履带采矿车海底斜坡地形转向控制算法研究
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摘要
深海底采矿车工作于6000米深的海底环境中,海底极稀软底质和各种扰动的存在对采矿车的行走控制起着很大的影响。设计合理的控制算法对于提高采矿车的行走性能起着关键作用,特别是当采矿车行驶于海底坡度地形时,对采矿车转向策略、转向行走控制参数的优化则更为重要。因此,针对采矿车转向控制技术的研究对于提高海底采矿车的控制精度、采矿效率以及安全作业有着重要意义。
采矿车在海底斜坡上行走作业时的转向控制受诸多参数制约,我国矿区的海底海泥力学性质、采矿车海底斜坡坡度、采矿车转向方式与坡度相对关系、转向速度和角度、斜坡走向、采矿车打滑率、采矿车电液驱动装置、海底沉积物特性以及未知扰动等因素对采矿车转向过程和转向驱动方式均产生多参数耦合的作用。通过分析转向过程中采矿车与海底底质的作用力关系,建立了采矿车在海底斜坡转向的运动学模型,设计了以最优控制器为核心的转向控制系统。转向控制系统考虑了在采矿车斜坡上转向行走的打滑和扰动等因素,提高了转向过程中对轨迹跟踪的控制精度,保证了采矿车的安全行走作业。
运用MATLAB/Simulink平台,给定不同转向方式的预定轨迹和斜坡坡度,对转向控制器进行了仿真研究。考虑到海底强烈的扰动和履带打滑因素,在仿真中加入了随机干扰,仿真结果验证了所设计的转向控制算法的有效性。
The deep-ocean mining vehicles work in 6000m's deep-seabed. The control precision of the vehicles have been influenced detrimentally by the proliferation of soft seabed sediments and various disturbances in the deep-sea environment. Consequently, a suitable control algorithm plays a pivotal role in improving the vehicles'performance. Especially when the vehicle mines around the deep-sea slope, the optimization of the steering strategies and parameters is dominant. Overall, it is imperative that the research on mining vehicle's steering control technology is conducted for the sake of the control precision and mining efficiency.
The mining vehicle's turning control process is restricted by many factors while working on the deep-sea slope. For instance, the mechanical properties of deep-sea mud, grade of the slope, the relativity between turning direction and gradient, turning speed and angle, the slip rate, the electro-hydraulic drive system and other unknown disturbances all have a definite link with the mining vehicle's parameters coupling effect during the steering course. The force relationship between the tracked vehicle and the seabed is first analyzed in this thesis. Secondly, the mining vehicle's kinematic model is deduced as driving on the slope. Finally, the optimal steering controller is designed as a key determinant of the turning control system. Since the turning control system takes the skidding and disturbances into account, the mining vehicle's tracking accuracy is enhanced and the driving safety on the slope is also ensured.
Through the predicted trajectories and gradient under the different turning way, a simulating research on the turning controller is carried out in the MATLAB/Simulink platform. The random interference is added into the simulation on the consideration of strong disturbance in the deep sea and slip between the tracks and sediment. And the results show the validity of the algorithm.
采矿车在海底斜坡上行走作业时的转向控制受诸多参数制约,我国矿区的海底海泥力学性质、采矿车海底斜坡坡度、采矿车转向方式与坡度相对关系、转向速度和角度、斜坡走向、采矿车打滑率、采矿车电液驱动装置、海底沉积物特性以及未知扰动等因素对采矿车转向过程和转向驱动方式均产生多参数耦合的作用。通过分析转向过程中采矿车与海底底质的作用力关系,建立了采矿车在海底斜坡转向的运动学模型,设计了以最优控制器为核心的转向控制系统。转向控制系统考虑了在采矿车斜坡上转向行走的打滑和扰动等因素,提高了转向过程中对轨迹跟踪的控制精度,保证了采矿车的安全行走作业。
运用MATLAB/Simulink平台,给定不同转向方式的预定轨迹和斜坡坡度,对转向控制器进行了仿真研究。考虑到海底强烈的扰动和履带打滑因素,在仿真中加入了随机干扰,仿真结果验证了所设计的转向控制算法的有效性。
The deep-ocean mining vehicles work in 6000m's deep-seabed. The control precision of the vehicles have been influenced detrimentally by the proliferation of soft seabed sediments and various disturbances in the deep-sea environment. Consequently, a suitable control algorithm plays a pivotal role in improving the vehicles'performance. Especially when the vehicle mines around the deep-sea slope, the optimization of the steering strategies and parameters is dominant. Overall, it is imperative that the research on mining vehicle's steering control technology is conducted for the sake of the control precision and mining efficiency.
