基于模糊神经网络的海底采矿车路径跟踪行走控制研究
|
摘要
富钴结壳是一种赋存于800-2500m海山侧表面上的海底矿产资源。钴结壳海底采矿车采用具有良好越障性能和爬坡能力及机动性能的铰接式履带车作为其行走机构。海底采矿车按预定路径行走控制为采矿作业关键技术之一。
本文以海底采矿车多刚体动力学模型为基础,提出了一种基于ANFIS的模糊神经网络行走控制方法,并建立了基于Simulink、ADAMS和LabVIEW的海底采矿车协同仿真模型,从而为海底采矿车自动行走控制研究提供了新的方法和思路。首先,设计了以Compact RIO控制器为核心的海底采矿车控制系统方案,提出了在LabVIEW测控平台上采用内环速度控制和外环路径控制的智能自动行走控制方案。在此基础上,开展了海底采矿车运动学分析和建模,构建了基于ANFIS的模糊神经网络外环路径控制和PID内环速度控制的按预定路径行走控制模型；同时,基于ANFIS神经模糊推理系统,根据训练数据,完成了模糊神经网络路径控制器设计；设计了PID控制器,并对参数进行了整定；建立了速度分配模块、滑转率控制模块、滑转率实时计算模块和延时模块等模型。
其次,建立了海底采矿车动力学机械模型与按预定路径行走控制模型的协同仿真模型,开展了海底采矿车越单边障碍、偏离路径跟踪、爬坡滑转率控制的直线路径跟踪控制的仿真研究,仿真结果表明,海底采矿车行走路径跟踪控制和滑转率控制效果良好,表明所设计的基于ANFIS的模糊神经网络的行走控制算法是有效的。
然后,利用SIT Sever,建立了基于Simulink、ADAMS和LabVIEW的海底采矿车协同仿真模型,实现了Simulink、ADAMS和LabVIEW三个软件的协同仿真,为海底采矿车自动行走控制提供了技术支持。
最后,开展了海底采矿车模型机行走实验,实现了海底采矿车行走控制算法与LabVIEW测控系统的联接,验证了所设计的基于ANFIS的模糊神经网络外环控制和PID内环速度控制的算法是有效的。
Cobalt-rich crust is the seabed mineral resource which exists on the surface of the marine hills.Beacause articulated tracked vehicle is of good obstacle performance,climbing ability and advanced mobility, articulated tracked vehicle is selected as the running machine for cobalt crust mining.It is a key technology that cobalt crust mining walks on the Scheduled path.
On the foundation of multi-body dynamic model of seabed mining vehicle,a fuzzy neural network running control method is presented based on ANFIS,and a co-simulation model is established which is based on Simulink, ADAMS and Lab VIEW. So new methods and ideas are provided for walking control research of seabed mining vehicle.
First of all,the control scheme of seabed mining vehicle is designed which takes Compact RIO controller as a core.And the intelligent automatic running control program is proposed which is of inner loop using speed control and outer loop using path control with Lab VIEW. On this basis,the kinematic analysis and modeling of seabed mining vehicle is carried out. And the walking control model of outer loop using path control and inner loop using PID speed control is established based on ANFIS. According to the training data, the path controller of fuzzy neural network is designed based on ANFIS.Then, the PID controller is designed and parameters is tuned.At the same time, the model of speed distribution module,slip rate control module,slip rate calculation module and real-time delay module is established.
Secondly,the co-simulation model of a dynamic mechanical model and a scheduled path walking control model is established.And the simulation study of straight path tracking control about steping over unilateral barriers,deviating from the path and slip rate control when the seabed mining vehicle climbing is carried out. A set of simulation results is presented,showing the validity of the proposed control method based on ANFIS.
Afterwards, a co-simulation model is established which is based on Simulink,ADAMS and Lab VIEW by SIT Sever,, achieving the purpose of three softwares co-simulation, so the technical support is provided for the automatic control of.
