超小型无人直升机飞控系统及自主滞空飞行的研究
|
摘要
超小型无人直升机具有成本低、体积小、携带方便、起飞着陆场地小等特点,尤其是可做滞空飞行,这使其在反恐防爆等重要场合进行应用的优越性特别突出。但是,超小型无人直升机是一个非线性、强耦合以及非稳定的动力学系统,尤其是在滞空飞行状态下,其稳定性非常差,更容易受到风等外力的干扰,所以,进行超小型无人直升机飞控系统以及自主滞空飞行的研究,具有重要的理论意义和应用价值。
本论文在分析了国内外对超小型无人直升机系统研究的基础上,归纳了超小型无人直升机系统的若干问题,并根据研究背景的需要,提出了进行超小型无人直升机飞控系统的研究目标,并规划了为实现研究目标而需要进行的研究内容。
接着,从实际需求出发,对超小型无人直升机系统的传感器、控制器和通讯系统进行了选型,并基于模块化的指导思想进行了超小型无人直升机的总体方案设计。
姿态传感器是超小型无人直升机控制系统的核心部件,为了得到高性能的姿态参考系统,本论文对超小型无人直升机机载惯性传感器进行了信息融合的研究;融合的主要思想是:积分角速率信号得到预估姿态,然后由加速度计和磁力计得到的姿态角作为观测量,纠正预估姿态中由于随机漂移等因素引起的误差,得到最优的姿态信息,并同时对角速度陀螺的漂移误差进行估计。根据上述融合思想,本论文提出了卡尔曼滤波算法一种新的模型,并进行了线性化和离散化处理,最后通过实验验证了基于该扩展卡尔曼滤波算法的低成本姿态参考系统的静态性能和动态性能。
对于一个实际的系统,推导其数学模型是一个基本而且重要的部分,一个好的数学模型可以使我们明白系统的运动机理和物理结构,对进行控制系统的设计有很大的帮助。为了建立超小型无人直升机的数学模型,本论文首先建立了超小型无人直升机的机体刚体动力学方程和空气动力学模型,同时对主桨和贝尔—希勒翼进行了研究,在上述研究的基础上,通过对滞空飞行状况下超小型无人直升机动力学方程的合理假设,先后求解得到伺服小翼挥舞角的表达式以及俯仰力矩、横滚力矩和偏航力矩的简化方程,从而确定了具有物理意义的滞空飞行状态下的超小型无人直升机姿态模型的结构。
对上述滞空飞行状态下超小型无人直升机姿态模型中存在的一些未知参数,本论文通过系统辨识的方法得到上述参数。首先,分析超小型无人直升机的特点,并根据其特点设计了飞行实验,然后利用飞行数据,采用预测误差法对姿态模型中的未知参数进行系统辨识,从而获得完整的姿态模型;然后,通过仿真对上述姿态模型进行研究,通过研究发现:在滞空飞行状态下,超小型无人直升机姿态的耦合性主要存在与俯仰通道和横滚通道之间。
超小型无人直升机的飞控系统包括导航控制和姿态控制,而且导航控制一般也是以姿态控制作为内环来实现的。姿态控制是超小型无人直升机飞控系统的核心问题,也是最关键的问题。根据上面的分析,本论文建立以姿态控制为内环,导航控制为外环的超小型无人直升机飞控系统的控制框架。针对超小型无人直升机姿态通道之间的耦合性,本论文首先采用了一种神经网络解耦控制算法;然后提出了一种模糊规则前提、模糊规则结论和解模糊具有自适应调节性能的超小型无人直升机姿态自适应模糊控制算法,并对超小型无人直升机姿态控制系统的性能进行了仿真验证;另外,对超小型无人直升机的导航系统进行了研究。
在上述几章研究的基础上,本论文对超小型无人直升机飞控系统的软硬件进行了设计。本论文首先采用模块化的思想设计了机载飞控系统,它由姿态参考系统模块、GPS制导模块、舵机控制模块和主控模块组成。然后,根据各个模块的功能,对机载飞控系统的软件任务进行了分解,简化了软件设计的难度;并采用时钟驱动策略和循环查询标志策略相结合的方法,对机载飞控系统的软件任务进行调度。并且,设计具有实时监控功能的地面监控系统。
最后,通过超小型无人直升机系统完成自主滞空飞行,本论文验证了设计的超小型无人直升机飞控系统的性能。首先,设计了超小型无人直升机系统的自主滞空飞行试验,然后,通过分析试验数据验证了超小型无人直升机系统导航控制和姿态控制算法的可行性。
Subminiature Unmanned Helicopter (SUH) has the advantage of the low cost、the small volume、the conveniency for transportation、the small land for flying-off and landfall. Especially,it can hang in the small space. So it has the widely purpose in the military and civial fields. The flight control system is the key of the subminiature unmanned helicopter system. The research of flight control system and autonomously hanging is very valuable.
Fistly, from the view of the actual requirement, the sensors、the microchip and data linker of subminiature unmanned helicopter system were choosed. The whole scheme of system is designed on the thought of modularization.
Attitude sensors are the key part to the flight control system. For the high precision attitude and heading referrence system (AHRS), the information fuse to the sensors on the flight control system was carried out. The main thought of the data fuse is that estimated attitude was get by the integral the gyroscope, the attitude from the acceleratoremter and magnetmeter was regard as the observation data to correct the error of the estimated attitude and get the error of the gyroscope. Based on the above thought, the new kalman filter mode was put forward and was linearizated and discreted. Finally, the experiment was carried out to testify the performance of the AHRS.