The mining vehicle's turning control process is restricted by many factors while working on the deep-sea slope. For instance, the mechanical properties of deep-sea mud, grade of the slope, the relativity between turning direction and gradient, turning speed and angle, the slip rate, the electro-hydraulic drive system and other unknown disturbances all have a definite link with the mining vehicle's parameters coupling effect during the steering course. The force relationship between the tracked vehicle and the seabed is first analyzed in this thesis. Secondly, the mining vehicle's kinematic model is deduced as driving on the slope. Finally, the optimal steering controller is designed as a key determinant of the turning control system. Since the turning control system takes the skidding and disturbances into account, the mining vehicle's tracking accuracy is enhanced and the driving safety on the slope is also ensured.
Through the predicted trajectories and gradient under the different turning way, a simulating research on the turning controller is carried out in the MATLAB/Simulink platform. The random interference is added into the simulation on the consideration of strong disturbance in the deep sea and slip between the tracks and sediment. And the results show the validity of the algorithm.
引文
[1]文保先.海洋开采[M].北京：冶金工业出版社,1996.1～12
[2]神谷夏实.深海底矿物资源开发的现状,国外金属矿山,1994,23(5)：48～54
[3]吴自军,周怀阳.刍议中国国际深海资源开发中长期发展战略,国际海底开发动态,2004,9(1)：1～6
[4]中国大洋矿产资源研究开发协会.深海采矿政策研讨会论文集.北京：海洋出版社,1991：72～206
[5]陈奋翔.海洋世纪的挑战[J]. 海洋开发与管理,1998,15(4)：4～8
[6]肖林京,方湄,张文明.大洋多金属结核开采研究进展与现状[J].金属矿山,2000,(8)：11～14
[7]肖林京.深海采矿扬矿管运动学和动力学特性研究[D].北京：北京科技大学,2000
[8]毛麟瑞.大洋潜在的矿产资源与开发前景[J].地球,1998(5)：17
[9]史力晨,王良曦,张兵志,等.履带车辆在坚实地面转向瞬态过程模拟计算[J].车辆与动力技术,2003,1：27～33
[10]卢文涛,李永奎,邓志刚,等.自行走车辆转向控制算法及MATLAB的实现[J].沈阳农业大学学报,2005,36(3)：358～360
[11]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
[12]王荣本,张荣辉,游峰,等.智能车辆弧线跟踪控制算法[J].吉林大学学报,2006,36(5)：731～735
[13]李岩,杨向东,陈恳.履带式移动机器人动力学模型及其反馈控制[J]. 清华大学学报,2006,46(8)：1377～1380
[14]史青录,孙逢春.履带式车辆斜坡转向稳定性研究[J].农业机械学报,2007,38(7)：22～26
[15]宋海军,高连华,程军伟.履带车辆中心转向模型研究[J].装甲兵工程学院学报,2007,21(2)：55～58
[16]王维涛,张磊.某型履带车辆下行不同坡度发动机制动特性研究[J].四川兵工学报,2009,5：52～57
[17]卜建国,徐友春,戴书泉,等.智能车自主导航的神经网络转向控制算法[J].装 甲兵工程学院学报,2007,21(4)：66～71
[18]王京起,陈慧岩,郑培.应用模糊自适应PID和预瞄策略的自主车辆转向控制[J].汽车工程,2003,25(4)：367～371
[19]Zhejun Fan, Y.Koren, D.Wehe, Tracked mobile robot control:hybrid approach. Control Eng. Practice,1995,3,(3):329～336
[20]k.Rintanen, H.Makela, etc. Development of an autonomous navigation system for an outdoor vehicle. Control Eng. Practice,1996,4(4):499～505
[21]Zvi Shiller, William Serate, Minh Hua. Trajectory Planning of Tracked Vehicles. 1993 IEEE Int. Conf. On Robotics and Automation, Atlanta, GA, pp.796～801
[22]N.Arada, J.P.Raymond. Optimal control problems with mixed control-state constraints. SIAM Journal on Control and Optimization,2001,39(5): pp.1391～1407
[23]M.Motta. On nonlinear optimal control problems with state constraints. SIAM Journalon Control and Optimization,1995,33(5):pp.1411～1424.