Finally,the model experiments about seabed mining vehicle are carried out, which achieves the connection of the control algorithm and LabVIEW.So it is verified that the validity of the proposed control method of seabed mining vehicle.
本文以海底采矿车多刚体动力学模型为基础,提出了一种基于ANFIS的模糊神经网络行走控制方法,并建立了基于Simulink、ADAMS和LabVIEW的海底采矿车协同仿真模型,从而为海底采矿车自动行走控制研究提供了新的方法和思路。首先,设计了以Compact RIO控制器为核心的海底采矿车控制系统方案,提出了在LabVIEW测控平台上采用内环速度控制和外环路径控制的智能自动行走控制方案。在此基础上,开展了海底采矿车运动学分析和建模,构建了基于ANFIS的模糊神经网络外环路径控制和PID内环速度控制的按预定路径行走控制模型；同时,基于ANFIS神经模糊推理系统,根据训练数据,完成了模糊神经网络路径控制器设计；设计了PID控制器,并对参数进行了整定；建立了速度分配模块、滑转率控制模块、滑转率实时计算模块和延时模块等模型。
其次,建立了海底采矿车动力学机械模型与按预定路径行走控制模型的协同仿真模型,开展了海底采矿车越单边障碍、偏离路径跟踪、爬坡滑转率控制的直线路径跟踪控制的仿真研究,仿真结果表明,海底采矿车行走路径跟踪控制和滑转率控制效果良好,表明所设计的基于ANFIS的模糊神经网络的行走控制算法是有效的。
然后,利用SIT Sever,建立了基于Simulink、ADAMS和LabVIEW的海底采矿车协同仿真模型,实现了Simulink、ADAMS和LabVIEW三个软件的协同仿真,为海底采矿车自动行走控制提供了技术支持。
最后,开展了海底采矿车模型机行走实验,实现了海底采矿车行走控制算法与LabVIEW测控系统的联接,验证了所设计的基于ANFIS的模糊神经网络外环控制和PID内环速度控制的算法是有效的。
Cobalt-rich crust is the seabed mineral resource which exists on the surface of the marine hills.Beacause articulated tracked vehicle is of good obstacle performance,climbing ability and advanced mobility, articulated tracked vehicle is selected as the running machine for cobalt crust mining.It is a key technology that cobalt crust mining walks on the Scheduled path.
On the foundation of multi-body dynamic model of seabed mining vehicle,a fuzzy neural network running control method is presented based on ANFIS,and a co-simulation model is established which is based on Simulink, ADAMS and Lab VIEW. So new methods and ideas are provided for walking control research of seabed mining vehicle.
First of all,the control scheme of seabed mining vehicle is designed which takes Compact RIO controller as a core.And the intelligent automatic running control program is proposed which is of inner loop using speed control and outer loop using path control with Lab VIEW. On this basis,the kinematic analysis and modeling of seabed mining vehicle is carried out. And the walking control model of outer loop using path control and inner loop using PID speed control is established based on ANFIS. According to the training data, the path controller of fuzzy neural network is designed based on ANFIS.Then, the PID controller is designed and parameters is tuned.At the same time, the model of speed distribution module,slip rate control module,slip rate calculation module and real-time delay module is established.
Secondly,the co-simulation model of a dynamic mechanical model and a scheduled path walking control model is established.And the simulation study of straight path tracking control about steping over unilateral barriers,deviating from the path and slip rate control when the seabed mining vehicle climbing is carried out. A set of simulation results is presented,showing the validity of the proposed control method based on ANFIS.
Afterwards, a co-simulation model is established which is based on Simulink,ADAMS and Lab VIEW by SIT Sever,, achieving the purpose of three softwares co-simulation, so the technical support is provided for the automatic control of.
Finally,the model experiments about seabed mining vehicle are carried out, which achieves the connection of the control algorithm and LabVIEW.So it is verified that the validity of the proposed control method of seabed mining vehicle.