To the actual system, the model of system is an importance part. The high precision model is very helpful to the design the control system. For the model of the SUH, the geostatics equation and aerodynamics equation was set up. At the same time, the main blade and the bell-hiller flybar were studied. Based on the above research, the wave angle of bell-hiller flybar、pitch moment equation、roll moment equation and yaw moment equation was got by the reasonable assumption to the geostatics equation of SUH system at the flying state of hanging. So the structure of the attitude model of SUH sytem at hanging was got.
To the unknown parameters of the above attitude model,the system identification was carried out. Firstly, the characteristic of SUH system was researched. The flying experimation was implemented to get the data. Then the prediction error method was used to get the unknown parameters. So the integrated attitude model of SUH was got. Finally the attitude model of SUH system was researched by the simulation. The result was that the coupling effect of SUH system at the handing mainly existed in pitch channel and roll channel.
The flight control system of SUH system included of the navigation system and attitude control system. And the navigation system was carried out by the contol system being the inner circle. The attitude control system was the basic and key part problem. Based on above analysis, the flight contol sytem by attitude control system being the inner circle and navigation control system being the outer circle was designed. To deal with the coupling effect of the attitude channels, the nerve network athrimetic was dopted. Then the adaptive fuzzy arithmetic was put forward. The performation of the flight control system was testified by the simulation. And the ground surveillance system was designed too.
Besed on the low-cost attitude and heading referrence system、system identification、the nerve network decoupled arithmetic and the adaptive fuzzy arithmetic, the software and hardware system was designed. Then the ground surveillance system was designed too.
Finally, the performation of the flight control system was testified by the autonomously hanging flight which is the worst flight state. The navigtaion control and attitude control system was proved to be viable by analyzing the flight data.
本论文在分析了国内外对超小型无人直升机系统研究的基础上,归纳了超小型无人直升机系统的若干问题,并根据研究背景的需要,提出了进行超小型无人直升机飞控系统的研究目标,并规划了为实现研究目标而需要进行的研究内容。
接着,从实际需求出发,对超小型无人直升机系统的传感器、控制器和通讯系统进行了选型,并基于模块化的指导思想进行了超小型无人直升机的总体方案设计。
姿态传感器是超小型无人直升机控制系统的核心部件,为了得到高性能的姿态参考系统,本论文对超小型无人直升机机载惯性传感器进行了信息融合的研究;融合的主要思想是:积分角速率信号得到预估姿态,然后由加速度计和磁力计得到的姿态角作为观测量,纠正预估姿态中由于随机漂移等因素引起的误差,得到最优的姿态信息,并同时对角速度陀螺的漂移误差进行估计。根据上述融合思想,本论文提出了卡尔曼滤波算法一种新的模型,并进行了线性化和离散化处理,最后通过实验验证了基于该扩展卡尔曼滤波算法的低成本姿态参考系统的静态性能和动态性能。
对于一个实际的系统,推导其数学模型是一个基本而且重要的部分,一个好的数学模型可以使我们明白系统的运动机理和物理结构,对进行控制系统的设计有很大的帮助。为了建立超小型无人直升机的数学模型,本论文首先建立了超小型无人直升机的机体刚体动力学方程和空气动力学模型,同时对主桨和贝尔—希勒翼进行了研究,在上述研究的基础上,通过对滞空飞行状况下超小型无人直升机动力学方程的合理假设,先后求解得到伺服小翼挥舞角的表达式以及俯仰力矩、横滚力矩和偏航力矩的简化方程,从而确定了具有物理意义的滞空飞行状态下的超小型无人直升机姿态模型的结构。
对上述滞空飞行状态下超小型无人直升机姿态模型中存在的一些未知参数,本论文通过系统辨识的方法得到上述参数。首先,分析超小型无人直升机的特点,并根据其特点设计了飞行实验,然后利用飞行数据,采用预测误差法对姿态模型中的未知参数进行系统辨识,从而获得完整的姿态模型;然后,通过仿真对上述姿态模型进行研究,通过研究发现:在滞空飞行状态下,超小型无人直升机姿态的耦合性主要存在与俯仰通道和横滚通道之间。
超小型无人直升机的飞控系统包括导航控制和姿态控制,而且导航控制一般也是以姿态控制作为内环来实现的。姿态控制是超小型无人直升机飞控系统的核心问题,也是最关键的问题。根据上面的分析,本论文建立以姿态控制为内环,导航控制为外环的超小型无人直升机飞控系统的控制框架。针对超小型无人直升机姿态通道之间的耦合性,本论文首先采用了一种神经网络解耦控制算法;然后提出了一种模糊规则前提、模糊规则结论和解模糊具有自适应调节性能的超小型无人直升机姿态自适应模糊控制算法,并对超小型无人直升机姿态控制系统的性能进行了仿真验证;另外,对超小型无人直升机的导航系统进行了研究。
在上述几章研究的基础上,本论文对超小型无人直升机飞控系统的软硬件进行了设计。本论文首先采用模块化的思想设计了机载飞控系统,它由姿态参考系统模块、GPS制导模块、舵机控制模块和主控模块组成。然后,根据各个模块的功能,对机载飞控系统的软件任务进行了分解,简化了软件设计的难度;并采用时钟驱动策略和循环查询标志策略相结合的方法,对机载飞控系统的软件任务进行调度。并且,设计具有实时监控功能的地面监控系统。
最后,通过超小型无人直升机系统完成自主滞空飞行,本论文验证了设计的超小型无人直升机飞控系统的性能。首先,设计了超小型无人直升机系统的自主滞空飞行试验,然后,通过分析试验数据验证了超小型无人直升机系统导航控制和姿态控制算法的可行性。
Subminiature Unmanned Helicopter (SUH) has the advantage of the low cost、the small volume、the conveniency for transportation、the small land for flying-off and landfall. Especially,it can hang in the small space. So it has the widely purpose in the military and civial fields. The flight control system is the key of the subminiature unmanned helicopter system. The research of flight control system and autonomously hanging is very valuable.