[24]A.Weinreb, A.E.Bryson. Optimal control of systems with hard control bounds. IEEE Transactions on Automatic Control,1985, AC-30(11):pp.1135～1138.
[25]R.W.H.Sargent. Optimal control. Journal of Computational and Applied Mathematics.2000,124(1-2):pp.361～371
[26]王仲民,岳宏,李充宁,等.轮式移动机器人轨迹跟踪的最优控制[J].机械科学与技术,2006,25(1)：21～23
[27]衣法臻,何平,胡恒章.机器人视觉动态目标跟踪的最优控制算法研究[J].哈尔滨工业大学学报,1999,31(3)：122～128
[28]周俊,姬长英.基于视觉导航的轮式移动机器人横向最优控制[J].机器人,2002,24(3)：209～212
[29]刘德满,吴成东,刘宗富,等.最优控制具有非完整性的两轮驱动机器人小车[J].东北大学学报,1994,15(3)：277～281
[30]熊蓉,褚健,何臻峰,等.四轮全方位移动机器人的建模和最优控制[J].控制理论与应用,2006,23(1)：93～98
[31]罗进生,张永俊.末端轨迹指定的机器人最优二次轨迹规划[J].机床与液压,2002,3：102～103
[32]杜峰,魏朗,赵建友.基于状态反馈的四轮转向汽车最优控制[J].长安大学学报,2008,28(4)：91～94
[33]吕安涛,宋正河,毛恩荣.拖拉机自动转向最优控制方法的研究[J].农业工程学报,2006,22(8)：116～119
[34]韩冰,陈军.拖拉机转弯最佳路径设计[J].农机化研究,2007,8：71～73
[35]徐林,孙树栋.基于最小值原理的壁面攀爬机器人时间最优控制[J].智能控制技术,2006,35(21)：37～46
[36]吴必豪.太平洋中部沉积物的矿物组成与沉积作用的研究[M].北京：地质出版社,1993
[37]宋连清.大洋多金属结核矿区沉积物土工性质[J].海洋学报,1999,6(21)：47～54
[38]Black, JRH. Metals Recovery from Manganese Nodules:A Review of Processing Schemes. Marine Mining:A New Beginning,1982, pp93-107, Humphrey, PB, The State of Hawaii, Honolulu, Hawaii
[39]韩雪梅,刘侃,周玉珑.履带车辆行驶力学[M].1988,北京：国防工业出版社
[40]M. G Bekker. Introduction to Terrain-Vehicle Systems. University of Michigan Press, Ann Arbor, MI 1969
[41]王良曦,王红岩.车体动力学[M].北京：国防工业出版社,2008
[42]陈峰,桂卫华,王随平,等.深海底履带机器车建模及仿真研究[J].机器人,2004,26(6)：510～515
[43]Wong, J.Y.Computer aided analysis of the effects of design parameters on the performance of tracked vehicles[J]. Journal of Terramechanics,1986,32(2): 95～124
[44]Gigler JK, Ward M. Simulation model for the prediction of the ground pressure distribution under tracked vehicles[J]. Journal of Terramechanics,1999,30(6): 46～91
[45]韩冷飞.深海作业型机器人防滑控制研究[D].长沙：中南大学,2008
[46]蒋新松.水下机器人[M].沈阳：辽宁科技出版社,2000
[47]Rudolph van der Merwe, Nando de Freitas, Arnaud Doucet, Eric Wan. The Unscented Particle Filter. Adv. Neural Inform, Process. Syst.,11,2000
[48]张克健.车辆地面力学[M].北京：国防工业出版社,2008
[49]刘延柱.刚体力学理论与应用[M].上海：上海交通大学出版社,2006
[50]诸文农.履带推土机机构与设计[M].北京：机械工业出版社,2000
[51]吴国锐.深海履带式钴结壳采矿车工作稳定性仿真研究[D].长沙：中南大学,2007
[52]贺建飚,唐修俊,张彭,等.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
[53]李远林.近海结构水动力学[J].华南理工大学出版社,2004
[54]彭晓军,史美萍,贺汉根.虚拟环境中装甲车辆运动仿真的研究[J].计算机仿真,2004,2(21)：28～31
[55]王震宇.深海履带式集矿机行驶性能虚拟现实研究[D].长沙：中南大学,2005