引文
[1]菲尔莫尔CF埃尔尼著,翟国谦等译.海洋矿产资源[M].北京：海洋出版社,1991
[2]简曲.21世纪的大洋采矿[J].矿山机械,2000,4：8-11
[3]GP.Glasby. Lessons Learned from Deep-Sea Mining[J]. Science,2000,289(5479): 551～553
[4]沈裕军,钟祥,贺泽全.大洋钻结壳资源钻究开发现状[J].矿冶工程,1999,19(2)：11-13
[5]Yamazaki,T.Sharma,T. Distribution characteristics of co-rich manganese deposits on a sea-mount in the central Pacific Ocean[J].Marine Georesources&Geotechnology,1998,16 (4):283～305
[6]F.T.Manheim. Marine Cobalt Resources[J].Science,1986,232(4750):600～603
[7]James Hein. Cobalt-rich ferromanganese crusts:global distribution, composition, origin and research activities.Polymetallic massive sulphides and cobalt-rich ferromanganese crusts:status and prospects[R].ISA Technical study,2000, (2):43～ 49
[8]刘淮.国外深海技术发展研究(二)[J].船舶工业,2006,260：18-23
[9]阳宁,夏建新.国际海底资源开发技术及其发展趋势[J].矿业工程,2000,20(1)：1-4
[10]戴瑜,刘少军,李流军.Nautilus矿业公司SMS勘探技术中采用的取样技术与装被[J].海洋技术,2008,06：12-16
[11]石海林.我国富钴结壳矿床开采技术研究分析[J].矿业快报,2008,08(16)：1-3
[12]Yamazaki T,etal. Microtopographic Analysis of the Cobalt-Rich Manganese Deposits on a Mid-Pacific Seamount [J].Marine georesources and geotechnology, 1994, (12):33～52
[13]邱长军.钴结壳和基岩的特性与模拟研究[博士学位论文].长沙：中南大学,2002
[14]邬长斌,刘少军,戴瑜.海底多金属硫化物开发动态与前景分析[J].海洋通报,2008,27(6)：101-108
[15]潘艳.我国自然资源的基本状况及面临的严峻问题[J].社会发展,2009,4： 61-62
[16]王明和,简曲,陈新民.海底作业车的研究[J].海洋技术,1997,16(4)：44-49
[17]简曲.大洋采矿集矿机的研究.中国有色金属学报[J].1998,8(2)：783-786
[18]陈峰,桂卫华,王随平等.深海底采矿机器车的研究现状[J].2005,33(9)：6-9
[19]陈新明,吴鸿云,丁六怀等.富钻结壳开采技术研究现状[J].矿业研究与开发,2008(6)：1-3
[20]梁平,石海林,崔波等.洋底富钴结壳的开采方法[J].金属矿山,2002,11：20-22
[21]赵辉.铰接履带式海底作业车行走与控制仿真研究[硕士学位论文].长沙：中南大学,2008
[22]国际海底管理局秘书长根据《联合国海洋法公约》第一六六条第4款提出的报告[D].国际海底管理局第十四届会议,牙买加,金斯敦,2008,5
[23]陈新明,高宇清,吴鸿云等.海底热液硫化物的开发现状[J].矿业研究与开发,2008,28(5)：1-5
[24]WANG Zhen-yu,LIU Shao-jun,LI Li.Craw Ling Feasibility Simulational Study on Tracked vehicle for Deep Ocean Mining[J].系统仿真学报,2004(4)
[25]简曲.中国大洋采矿技术发展述评[J].采矿技术,2001,1(2)：9-11
[26]简曲,王明和,高宇清,李力.大洋采矿集矿技术和集矿模型机研究[J].有色金属,1997(3)
[27]周良.铰接式履带车动力学仿真与有限元分析[硕士学位论文].长沙：中南大学,2009
[28]王俊杰.钴结壳铰接履带式行走机构仿真研究[硕士学位论文].长沙：中南大学,2007
[29]李炳华.海底车体转向式履带车行走性能的仿真研究[硕士学位论文].长沙：中南大学,2008
[30]陈金涛.钴结壳采矿铰接式履带作业车仿真研究[硕士学位论文].长沙：中南大学,2007
[31]李小飞,李力,周良等.机电液协同仿真技术的钴结壳采矿车行走控制研究[J].北京：现代制造工程,2009(10)：92-96
[32]许宏南.橡胶履带全地形车的研制及市场前景分析[J].专用汽车,1996,(3)：26-28