Fistly, from the view of the actual requirement, the sensors、the microchip and data linker of subminiature unmanned helicopter system were choosed. The whole scheme of system is designed on the thought of modularization.
Attitude sensors are the key part to the flight control system. For the high precision attitude and heading referrence system (AHRS), the information fuse to the sensors on the flight control system was carried out. The main thought of the data fuse is that estimated attitude was get by the integral the gyroscope, the attitude from the acceleratoremter and magnetmeter was regard as the observation data to correct the error of the estimated attitude and get the error of the gyroscope. Based on the above thought, the new kalman filter mode was put forward and was linearizated and discreted. Finally, the experiment was carried out to testify the performance of the AHRS.
To the actual system, the model of system is an importance part. The high precision model is very helpful to the design the control system. For the model of the SUH, the geostatics equation and aerodynamics equation was set up. At the same time, the main blade and the bell-hiller flybar were studied. Based on the above research, the wave angle of bell-hiller flybar、pitch moment equation、roll moment equation and yaw moment equation was got by the reasonable assumption to the geostatics equation of SUH system at the flying state of hanging. So the structure of the attitude model of SUH sytem at hanging was got.
To the unknown parameters of the above attitude model,the system identification was carried out. Firstly, the characteristic of SUH system was researched. The flying experimation was implemented to get the data. Then the prediction error method was used to get the unknown parameters. So the integrated attitude model of SUH was got. Finally the attitude model of SUH system was researched by the simulation. The result was that the coupling effect of SUH system at the handing mainly existed in pitch channel and roll channel.
The flight control system of SUH system included of the navigation system and attitude control system. And the navigation system was carried out by the contol system being the inner circle. The attitude control system was the basic and key part problem. Based on above analysis, the flight contol sytem by attitude control system being the inner circle and navigation control system being the outer circle was designed. To deal with the coupling effect of the attitude channels, the nerve network athrimetic was dopted. Then the adaptive fuzzy arithmetic was put forward. The performation of the flight control system was testified by the simulation. And the ground surveillance system was designed too.
Besed on the low-cost attitude and heading referrence system、system identification、the nerve network decoupled arithmetic and the adaptive fuzzy arithmetic, the software and hardware system was designed. Then the ground surveillance system was designed too.
Finally, the performation of the flight control system was testified by the autonomously hanging flight which is the worst flight state. The navigtaion control and attitude control system was proved to be viable by analyzing the flight data.
引文
[1]http://www.cs.cmu.edu/afs/cs/project/chopper/www/index.html
[2]http://sun-valley.stanford.edu/
[3]http://gewurtz.mit.edu/research/heli.htm
[4]http://pdv.cs.tu-berlin.de/MARV1N/
[5]http://robotics.eecs.berkeley.edu/bear/people.htm
[7]http://icsl.marc.gatech.edu/index.asp?page=none
[8]http://www.rose-hulman.edu/arc/index.htm
[9]http://rhitrobotics.org
[10]http://www-2.cs.cmu.edu/afs/cs/project/chopper/www/capability.
[11]邓寅喆.超小型无人驾驶直升机研究现状[J],机电一体化2004(1):P18-P21.
[12]马晓平.系统工程学在无人机研制中的应用[J],航空科学技术2003(4):P30-P31.
[13]邱晓红.无人机系统技术发展趋势[J].航空科学技术,2000(1):P28-P30.
[14]袁锁中.数字式无人机飞控系统研制[J].计算机测量与控制,2003(1):P64-P67.
[15]刘诗斌,严家明,孙希任.无人机航向测量的罗差修正研究[J].航空学报,2001(1):P78-P90.
[16]孙杰,林宗坚,崔红霞.无人机低空遥感监测系统[J].遥感信息,2003(1):P25-P27.
[17]苏昀,张晓林.无人直升机遥控系统关键技术研究[J].遥测遥控,2002(6):P53-P58.
[18]杨宁,王保印.无人机航空电子综合测试系统[J].武器装备自动化,2004(1):P7-P10.
[19]Technical paper for International Aerial Robotics Competition 2004 Dronalab UAV team 2004.
[20]Simon Fraser University Aerial Robotics Group "Automated Helicopter System Integration"Competition Paper Entry 2004 International Aerial Robotics Competition
[21]Helicopter Flight Automation.Pavel Haintz,School of Engineering Science Simon Fraser University 2003
[22]Pedro Santana.Unmanned Helicopters Applied to Humanitarain Deming[C].Emerging Technologies and Factory Automation,2005.ETFA 2005.10th IEEE Conference on.Volume 1,19-22 Sept.2005 Page(s)729-P738.
[23]The Development of a Small Autonomous Helicopter Robot for Search and Rescue in Hostile Environments.Aerial Robotics Group Department of Aeronautics and Astronautics Massachusetts Institute of Technology Cambridge MA 02139 1999
[24]MAVIN Technology university Berlins Flying Robot for IARC Millennial Event.Technology University Berlin Department of Computer Science Real-time Systems& Robotics Group 2000
[25]Ongoing Development of an Autonomous Aerial Reconnaissance System at Georgia Tech.Alison A.Proctor UAV Laboratory School of Aerospace Engineering Georgia Institute of Technology 2003
[26]Development of Autonomous Aerial Reconnaissance System.John M.Connelly,Scott M.Beecher,David L.Urlacher,School of Engineering and Engineering Technology LeToureau University 2004
[27]Autonomous Air Vehicle Implementation Into The 2004 International Aerial Robotics Competition Adam Felske,David Muncaster DeVry Institute of Technology Calgray Alberta 2004
[28]Design and Development of South Dakata School of Mines and Technology Aerial Robotic Reconnaissance System.Jason Howe,South Dakota School of Mines and Technology Unmanned Aerial Vehicle Team Rapid City,South Dakota 2003
[29]Rose-Hulman Institute of Technology Autonomous Helicopter for the 2004International Aerial Robotics Competition.2004
[30]A Network-Based Implementation of an Aerial Robotic System.University of waterloo Department of Electrical & Computer Engineering Waterloo Ontatrio,Canada 2004
[31]秦永元等《卡尔曼滤波与组合导航原理》[M].西安:西北工业大学出版社1998年.