[56]N.D.Manring and R.E.Johnson. Modeling and designing a variable-displacement open loop pump. Journal Dynamic Systems, Measurement and Control,1996,118: 262～272
[57]Rudolph van der Merwe, Nando de Freitas,Arnaud Doucet, Eric Wan.The Unscented Particle Filter. Adv.Neural Inform, Process. Syst.,11,2000
[58]陈峰.深海底采矿机器车运动建模与控制研究[D].长沙：中南大学,2005
[59]王学宁.越野环境中坦克动力学建模研究[D].长沙：国防科技大学,2002
[60]吴绍斌,丁华荣,刘溧,等.履带车辆遥控驾驶的转向控制技术[J].兵工学报,2002,8,(23)：402～405
[61]J.X.Lee, GVukovich. Dynamic fuzzy logic system:Nonlinear system identification and application to robotic manipulators. Journal of Robotic Systems, 1997,14(6):pp.391～405
[62]C.Meyer, A.Rosch. Superconvergence properties of optimal control problems. SIAM Journal on Control and Optimization,2005,43(3):pp.970～985
[63]R.Castelein, A.Johnson. Constrained optimal control.IEEE Transactions on Automatic Control,1989,34(1):122～126
[64]吕显瑞,黄庆道.最优控制理论基础[M].北京：科学出版社,2008
[65]J.P.Lasalle. The Time Optimal Control Problem,Theory of Nonlinear Oscillations. Princeton Univ.Press,1961,5:1～24
[66]SC.Tsay, I. L.Wu, T-T.Long. Optimal control of linear time-delay systems via general orthogonal polynomials. International Journal of Systems Science, 1988,19(2):365～376
[67]M.Djouadi, GZames. On optimal robust disturbance attenuation. Systems&Control Letters,2002,46(5):343～351
[68]G.Y.Tang, Z.H.Sun, Z.Q.Yu. Feedforward and feedback optimal control for systems with step disturbances. Advances in Modeling and Analysis, 2002,57(1～2):53～61
[69]吴受章.最优控制理论与应用[M].北京：机械工业出版社,2008
[70]陈军,朱忠祥,鸟巢谅,等.拖拉机沿曲线路径跟踪控制[J].农业工程学报,2006,22(11)：108～112
[71]张利平.液压传动系统及设计[M].北京：化学工业出版社,2005
[72]姚怀新.行走机械液压传动与控制[M].北京：人民交通出版社,2002
[73]王春行.液压控制系统[M].北京：机械工业出版社,2004
[74]杨书林.深海集矿机轨迹跟踪算法研究[D].长沙：中南大学,2008
[75]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
[76]龚德文.深海集矿机测控系统的研究开发[J].矿冶工程,2004,24(3)：8～11
[77]Chenyang Lu, J A Stankovic. Design and evaluation of a feedback control EDF scheduling algorithm[J]. Proceedings of the 20th IEEE Real-Time System Symposium. Phoenix, Arizona:IEEE Computer Society,1999,55～60
[78]邢志伟,张禹,封锡盛.基于超短基线/多普勒的水下机器人位置估计[J].机器人,2003,23(3)：231～234
[79]G Buttazzo, M Spuri, F Seensini. Value vs.deadline scheduling in overload conditions [J]. Proceedings of the 16th IEEE Real-Time Systems Symposium.Los Alarmitos, California:IEEE Computer Society,1995,90～99