[33]A.Falk.Advanced mobility in difficult terrain[J]. Journal of Terramechanics, 2004, (41):101～111
[34]周丽萍.瑞典改进型BV206s全地形装甲车[J].国外坦克,2004,(12)：29-30
[35]杨书林.深海集矿机轨迹跟踪算法研究[硕士学位论文].长沙：中南大学,2008
[36]Zhejun, Fan, Y.Koren, D.Wehe. Tracked mobile robot control:hybrid approach[J].Control Eng. Pratice,1995,3(3):329～339
[37]Zhejun Fan, Yoram Koren, David Wehe. A simple trakction control for tracked vehicles[J].Proceeding of the American control conference,1995, (7):1176～1177
[38]k.Rintanen, H.Makela, etc. Development of an autonomous navigation system for an outdo-or vehicle[J].Control Eng.Practice,1996,4(4):499～505
[39]ZviShiller, William Serate, Minh Hua. Trajectory Planning of Tracked Vehicles[J].1993 IEEE International Conference On Robotics and Automation,1993, (5):796～801
[40]M.Ahmadi, V.Polotski, R.Hurteau. Path Tracking Control of Tracked Vehickes [C].Proceed-ing of the 2000 IEEE International Conference on Robotics&Automation,2000, (4):2938～2943
[41]赵登峰,王国强,许纯新,陈向东.基于模糊神经网络的智能履带车路径跟踪系统[J].农业工程学报,2003,19(2)：149-152
[42]黄泰松,桂卫华,蔡自兴.模糊控制在深海集矿机行走控制中的应用[J].中国有色金属学报,1998,8(3)：113-116
[43]邹兴龙.海底作业车行走液压系统与路径控制研究[硕士学位论文].长沙：中南大学,2006
[44]王随平.深海集矿机自行走预测控制[J].系统计算机测量与控制,2007,15(11)：1593-1596
[45]朱洪前,桂卫华.大洋集矿轨迹跟踪自适应PID控制[J].机床与液压,2007,35(12)：87-89
[46]贺建飚,唐修俊,张彭,赵经纶.越野移动机器人自动驾驶专家系统的研究[J].机器人,1994,9(16)264-268
[47]王和平,王爱武.自行式海底作业车的智能控制系统[J].矿业研究与开发,2002,22(2)：30-32
[48]李瑞涛,方湄,张文明.虚拟样机技术的概念及应用[J].机电一体化,2000,(5)：17-19
[49]吕东,何将三,刘少军.深海资源开发装备虚拟样机技术应用研究[J].机械工程师,2003,(10)：16-18
[50]于海生.计算机控制技术[M].北京：机械工业出版社,2007.6
[51]李力,邹兴龙.海底机器人自动跟踪预定开采路径控制[J].机械工程学报,2007,43(1)：152-157
[52]Msc software. ADAMS Tracked Vehicle Toolkit version 2005[M]. Sweden:MDI, 2004
[53]陈新明.中国深海采矿技术的发展[J].长沙矿山研究院建院50周年院庆论文集,2006,(10)：40-45
[54]王随平.COMPACT-PCI IPC用于深海集矿作业车两级控制系统[J].计算技术与自动化,2002,21(2)：7-10
[55]Zhiming Gong, Javier Ibanez Guunan, Steven J. Scheding, David C. Rye, Gamini Dissanayake, Hugh Durrant-Whyte. A Heuristic rule-based switching and adaptive PID controller for a large autonomous tracked vehicle:From development to implementation [C].In:Proceedings of the 2004 IEEE International Conference on Control Applications. September 2-4,2004, Taipei, Taiwan.IEEE,2004:1272-1277
[56]ZhejunFan, Y.Koren, D.Wehe. Tracked mobile robot control:Hybrid approach[C]. Control Engineering Practice,1995,3(3):329-336