[32]百宇俊.神经网络辅助卡尔曼滤波技术在组合导航系统中的应用研究[J].中国惯性技术学报2001(2)P40-P43.
[33]钱正祥.GPS/INS组合导航卡尔曼滤波技术[J].仪器仪表学报,2003(4):P533-P534.
[34]高宪军.GPS/INS组合导航系统的研究[J].光学精密工程,2004(2):P146-P150.
[35]许丽佳.GPS/INS组合导航系统中的信息融合算法研究[J].计算机仿真,2004(5):P20-P23.
[36]仲元昌.GPS/INS组合系统在飞船自主定位中的应用[J],重庆大学学报2002(7):P124-P127.
[37]彭霞.联邦卡尔曼滤波与集中式卡尔曼滤波的等价性[J].青岛科技大学学报2005(2):P169-P172
[38]刘海涛.低成本INS/GPS组合导航系统算法研究及其实现[J].遥测遥控,2003(3):P36-P41
[39]Chang-sun Yoo,Iee-ki Ahn.Low cost GPS/INS Sensor Fusion System For UAV Navigation[C].Digital Avionics Systems Conference,2003.DASC'03.The 22nd Volume 2,12-16 oct.2003 Page(s):8.A.1-8.1-9 vol.2.
[40]Chirstopher Hide,Terry Maritin Simith.Adaptive Kalman Filtering Algorithms for Integrating GPS and Low Cost INS[C].Position Location and Navigation Symposium,2004.PLANS 200426-29 April 2004 Page(s):227-233.
[41]X.Yun,E.R.Bachmann,R.B.Testing and Evaluation of an Integrated GPS/INS System for small AUV Navigation[C].IEEE Journal Of Oceanic Engineering,VOL,24,No,3,JULY 1999.
[42]Roy R.Minor,David W,Rowe.Utilization of GPS/MEMS-IMU for Measurement of Dynamics for Range Testing of Missiles and Rockets[C].Position Location and Navigation Symposium,IEEE 1998,20-23 April 1998 Page(s):602-607.
[43]Joerg s.Dittrich,Eric N.Jonhson.Multi-Sensor Navigation System for an Autonomous Helicopter[C].in Proceedings The 21st Digital Avionics Systems Conference,Volume 2,2002 Page(s):SCl-1-8C1-19 vol.2.
[44]Albert-Jan Baerveldt and Robert Klang.A Low-cost and Low-Weight Attitude Estimation System for an Autonomous Helicopter[C].in Proceedings of IEEE International Conference on Intelligent Engineering Systems,15-17 Sept.1997Page(s):391-395.
[45]Implementation and Experimental Results of a Quaternion-Based Kalman Filter for Human Body Motion Tracking[C].in Proceedings of the 2005 IEEE international Conference on Rbotics and Automation Barchelona,Spain,April 2005:P317-P322.
[46]Demoz Gebre-egzibher,Gabriel H.Elkain.A Gyro-Free Quaternion-Based Attitude Determination System Suitable for Implemantation Using Low Cost Sensors[C].in IEEE Position Location and Navigation Symposium,13-16 March 2000 Page(s):185-192.
[47]Billur Barshan and Hugh E Durrant-Whyte.Interial Navigation Systems for Mobile Robots[C],in IEEE TRANSCATIONS ON ROBOTICS AND AUTOMATIO -N,VOL,11 NO,3.,JUNE 1995:P328-P342.
[48]Attitude and Gyro Bias Estimation for a Flying UAV[C].2005 IEEE/RSJ International Conference on Intelligent Robots and Systems,2005.(IROS 2005).2-6 Aug.2005 Page(s):1114-1120.
[49]Tuan Manh Pham.Kalman filter mechanization for INS airstart[J].Aerospace and Electronic Systems Magazine,IEEE Volume 7,Issue 1,Jan.1992 Page(s):3-11
[50]Xianmin Ma,Youlin Gui.Extended Kalman Filter for Speed Sensor-less DTC Based on DSP[C].in Proceedings of the 4b World Congress on Intelligent Control and Automation,lune 10-14,2002,Shanghai,P.R.China:2002:p 119-p213.
[51]方崇智等《过程辨识》[M].北京:清华大学出版社,1988年8月.
[52]蔡金狮等《飞行器系统辨识》[M].北京:北京宇航出版社,1995年.
[53]刘叔军,盖晓华,樊京.《MATLAB7.控制系统应用与实例》[M].北京:机械工业出版社,2006.
[54]侯媛彬,汪梅,王立琦.《系统辨识以及MATLAB仿真》[M].北京:科学出版社,2004.
[55]王志贤.《最优状态估计与系统辨识》[M].西安:西安工业大学出版社,2004年.
[56]陈皓生.悬停状态下微型直升机航向模型的系统辨识 清华大学学报(自然科学版)2003年第43卷第2期P184-P187
[57]陈皓生.微型直升机动力学建模的研究现状 飞行力学 第21卷第3期2003年9月P1-P4.