[80]杜春雷.ARM体系结构与编程[M].北京：清华大学出版社,2003
[81]江南,黄建国,李姗.长基线水下目标定位新技术研究[J].仪器仪表学报.2004,25(4)：77～80
[82]邓鲁华,宗光华.机器人导航中数字罗盘HMR3000的数据处理方法[J].沈阳航空工业学院学报.2006,23(4)：15～17
[83]陈志勇,高钟毓,张嵘.微角速度传感器在不同气压下的振动特性[J].清华大学学报.2002,42(6)：799～801
[84]Kuroda S. A simple stray-free capacitance meter by using an operational amplifier. IEEE Transactions on Instrumentation and Measurement.1983,32(4):512～515
[85]董煜茜,高钟毓,张嵘.微机械陀螺仪的性能分析[J].清华大学学报.1998,38(11)：1～3
[2]神谷夏实.深海底矿物资源开发的现状,国外金属矿山,1994,23(5)：48～54
[3]吴自军,周怀阳.刍议中国国际深海资源开发中长期发展战略,国际海底开发动态,2004,9(1)：1～6
[4]中国大洋矿产资源研究开发协会.深海采矿政策研讨会论文集.北京：海洋出版社,1991：72～206
[5]陈奋翔.海洋世纪的挑战[J]. 海洋开发与管理,1998,15(4)：4～8
[6]肖林京,方湄,张文明.大洋多金属结核开采研究进展与现状[J].金属矿山,2000,(8)：11～14
[7]肖林京.深海采矿扬矿管运动学和动力学特性研究[D].北京：北京科技大学,2000
[8]毛麟瑞.大洋潜在的矿产资源与开发前景[J].地球,1998(5)：17
[9]史力晨,王良曦,张兵志,等.履带车辆在坚实地面转向瞬态过程模拟计算[J].车辆与动力技术,2003,1：27～33
[10]卢文涛,李永奎,邓志刚,等.自行走车辆转向控制算法及MATLAB的实现[J].沈阳农业大学学报,2005,36(3)：358～360
[11]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
[12]王荣本,张荣辉,游峰,等.智能车辆弧线跟踪控制算法[J].吉林大学学报,2006,36(5)：731～735
[13]李岩,杨向东,陈恳.履带式移动机器人动力学模型及其反馈控制[J]. 清华大学学报,2006,46(8)：1377～1380
[14]史青录,孙逢春.履带式车辆斜坡转向稳定性研究[J].农业机械学报,2007,38(7)：22～26
[15]宋海军,高连华,程军伟.履带车辆中心转向模型研究[J].装甲兵工程学院学报,2007,21(2)：55～58
[16]王维涛,张磊.某型履带车辆下行不同坡度发动机制动特性研究[J].四川兵工学报,2009,5：52～57
[17]卜建国,徐友春,戴书泉,等.智能车自主导航的神经网络转向控制算法[J].装 甲兵工程学院学报,2007,21(4)：66～71
[18]王京起,陈慧岩,郑培.应用模糊自适应PID和预瞄策略的自主车辆转向控制[J].汽车工程,2003,25(4)：367～371
[19]Zhejun Fan, Y.Koren, D.Wehe, Tracked mobile robot control:hybrid approach. Control Eng. Practice,1995,3,(3):329～336
[20]k.Rintanen, H.Makela, etc. Development of an autonomous navigation system for an outdoor vehicle. Control Eng. Practice,1996,4(4):499～505
[21]Zvi Shiller, William Serate, Minh Hua. Trajectory Planning of Tracked Vehicles. 1993 IEEE Int. Conf. On Robotics and Automation, Atlanta, GA, pp.796～801
[22]N.Arada, J.P.Raymond. Optimal control problems with mixed control-state constraints. SIAM Journal on Control and Optimization,2001,39(5): pp.1391～1407
[23]M.Motta. On nonlinear optimal control problems with state constraints. SIAM Journalon Control and Optimization,1995,33(5):pp.1411～1424.
[24]A.Weinreb, A.E.Bryson. Optimal control of systems with hard control bounds. IEEE Transactions on Automatic Control,1985, AC-30(11):pp.1135～1138.