[57]陈峰,桂卫华,王随平,韩晓英.一种新的履带机器车轨迹跟踪控制[J].计算机工程与应用,2005(29)：187-189
[58]Mitsuji Sampei, Takeshi Tamura, Tadaharu Kobayashi, and Nobuhiro Shibui. Arbitrary Path Tracking Control of Articulated Vehicles Using Nonlinear Control Theory [J]. Transactions On Control Systems Technology,1995,3 (1):125～131
[59]Ahmadi M, Polotski V, Hurteau R. Path tracking control of tracked vehicles[J]. Proc IEEE Int Conf Rob Autom,2000,3:2938-2943
[60]K. Herzog, E. Schulte, M. A. Atmanand, and W. Schwarz. Slip Control System for a Deep-Sea Mining Machine[J]. Transactions On Automation Science And Engineering,2007,4 (2):282～286
[61]Yugang Liu, Guangjun Liu. Modeling of tracked mobile manipulators with consideration of track-terrain and vehicle-manipulator interactions[J]. Robotics and Autonomous Systems,2009 (57):1065～1074
[62]石辛民,郝整清.模糊控制及其MATLAB仿真[M].北京：清华大学出版社,北京交通大学出版社,2008
[63]刘怀国,孙建华,张冰,张尤赛.ANFIS及其在控制系统中的应用[J].华东船舶工业学院学报(自然科学版),2001,15(5)：27-31
[64]Zhi Q. Gu, S. Olutunde Oyadiji. Application of MR damper in structural control using ANFIS method[J]. Computers and Structures,2008, (86):427-436
[65]Chaio-Shiung Chen. Dynamic structure adaptive neural fuzzy control for MIMO uncertain nonlinear systems [J]. Information Sciences,179(2009):2676-2688
[66]Lon-Chen Hung, Hung-Yuan Chung. Decoupled sliding-mode with fuzzy-neural network controller for nonlinear systems[J].Science Direct,2007 (46):74～97
[67]Tomchiro Takagi and Michio Sugeno.Fuzzy identification of systems and its applications to modeling and control[J].IEEE Translations on Systems Man and Cybernetics,1985:116-132
[68]孙增圻,徐红兵.基于T-S模型的模糊神经网络[J].清华大学学报(自然科学版),1997,37(3)：76-80
[69]孙增圻.模糊神经网络及其在系统建模与控制中的应用[J].南京化工大学学报,2000,22(4)：1-6
[70]陈新兵.ANFIS的MATLAB实现与液压成型机模糊温控系统的研究[硕士论文].长沙：湖南大学,2005.4
[71]岳玉芳,毛剑琴.一种基于T-S模型的快速自适应建模方法[J].控制与决策,2002,17(2)：155-158
[72]童树鸿,沈毅,刘志言.基于聚类分析的模糊分类系统构造方法[J].控制与决策,2001,16(11)：737-744
[73]李少远,王群仙,陈增强等.Sugeno模糊模型的辨识[J].南开大学学报(自然科学版),1999,32(1)：58-63
[74]张平安,李人厚.基于模糊聚类和卡尔曼滤波方法的模糊辨识[J].控制理论与应用,1996,13(5)：639-643
[75]Azeem.M.F,Hanmandlu.M,Ahmad.N.Generalization of adaptive neuro-fuzzy inference systems.IEEE Transactions on Neural Network,2000,11(6):1332-1346
[76]邓志东,孙增圻,张再兴.一种模糊CMAC神经网络[J].自动化学报,1995,21(3)：289-293