[58]Sung K Kim Modeling,identification,and trajectory planning for a model-scale helicopter,A dissertation for degree of Doctor of Philosophy in The University of Michigan.
[59]Colin Rhys,Theodore Helicopter flight dynamics simulation with refined aerodynamic modeling A dissertation for degree of Doctor of Philosophy in The University of Maryland,College.
[60]Jaune Del Cerro,Julio Valero.Modeling and identification of a small unmanned helicopter[J].in Proceedings of World Automation Congress.Volume 15,28 Junel July 2004 Page(s):461-466.
[61]高金源.《飞机电传操作系统与主动控制技术》[M].北京:北京航天航空大学出版社,2005年.
[62]高正等.《直升机飞行动力学》[M].科学出版社,2003年.
[63]张明廉等.《飞控系统》[M].北京:北京航天工业出版社,1994年.
[64]刘哥群.《无人机飞行控制器设计以及检测与控制技术研究》[D].[硕士论文]西安:西北工业大学硕士论文,2004年.
[65]宋子善等.无人直升机综合飞控系统设计[J],北京航天航空大学学报,1999(3):P280-P283.
[66]郎平.一种改进的控制系统OFT设计算法[J],哈尔滨工业大学学报1997(4):P65-P71
[67]肖永利.定量反馈理论(QFT)及其设计应用[J],信息与控制1999(6):P437-P445.
[68]韦巍 定量反馈理论在鲁棒与容错飞控系统中的应用[J],南京航空航天大学学报2001(2):P130-P134.
[69]柴天佑.多变量自适应解耦控制及应用[M].北京:科学出版社,2001年.
[70]Xin Hou,Ping Li,Zhou Fang,Bo han.An Application of Fuzzy PID Alogrithm on Unmanned Helicopter Attitude Control[C].in Proceedings of the 6th World Congress on Intelligent Control and Automation,June 21-23,Dalian,china,P9129-P9133.
[71]曾丽兰,王道波,樊春霞.基于模糊PD的无人直升机解耦控制研究[J],应用科学学报,2004:P498-P502.
[72]曾丽兰,王道波,郭才根等.无人驾驶直升机飞行控制技术综述[J],控制与决策,2006:P361-P366.
[73]宋明山,蒋支运,吴文海.无人直升机飞控系统设计[J],飞机设计,2003:P67-P72.
[74]宋彦国,张呈林.直升机模糊飞控系统的现状与发展[J],直升机技术,2002(1):P41-P45.
[75]宋彦国,张呈林.直升机内回路姿态模糊控制[J],航空学报,2003(4):P365-P369.
[76]Edgar N.Sanchez,Hector M.Becerra,Carlos M.Velez.Combining fuzzy and PID control for an unmanned helicopter.in Annual Meeting of the North American Fuzzy Information Processing Society.2005:P235-P240.
[77]W.GHARIEB.Fuzzy Control To Multivariable Systems Case Study:Helicopter Meol[C].in Fuzzy Systems,1996.,Proceedings of the Fifth IEEE International Conference,1996:P400-P405.
[78]Carla Cavalcante,Janette Cardoso.Design and Tuning of a Helicopter Fuzzy Controller[C]Fuzzy Systems,International Joint Conference of the Fourth IEEE International Conference on Fuzzy Systems and The Second Proceedings of 1995 IEEE International Conference on International Fuzzy Engineering Symposium., , 1995:P1549-1553.
[79]Chun-Liang Lin. On the Design of an Adaptive Fuzzy Gain-Scheduled Autopilot[C]. in Proceedings of the American Control Conferece, Achorage, AK May 8-10, 2002:P1567-P1572.
[80]Dariusz Krol. Helicopter Intelligence in Hover Quality Improvement of the Fuzzy Regulator [C]. in proceedings of the Sixth international conference on Intelligent Systems Design and Applications, 2006:P120—P125.
[81]Dong-Ling Tsay, Hung-Yuan Chung, and Ching-Jung Lec. The Adaptive Control of Nonlinear Systems Using THE Sugeno-Type of Fuzzy Logic [J]. IEEE TRANSACTIONS ON FUZZY SYSTEMS, VOL. 7, NO. 2, APRIL 1999:P225-P229.
[82]Pil-Sang Yoon. Adaptive Fuzzy Control of Nonaffine Nonlinear Systems Using Takagi-Sugeno Fuzzy Models[C]. Fuzzy Systems, 2001. The 10th IEEE International Conference on Volume 2, 2-5 Dec. 2001 Page(s) :642 - 645 vol. 3
[83]J.-Y. Chen and C.-C. Wong. Implementation of the Takagi-Sugeno Model-based fuzzy control using an adaptive gain controller[J]. IEE Proc.-Control Theory Application,Vol 147, No. 5, September 2000:P509-P514.
[84]Gang Feng. A Survey on Analysis and Desgin of Model-Based Fuzzy Control Systems [J]. IEEE TRANSACTIONS ON FUZZY SYSTEMS, VOL. 14,NO. 5, OCTOBER 2006:P676-P697.
[85]DAI Jiyang, MAO Jianqin. Fuzzy Switching Control Law Design for Helicopters[C]. in Proceedings. 2002 IEEE Region 10 Conference on Computers, Communications, Control and Power Engineering Volume 3, 28-31 Oct. 2002 Page(s): 1634 - 1637 vol.3.
[86]I, Rojas, H. Pomares, C. G. Puntonet. On-line Apaptive Fuzzy Controller: Application to Helicopter Stabilization of the altitude of a helicopter [C]. in Internaltional Symposium on Computaional Intelligence for Measurements Systems and applications Lugano, Switzerland, 29-31 July 2003: P119-P123.