[25]R.W.H.Sargent. Optimal control. Journal of Computational and Applied Mathematics.2000,124(1-2):pp.361～371
[26]王仲民,岳宏,李充宁,等.轮式移动机器人轨迹跟踪的最优控制[J].机械科学与技术,2006,25(1)：21～23
[27]衣法臻,何平,胡恒章.机器人视觉动态目标跟踪的最优控制算法研究[J].哈尔滨工业大学学报,1999,31(3)：122～128
[28]周俊,姬长英.基于视觉导航的轮式移动机器人横向最优控制[J].机器人,2002,24(3)：209～212
[29]刘德满,吴成东,刘宗富,等.最优控制具有非完整性的两轮驱动机器人小车[J].东北大学学报,1994,15(3)：277～281
[30]熊蓉,褚健,何臻峰,等.四轮全方位移动机器人的建模和最优控制[J].控制理论与应用,2006,23(1)：93～98
[31]罗进生,张永俊.末端轨迹指定的机器人最优二次轨迹规划[J].机床与液压,2002,3：102～103
[32]杜峰,魏朗,赵建友.基于状态反馈的四轮转向汽车最优控制[J].长安大学学报,2008,28(4)：91～94
[33]吕安涛,宋正河,毛恩荣.拖拉机自动转向最优控制方法的研究[J].农业工程学报,2006,22(8)：116～119
[34]韩冰,陈军.拖拉机转弯最佳路径设计[J].农机化研究,2007,8：71～73
[35]徐林,孙树栋.基于最小值原理的壁面攀爬机器人时间最优控制[J].智能控制技术,2006,35(21)：37～46
[36]吴必豪.太平洋中部沉积物的矿物组成与沉积作用的研究[M].北京：地质出版社,1993
[37]宋连清.大洋多金属结核矿区沉积物土工性质[J].海洋学报,1999,6(21)：47～54
[38]Black, JRH. Metals Recovery from Manganese Nodules:A Review of Processing Schemes. Marine Mining:A New Beginning,1982, pp93-107, Humphrey, PB, The State of Hawaii, Honolulu, Hawaii
[39]韩雪梅,刘侃,周玉珑.履带车辆行驶力学[M].1988,北京：国防工业出版社
[40]M. G Bekker. Introduction to Terrain-Vehicle Systems. University of Michigan Press, Ann Arbor, MI 1969
[41]王良曦,王红岩.车体动力学[M].北京：国防工业出版社,2008
[42]陈峰,桂卫华,王随平,等.深海底履带机器车建模及仿真研究[J].机器人,2004,26(6)：510～515
[43]Wong, J.Y.Computer aided analysis of the effects of design parameters on the performance of tracked vehicles[J]. Journal of Terramechanics,1986,32(2): 95～124
[44]Gigler JK, Ward M. Simulation model for the prediction of the ground pressure distribution under tracked vehicles[J]. Journal of Terramechanics,1999,30(6): 46～91
[45]韩冷飞.深海作业型机器人防滑控制研究[D].长沙：中南大学,2008
[46]蒋新松.水下机器人[M].沈阳：辽宁科技出版社,2000
[47]Rudolph van der Merwe, Nando de Freitas, Arnaud Doucet, Eric Wan. The Unscented Particle Filter. Adv. Neural Inform, Process. Syst.,11,2000
[48]张克健.车辆地面力学[M].北京：国防工业出版社,2008
[49]刘延柱.刚体力学理论与应用[M].上海：上海交通大学出版社,2006
[50]诸文农.履带推土机机构与设计[M].北京：机械工业出版社,2000
[51]吴国锐.深海履带式钴结壳采矿车工作稳定性仿真研究[D].长沙：中南大学,2007
[52]贺建飚,唐修俊,张彭,等.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
[53]李远林.近海结构水动力学[J].华南理工大学出版社,2004
[54]彭晓军,史美萍,贺汉根.虚拟环境中装甲车辆运动仿真的研究[J].计算机仿真,2004,2(21)：28～31
[55]王震宇.深海履带式集矿机行驶性能虚拟现实研究[D].长沙：中南大学,2005
[56]N.D.Manring and R.E.Johnson. Modeling and designing a variable-displacement open loop pump. Journal Dynamic Systems, Measurement and Control,1996,118: 262～272
[57]Rudolph van der Merwe, Nando de Freitas,Arnaud Doucet, Eric Wan.The Unscented Particle Filter. Adv.Neural Inform, Process. Syst.,11,2000