[77]郑建荣.ADAMS虚拟样机技术入门与提高[M].机械工业出版社,2002
[2]简曲.21世纪的大洋采矿[J].矿山机械,2000,4：8-11
[3]GP.Glasby. Lessons Learned from Deep-Sea Mining[J]. Science,2000,289(5479): 551～553
[4]沈裕军,钟祥,贺泽全.大洋钻结壳资源钻究开发现状[J].矿冶工程,1999,19(2)：11-13
[5]Yamazaki,T.Sharma,T. Distribution characteristics of co-rich manganese deposits on a sea-mount in the central Pacific Ocean[J].Marine Georesources&Geotechnology,1998,16 (4):283～305
[6]F.T.Manheim. Marine Cobalt Resources[J].Science,1986,232(4750):600～603
[7]James Hein. Cobalt-rich ferromanganese crusts:global distribution, composition, origin and research activities.Polymetallic massive sulphides and cobalt-rich ferromanganese crusts:status and prospects[R].ISA Technical study,2000, (2):43～ 49
[8]刘淮.国外深海技术发展研究(二)[J].船舶工业,2006,260：18-23
[9]阳宁,夏建新.国际海底资源开发技术及其发展趋势[J].矿业工程,2000,20(1)：1-4
[10]戴瑜,刘少军,李流军.Nautilus矿业公司SMS勘探技术中采用的取样技术与装被[J].海洋技术,2008,06：12-16
[11]石海林.我国富钴结壳矿床开采技术研究分析[J].矿业快报,2008,08(16)：1-3
[12]Yamazaki T,etal. Microtopographic Analysis of the Cobalt-Rich Manganese Deposits on a Mid-Pacific Seamount [J].Marine georesources and geotechnology, 1994, (12):33～52
[13]邱长军.钴结壳和基岩的特性与模拟研究[博士学位论文].长沙：中南大学,2002
[14]邬长斌,刘少军,戴瑜.海底多金属硫化物开发动态与前景分析[J].海洋通报,2008,27(6)：101-108
[15]潘艳.我国自然资源的基本状况及面临的严峻问题[J].社会发展,2009,4： 61-62
[16]王明和,简曲,陈新民.海底作业车的研究[J].海洋技术,1997,16(4)：44-49
[17]简曲.大洋采矿集矿机的研究.中国有色金属学报[J].1998,8(2)：783-786
[18]陈峰,桂卫华,王随平等.深海底采矿机器车的研究现状[J].2005,33(9)：6-9
[19]陈新明,吴鸿云,丁六怀等.富钻结壳开采技术研究现状[J].矿业研究与开发,2008(6)：1-3
[20]梁平,石海林,崔波等.洋底富钴结壳的开采方法[J].金属矿山,2002,11：20-22
[21]赵辉.铰接履带式海底作业车行走与控制仿真研究[硕士学位论文].长沙：中南大学,2008
[22]国际海底管理局秘书长根据《联合国海洋法公约》第一六六条第4款提出的报告[D].国际海底管理局第十四届会议,牙买加,金斯敦,2008,5
[23]陈新明,高宇清,吴鸿云等.海底热液硫化物的开发现状[J].矿业研究与开发,2008,28(5)：1-5
[24]WANG Zhen-yu,LIU Shao-jun,LI Li.Craw Ling Feasibility Simulational Study on Tracked vehicle for Deep Ocean Mining[J].系统仿真学报,2004(4)
[25]简曲.中国大洋采矿技术发展述评[J].采矿技术,2001,1(2)：9-11
[26]简曲,王明和,高宇清,李力.大洋采矿集矿技术和集矿模型机研究[J].有色金属,1997(3)
[27]周良.铰接式履带车动力学仿真与有限元分析[硕士学位论文].长沙：中南大学,2009
[28]王俊杰.钴结壳铰接履带式行走机构仿真研究[硕士学位论文].长沙：中南大学,2007
[29]李炳华.海底车体转向式履带车行走性能的仿真研究[硕士学位论文].长沙：中南大学,2008
[30]陈金涛.钴结壳采矿铰接式履带作业车仿真研究[硕士学位论文].长沙：中南大学,2007
[31]李小飞,李力,周良等.机电液协同仿真技术的钴结壳采矿车行走控制研究[J].北京：现代制造工程,2009(10)：92-96
[32]许宏南.橡胶履带全地形车的研制及市场前景分析[J].专用汽车,1996,(3)：26-28
[33]A.Falk.Advanced mobility in difficult terrain[J]. Journal of Terramechanics, 2004, (41):101～111