[87]T. John Koo and Shankar Sastry. Output Tracking Control Design of a Helicopter Model Based on Approximate Linearization [J]. Proceedings of the 37th IEEE Conference on Decision & Control Tampa, Florida USA December 1998:P3635-P3640.
[88] D. J. Wallcer, M. C. Turner, AJ. Smerlas. Robust Control of the Longitudinal and Lateral Dynamics of the BELL 205 Helicopter[J],Proceedings of the American Control Conference San Diego,California June 1999:P2742-P2746.
[89]I.Rojas,H.Pomares,F.J.Pelayo,M.Anguita,E.Ros.New methodology for the development of adaptive and self-learning fuzzy controllers in real time[C].International Journal of Approximate Reasoning 21(1999)109-136.
[90]H.Pomares *,I.Rojas,J.Gonz_alez,F.Rojas,M.Damns,A two-stage approach to self-learning direct fuzzy controllers[C].International Journal of approximate Reasoning 29(2002) 267-289.
[91]董绪荣等.《GPS/INS组合导航定位及其应用》[M].北京:国防工业出版社,1998年.
[92]王惠南.《GPS导航原理与应用》[M].北京:科学出版社,2003年.
[93]梁秋僮,程维明.超小型飞行器GPS自主导航算法的研究[J].无线电工程,2002(12):P27-P30.
[94]龚真春,宋执环,李平.超小型无人机GPS导航中的坐标转换[J].武器装备自动化,2005:P29-P30.
[95]王永生,李翔鹏.无人驾驶飞机GPS导航系统的设计与实现[J].西北工业大学学报,1996(3):P481-P484.
[96]吴蕾,王壬林.一类无人直升机的导航与控制[J].飞机设计2004(1):P60-P65.
[97]崔麦会,严德斌.GPS在无人机导航中的应用.现代防御技术.1999(3):P39-P40.
[98]王永林,黄一敏.虑侧风情况下的无人机自主导航控制技术研究[J].沈阳航空工业学院学报.2005(5):P7-P11.
[99]Ioannis K.Nikolos,Kimon P.Valavanis,Evolutionary Algorithm Based Offline/Online Path Planner for UAV Navigation[C].IEEE TRANSACTIONS ON SYSTEMS,MAN,AND CYBERNETICS—PART B:CYBERNETICS,VOL.33,NO.6,DECEMBER 2003:P898-P912.
[100]Guang Yang,Vikam kapila.Optimal Path Planning for Unmanned Air Vehicles with Kinematic and Tactical Constraints[C].in proceedings of the 41st IEEE Conference on Decision and Control Las Vegas,Navanda USA,December 2002:P1301-P1306
[2]http://sun-valley.stanford.edu/
[3]http://gewurtz.mit.edu/research/heli.htm
[4]http://pdv.cs.tu-berlin.de/MARV1N/
[5]http://robotics.eecs.berkeley.edu/bear/people.htm
[7]http://icsl.marc.gatech.edu/index.asp?page=none
[8]http://www.rose-hulman.edu/arc/index.htm
[9]http://rhitrobotics.org
[10]http://www-2.cs.cmu.edu/afs/cs/project/chopper/www/capability.
[11]邓寅喆.超小型无人驾驶直升机研究现状[J],机电一体化2004(1):P18-P21.
[12]马晓平.系统工程学在无人机研制中的应用[J],航空科学技术2003(4):P30-P31.
[13]邱晓红.无人机系统技术发展趋势[J].航空科学技术,2000(1):P28-P30.
[14]袁锁中.数字式无人机飞控系统研制[J].计算机测量与控制,2003(1):P64-P67.
[15]刘诗斌,严家明,孙希任.无人机航向测量的罗差修正研究[J].航空学报,2001(1):P78-P90.
[16]孙杰,林宗坚,崔红霞.无人机低空遥感监测系统[J].遥感信息,2003(1):P25-P27.
[17]苏昀,张晓林.无人直升机遥控系统关键技术研究[J].遥测遥控,2002(6):P53-P58.
[18]杨宁,王保印.无人机航空电子综合测试系统[J].武器装备自动化,2004(1):P7-P10.
[19]Technical paper for International Aerial Robotics Competition 2004 Dronalab UAV team 2004.
[20]Simon Fraser University Aerial Robotics Group "Automated Helicopter System Integration"Competition Paper Entry 2004 International Aerial Robotics Competition
[21]Helicopter Flight Automation.Pavel Haintz,School of Engineering Science Simon Fraser University 2003
[22]Pedro Santana.Unmanned Helicopters Applied to Humanitarain Deming[C].Emerging Technologies and Factory Automation,2005.ETFA 2005.10th IEEE Conference on.Volume 1,19-22 Sept.2005 Page(s)729-P738.
[23]The Development of a Small Autonomous Helicopter Robot for Search and Rescue in Hostile Environments.Aerial Robotics Group Department of Aeronautics and Astronautics Massachusetts Institute of Technology Cambridge MA 02139 1999
[24]MAVIN Technology university Berlins Flying Robot for IARC Millennial Event.Technology University Berlin Department of Computer Science Real-time Systems& Robotics Group 2000
[25]Ongoing Development of an Autonomous Aerial Reconnaissance System at Georgia Tech.Alison A.Proctor UAV Laboratory School of Aerospace Engineering Georgia Institute of Technology 2003
[26]Development of Autonomous Aerial Reconnaissance System.John M.Connelly,Scott M.Beecher,David L.Urlacher,School of Engineering and Engineering Technology LeToureau University 2004
[27]Autonomous Air Vehicle Implementation Into The 2004 International Aerial Robotics Competition Adam Felske,David Muncaster DeVry Institute of Technology Calgray Alberta 2004
[28]Design and Development of South Dakata School of Mines and Technology Aerial Robotic Reconnaissance System.Jason Howe,South Dakota School of Mines and Technology Unmanned Aerial Vehicle Team Rapid City,South Dakota 2003
[29]Rose-Hulman Institute of Technology Autonomous Helicopter for the 2004International Aerial Robotics Competition.2004
[30]A Network-Based Implementation of an Aerial Robotic System.University of waterloo Department of Electrical & Computer Engineering Waterloo Ontatrio,Canada 2004
[31]秦永元等《卡尔曼滤波与组合导航原理》[M].西安:西北工业大学出版社1998年.