[58]陈峰.深海底采矿机器车运动建模与控制研究[D].长沙：中南大学,2005
[59]王学宁.越野环境中坦克动力学建模研究[D].长沙：国防科技大学,2002
[60]吴绍斌,丁华荣,刘溧,等.履带车辆遥控驾驶的转向控制技术[J].兵工学报,2002,8,(23)：402～405
[61]J.X.Lee, GVukovich. Dynamic fuzzy logic system:Nonlinear system identification and application to robotic manipulators. Journal of Robotic Systems, 1997,14(6):pp.391～405
[62]C.Meyer, A.Rosch. Superconvergence properties of optimal control problems. SIAM Journal on Control and Optimization,2005,43(3):pp.970～985
[63]R.Castelein, A.Johnson. Constrained optimal control.IEEE Transactions on Automatic Control,1989,34(1):122～126
[64]吕显瑞,黄庆道.最优控制理论基础[M].北京：科学出版社,2008
[65]J.P.Lasalle. The Time Optimal Control Problem,Theory of Nonlinear Oscillations. Princeton Univ.Press,1961,5:1～24
[66]SC.Tsay, I. L.Wu, T-T.Long. Optimal control of linear time-delay systems via general orthogonal polynomials. International Journal of Systems Science, 1988,19(2):365～376
[67]M.Djouadi, GZames. On optimal robust disturbance attenuation. Systems&Control Letters,2002,46(5):343～351
[68]G.Y.Tang, Z.H.Sun, Z.Q.Yu. Feedforward and feedback optimal control for systems with step disturbances. Advances in Modeling and Analysis, 2002,57(1～2):53～61
[69]吴受章.最优控制理论与应用[M].北京：机械工业出版社,2008
[70]陈军,朱忠祥,鸟巢谅,等.拖拉机沿曲线路径跟踪控制[J].农业工程学报,2006,22(11)：108～112
[71]张利平.液压传动系统及设计[M].北京：化学工业出版社,2005
[72]姚怀新.行走机械液压传动与控制[M].北京：人民交通出版社,2002
[73]王春行.液压控制系统[M].北京：机械工业出版社,2004
[74]杨书林.深海集矿机轨迹跟踪算法研究[D].长沙：中南大学,2008
[75]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
[76]龚德文.深海集矿机测控系统的研究开发[J].矿冶工程,2004,24(3)：8～11
[77]Chenyang Lu, J A Stankovic. Design and evaluation of a feedback control EDF scheduling algorithm[J]. Proceedings of the 20th IEEE Real-Time System Symposium. Phoenix, Arizona:IEEE Computer Society,1999,55～60
[78]邢志伟,张禹,封锡盛.基于超短基线/多普勒的水下机器人位置估计[J].机器人,2003,23(3)：231～234
[79]G Buttazzo, M Spuri, F Seensini. Value vs.deadline scheduling in overload conditions [J]. Proceedings of the 16th IEEE Real-Time Systems Symposium.Los Alarmitos, California:IEEE Computer Society,1995,90～99
[80]杜春雷.ARM体系结构与编程[M].北京：清华大学出版社,2003
[81]江南,黄建国,李姗.长基线水下目标定位新技术研究[J].仪器仪表学报.2004,25(4)：77～80
[82]邓鲁华,宗光华.机器人导航中数字罗盘HMR3000的数据处理方法[J].沈阳航空工业学院学报.2006,23(4)：15～17
[83]陈志勇,高钟毓,张嵘.微角速度传感器在不同气压下的振动特性[J].清华大学学报.2002,42(6)：799～801
[84]Kuroda S. A simple stray-free capacitance meter by using an operational amplifier. IEEE Transactions on Instrumentation and Measurement.1983,32(4):512～515
[85]董煜茜,高钟毓,张嵘.微机械陀螺仪的性能分析[J].清华大学学报.1998,38(11)：1～3