[34]周丽萍.瑞典改进型BV206s全地形装甲车[J].国外坦克,2004,(12)：29-30
[35]杨书林.深海集矿机轨迹跟踪算法研究[硕士学位论文].长沙：中南大学,2008
[36]Zhejun, Fan, Y.Koren, D.Wehe. Tracked mobile robot control:hybrid approach[J].Control Eng. Pratice,1995,3(3):329～339
[37]Zhejun Fan, Yoram Koren, David Wehe. A simple trakction control for tracked vehicles[J].Proceeding of the American control conference,1995, (7):1176～1177
[38]k.Rintanen, H.Makela, etc. Development of an autonomous navigation system for an outdo-or vehicle[J].Control Eng.Practice,1996,4(4):499～505
[39]ZviShiller, William Serate, Minh Hua. Trajectory Planning of Tracked Vehicles[J].1993 IEEE International Conference On Robotics and Automation,1993, (5):796～801
[40]M.Ahmadi, V.Polotski, R.Hurteau. Path Tracking Control of Tracked Vehickes [C].Proceed-ing of the 2000 IEEE International Conference on Robotics&Automation,2000, (4):2938～2943
[41]赵登峰,王国强,许纯新,陈向东.基于模糊神经网络的智能履带车路径跟踪系统[J].农业工程学报,2003,19(2)：149-152
[42]黄泰松,桂卫华,蔡自兴.模糊控制在深海集矿机行走控制中的应用[J].中国有色金属学报,1998,8(3)：113-116
[43]邹兴龙.海底作业车行走液压系统与路径控制研究[硕士学位论文].长沙：中南大学,2006
[44]王随平.深海集矿机自行走预测控制[J].系统计算机测量与控制,2007,15(11)：1593-1596
[45]朱洪前,桂卫华.大洋集矿轨迹跟踪自适应PID控制[J].机床与液压,2007,35(12)：87-89
[46]贺建飚,唐修俊,张彭,赵经纶.越野移动机器人自动驾驶专家系统的研究[J].机器人,1994,9(16)264-268
[47]王和平,王爱武.自行式海底作业车的智能控制系统[J].矿业研究与开发,2002,22(2)：30-32
[48]李瑞涛,方湄,张文明.虚拟样机技术的概念及应用[J].机电一体化,2000,(5)：17-19
[49]吕东,何将三,刘少军.深海资源开发装备虚拟样机技术应用研究[J].机械工程师,2003,(10)：16-18
[50]于海生.计算机控制技术[M].北京：机械工业出版社,2007.6
[51]李力,邹兴龙.海底机器人自动跟踪预定开采路径控制[J].机械工程学报,2007,43(1)：152-157
[52]Msc software. ADAMS Tracked Vehicle Toolkit version 2005[M]. Sweden:MDI, 2004
[53]陈新明.中国深海采矿技术的发展[J].长沙矿山研究院建院50周年院庆论文集,2006,(10)：40-45
[54]王随平.COMPACT-PCI IPC用于深海集矿作业车两级控制系统[J].计算技术与自动化,2002,21(2)：7-10
[55]Zhiming Gong, Javier Ibanez Guunan, Steven J. Scheding, David C. Rye, Gamini Dissanayake, Hugh Durrant-Whyte. A Heuristic rule-based switching and adaptive PID controller for a large autonomous tracked vehicle:From development to implementation [C].In:Proceedings of the 2004 IEEE International Conference on Control Applications. September 2-4,2004, Taipei, Taiwan.IEEE,2004:1272-1277
[56]ZhejunFan, Y.Koren, D.Wehe. Tracked mobile robot control:Hybrid approach[C]. Control Engineering Practice,1995,3(3):329-336