[32]百宇俊.神经网络辅助卡尔曼滤波技术在组合导航系统中的应用研究[J].中国惯性技术学报2001(2)P40-P43.
[33]钱正祥.GPS/INS组合导航卡尔曼滤波技术[J].仪器仪表学报,2003(4):P533-P534.
[34]高宪军.GPS/INS组合导航系统的研究[J].光学精密工程,2004(2):P146-P150.
[35]许丽佳.GPS/INS组合导航系统中的信息融合算法研究[J].计算机仿真,2004(5):P20-P23.
[36]仲元昌.GPS/INS组合系统在飞船自主定位中的应用[J],重庆大学学报2002(7):P124-P127.
[37]彭霞.联邦卡尔曼滤波与集中式卡尔曼滤波的等价性[J].青岛科技大学学报2005(2):P169-P172
[38]刘海涛.低成本INS/GPS组合导航系统算法研究及其实现[J].遥测遥控,2003(3):P36-P41
[39]Chang-sun Yoo,Iee-ki Ahn.Low cost GPS/INS Sensor Fusion System For UAV Navigation[C].Digital Avionics Systems Conference,2003.DASC'03.The 22nd Volume 2,12-16 oct.2003 Page(s):8.A.1-8.1-9 vol.2.
[40]Chirstopher Hide,Terry Maritin Simith.Adaptive Kalman Filtering Algorithms for Integrating GPS and Low Cost INS[C].Position Location and Navigation Symposium,2004.PLANS 200426-29 April 2004 Page(s):227-233.
[41]X.Yun,E.R.Bachmann,R.B.Testing and Evaluation of an Integrated GPS/INS System for small AUV Navigation[C].IEEE Journal Of Oceanic Engineering,VOL,24,No,3,JULY 1999.
[42]Roy R.Minor,David W,Rowe.Utilization of GPS/MEMS-IMU for Measurement of Dynamics for Range Testing of Missiles and Rockets[C].Position Location and Navigation Symposium,IEEE 1998,20-23 April 1998 Page(s):602-607.
[43]Joerg s.Dittrich,Eric N.Jonhson.Multi-Sensor Navigation System for an Autonomous Helicopter[C].in Proceedings The 21st Digital Avionics Systems Conference,Volume 2,2002 Page(s):SCl-1-8C1-19 vol.2.
[44]Albert-Jan Baerveldt and Robert Klang.A Low-cost and Low-Weight Attitude Estimation System for an Autonomous Helicopter[C].in Proceedings of IEEE International Conference on Intelligent Engineering Systems,15-17 Sept.1997Page(s):391-395.
[45]Implementation and Experimental Results of a Quaternion-Based Kalman Filter for Human Body Motion Tracking[C].in Proceedings of the 2005 IEEE international Conference on Rbotics and Automation Barchelona,Spain,April 2005:P317-P322.
[46]Demoz Gebre-egzibher,Gabriel H.Elkain.A Gyro-Free Quaternion-Based Attitude Determination System Suitable for Implemantation Using Low Cost Sensors[C].in IEEE Position Location and Navigation Symposium,13-16 March 2000 Page(s):185-192.
[47]Billur Barshan and Hugh E Durrant-Whyte.Interial Navigation Systems for Mobile Robots[C],in IEEE TRANSCATIONS ON ROBOTICS AND AUTOMATIO -N,VOL,11 NO,3.,JUNE 1995:P328-P342.
[48]Attitude and Gyro Bias Estimation for a Flying UAV[C].2005 IEEE/RSJ International Conference on Intelligent Robots and Systems,2005.(IROS 2005).2-6 Aug.2005 Page(s):1114-1120.
[49]Tuan Manh Pham.Kalman filter mechanization for INS airstart[J].Aerospace and Electronic Systems Magazine,IEEE Volume 7,Issue 1,Jan.1992 Page(s):3-11
[50]Xianmin Ma,Youlin Gui.Extended Kalman Filter for Speed Sensor-less DTC Based on DSP[C].in Proceedings of the 4b World Congress on Intelligent Control and Automation,lune 10-14,2002,Shanghai,P.R.China:2002:p 119-p213.
[51]方崇智等《过程辨识》[M].北京:清华大学出版社,1988年8月.
[52]蔡金狮等《飞行器系统辨识》[M].北京:北京宇航出版社,1995年.
[53]刘叔军,盖晓华,樊京.《MATLAB7.控制系统应用与实例》[M].北京:机械工业出版社,2006.
[54]侯媛彬,汪梅,王立琦.《系统辨识以及MATLAB仿真》[M].北京:科学出版社,2004.
[55]王志贤.《最优状态估计与系统辨识》[M].西安:西安工业大学出版社,2004年.
[56]陈皓生.悬停状态下微型直升机航向模型的系统辨识 清华大学学报(自然科学版)2003年第43卷第2期P184-P187
[57]陈皓生.微型直升机动力学建模的研究现状 飞行力学 第21卷第3期2003年9月P1-P4.
