王成红,宋苏,孙长银.关于“基于数据的控制”的几点思考,技术报告,国家自然科学基金委员会第33期双清论坛“基于数据驭动的控制决策调度与故障诊断”学术研讨会,北京,2008.
[175]侯忠生,许建新.数据驱动控制理论及方法的现状和展望,技术报告,国家自然科学基金委员会第33期双清论坛“基于数据驱动的控制、决策、调度与故障诊断”学术研讨会北京.2008.
[176]Karimi A, Miskovic L, Bonvin D. Convergence analysis of an iterative correlation-based controller tuning method. In Proceedings of the 15th IF AC World Congress.Barcelona,Spain:IFAC,2002.1546-1551 P.
[177]Miskovic L, Karixni A, Bonvin D, Levers M. Correlation based tuning of decoupling multivariable controllers. Automatica,2007,43(9):1481-1494P.
[178]Safonov M G, Tsao T C. The unfalsified control concept:a direct path from experiment to controller. Feedback Control, Nonlinear Systems, and Complexity. Berlin: SpringerVerlag,1995.196-214P.
[179]van Helvoort J, de Jager B, Steinbuch M. Direct data-driven recursive controller unfalsification with analytic update. Automatica,2007,43(12):2034-2046P.
[180]van Helvoort J, de Jager B, Steinbuch M. Data-driven multivariable controller design using ellipsoidal unfalsified control. Systems and Control Letters,2008,57(9): 759-762P.
[181]Der-Chiang Li, Chiao-Wen Liu.A class possibility based kernel to increase classification accuracy for small data sets using support vector machines.Expert Systems with Applications, Volume 37, Issue 4, April 2010,3104-3110P.
[182]戴先中,孟正大等.神经网络α阶逆系统控制方法在机器人解耦控制中的应用[J].机器人,2001,23(4)：363-367页.
[183]陈小红,侯春海等.逆系统方法的径向基函数网络实现.控制与决策,1998,13(2)：146-150页.
[184]Zeng-Zhou Jia, Yu Huang etc. Robotic Manipul-ators Decoupling Control Based on ANN a th-order Inverse System Method. Proceedings of the Fourth International Conference on Machine Learning and Cybernetics. Guangzhou,2005.
[185]Mohsen Behzad, Keyvan Asghari, Morteza Eazi, Maziar Palhang.Generalization performance of support vector machines and neural networks in runoff modeling.Expert Systems with Applications, Volume 36, Issue 4, May 2009,7624-7629P
[186]李春文,冯元琨.多变量非线性控制的逆系统方法.北京：清华大学出版社,1991.
[187]Isidori A. Nonlinear Control Systems. New York:Springer Press,1989:234-281P.
[188]Suykens J.A.K., Vandewalle J., Chaos control using least squares support vector machines, International Journal of Circuit Theory and Applications, Special Issue on Communications, Information Processing and Control using Chaos, vol.27, no.6, Nov. 1999:605-615P.
[189]Suykens J.A.K., Vandewalle J., Recurrent least squares support vector machines, IEEE Transactions on Circuits and Systems-I, vol.47, no.7, Jul.2000:1109-1114P.
[190]宋夫华,李平.基于支持向量机α阶逆系统方法的非线性内模控制.自动化学报,2007,33(7)：778-781页.
[191]张浩然,韩正之等.基于支持向量机的未知非线性系统辨识与控制.上海交通大学学报.2003,37(6)：927-930页.
[192]刘陆洲,肖建,刘杰.一种新型神经网络广义逆系统.控制与决策.2009,24(9)：1390-1393页.