[57]陈峰,桂卫华,王随平,韩晓英.一种新的履带机器车轨迹跟踪控制[J].计算机工程与应用,2005(29)：187-189
[58]Mitsuji Sampei, Takeshi Tamura, Tadaharu Kobayashi, and Nobuhiro Shibui. Arbitrary Path Tracking Control of Articulated Vehicles Using Nonlinear Control Theory [J]. Transactions On Control Systems Technology,1995,3 (1):125～131
[59]Ahmadi M, Polotski V, Hurteau R. Path tracking control of tracked vehicles[J]. Proc IEEE Int Conf Rob Autom,2000,3:2938-2943
[60]K. Herzog, E. Schulte, M. A. Atmanand, and W. Schwarz. Slip Control System for a Deep-Sea Mining Machine[J]. Transactions On Automation Science And Engineering,2007,4 (2):282～286
[61]Yugang Liu, Guangjun Liu. Modeling of tracked mobile manipulators with consideration of track-terrain and vehicle-manipulator interactions[J]. Robotics and Autonomous Systems,2009 (57):1065～1074
[62]石辛民,郝整清.模糊控制及其MATLAB仿真[M].北京：清华大学出版社,北京交通大学出版社,2008
[63]刘怀国,孙建华,张冰,张尤赛.ANFIS及其在控制系统中的应用[J].华东船舶工业学院学报(自然科学版),2001,15(5)：27-31
[64]Zhi Q. Gu, S. Olutunde Oyadiji. Application of MR damper in structural control using ANFIS method[J]. Computers and Structures,2008, (86):427-436
[65]Chaio-Shiung Chen. Dynamic structure adaptive neural fuzzy control for MIMO uncertain nonlinear systems [J]. Information Sciences,179(2009):2676-2688
[66]Lon-Chen Hung, Hung-Yuan Chung. Decoupled sliding-mode with fuzzy-neural network controller for nonlinear systems[J].Science Direct,2007 (46):74～97
[67]Tomchiro Takagi and Michio Sugeno.Fuzzy identification of systems and its applications to modeling and control[J].IEEE Translations on Systems Man and Cybernetics,1985:116-132
[68]孙增圻,徐红兵.基于T-S模型的模糊神经网络[J].清华大学学报(自然科学版),1997,37(3)：76-80
[69]孙增圻.模糊神经网络及其在系统建模与控制中的应用[J].南京化工大学学报,2000,22(4)：1-6
[70]陈新兵.ANFIS的MATLAB实现与液压成型机模糊温控系统的研究[硕士论文].长沙：湖南大学,2005.4
[71]岳玉芳,毛剑琴.一种基于T-S模型的快速自适应建模方法[J].控制与决策,2002,17(2)：155-158
[72]童树鸿,沈毅,刘志言.基于聚类分析的模糊分类系统构造方法[J].控制与决策,2001,16(11)：737-744
[73]李少远,王群仙,陈增强等.Sugeno模糊模型的辨识[J].南开大学学报(自然科学版),1999,32(1)：58-63
[74]张平安,李人厚.基于模糊聚类和卡尔曼滤波方法的模糊辨识[J].控制理论与应用,1996,13(5)：639-643
[75]Azeem.M.F,Hanmandlu.M,Ahmad.N.Generalization of adaptive neuro-fuzzy inference systems.IEEE Transactions on Neural Network,2000,11(6):1332-1346
[76]邓志东,孙增圻,张再兴.一种模糊CMAC神经网络[J].自动化学报,1995,21(3)：289-293
[77]郑建荣.ADAMS虚拟样机技术入门与提高[M].机械工业出版社,2002