[58]Sung K Kim Modeling,identification,and trajectory planning for a model-scale helicopter,A dissertation for degree of Doctor of Philosophy in The University of Michigan.
[59]Colin Rhys,Theodore Helicopter flight dynamics simulation with refined aerodynamic modeling A dissertation for degree of Doctor of Philosophy in The University of Maryland,College.
[60]Jaune Del Cerro,Julio Valero.Modeling and identification of a small unmanned helicopter[J].in Proceedings of World Automation Congress.Volume 15,28 Junel July 2004 Page(s):461-466.
[61]高金源.《飞机电传操作系统与主动控制技术》[M].北京:北京航天航空大学出版社,2005年.
[62]高正等.《直升机飞行动力学》[M].科学出版社,2003年.
[63]张明廉等.《飞控系统》[M].北京:北京航天工业出版社,1994年.
[64]刘哥群.《无人机飞行控制器设计以及检测与控制技术研究》[D].[硕士论文]西安:西北工业大学硕士论文,2004年.
[65]宋子善等.无人直升机综合飞控系统设计[J],北京航天航空大学学报,1999(3):P280-P283.
[66]郎平.一种改进的控制系统OFT设计算法[J],哈尔滨工业大学学报1997(4):P65-P71
[67]肖永利.定量反馈理论(QFT)及其设计应用[J],信息与控制1999(6):P437-P445.
[68]韦巍 定量反馈理论在鲁棒与容错飞控系统中的应用[J],南京航空航天大学学报2001(2):P130-P134.
[69]柴天佑.多变量自适应解耦控制及应用[M].北京:科学出版社,2001年.
[70]Xin Hou,Ping Li,Zhou Fang,Bo han.An Application of Fuzzy PID Alogrithm on Unmanned Helicopter Attitude Control[C].in Proceedings of the 6th World Congress on Intelligent Control and Automation,June 21-23,Dalian,china,P9129-P9133.
[71]曾丽兰,王道波,樊春霞.基于模糊PD的无人直升机解耦控制研究[J],应用科学学报,2004:P498-P502.
[72]曾丽兰,王道波,郭才根等.无人驾驶直升机飞行控制技术综述[J],控制与决策,2006:P361-P366.
[73]宋明山,蒋支运,吴文海.无人直升机飞控系统设计[J],飞机设计,2003:P67-P72.
[74]宋彦国,张呈林.直升机模糊飞控系统的现状与发展[J],直升机技术,2002(1):P41-P45.
[75]宋彦国,张呈林.直升机内回路姿态模糊控制[J],航空学报,2003(4):P365-P369.
[76]Edgar N.Sanchez,Hector M.Becerra,Carlos M.Velez.Combining fuzzy and PID control for an unmanned helicopter.in Annual Meeting of the North American Fuzzy Information Processing Society.2005:P235-P240.
[77]W.GHARIEB.Fuzzy Control To Multivariable Systems Case Study:Helicopter Meol[C].in Fuzzy Systems,1996.,Proceedings of the Fifth IEEE International Conference,1996:P400-P405.
[78]Carla Cavalcante,Janette Cardoso.Design and Tuning of a Helicopter Fuzzy Controller[C]Fuzzy Systems,International Joint Conference of the Fourth IEEE International Conference on Fuzzy Systems and The Second Proceedings of 1995 IEEE International Conference on International Fuzzy Engineering Symposium., , 1995:P1549-1553.
[79]Chun-Liang Lin. On the Design of an Adaptive Fuzzy Gain-Scheduled Autopilot[C]. in Proceedings of the American Control Conferece, Achorage, AK May 8-10, 2002:P1567-P1572.
[80]Dariusz Krol. Helicopter Intelligence in Hover Quality Improvement of the Fuzzy Regulator [C]. in proceedings of the Sixth international conference on Intelligent Systems Design and Applications, 2006:P120—P125.
[81]Dong-Ling Tsay, Hung-Yuan Chung, and Ching-Jung Lec. The Adaptive Control of Nonlinear Systems Using THE Sugeno-Type of Fuzzy Logic [J]. IEEE TRANSACTIONS ON FUZZY SYSTEMS, VOL. 7, NO. 2, APRIL 1999:P225-P229.
[82]Pil-Sang Yoon. Adaptive Fuzzy Control of Nonaffine Nonlinear Systems Using Takagi-Sugeno Fuzzy Models[C]. Fuzzy Systems, 2001. The 10th IEEE International Conference on Volume 2, 2-5 Dec. 2001 Page(s) :642 - 645 vol. 3
[83]J.-Y. Chen and C.-C. Wong. Implementation of the Takagi-Sugeno Model-based fuzzy control using an adaptive gain controller[J]. IEE Proc.-Control Theory Application,Vol 147, No. 5, September 2000:P509-P514.
[84]Gang Feng. A Survey on Analysis and Desgin of Model-Based Fuzzy Control Systems [J]. IEEE TRANSACTIONS ON FUZZY SYSTEMS, VOL. 14,NO. 5, OCTOBER 2006:P676-P697.
[85]DAI Jiyang, MAO Jianqin. Fuzzy Switching Control Law Design for Helicopters[C]. in Proceedings. 2002 IEEE Region 10 Conference on Computers, Communications, Control and Power Engineering Volume 3, 28-31 Oct. 2002 Page(s): 1634 - 1637 vol.3.
[86]I, Rojas, H. Pomares, C. G. Puntonet. On-line Apaptive Fuzzy Controller: Application to Helicopter Stabilization of the altitude of a helicopter [C]. in Internaltional Symposium on Computaional Intelligence for Measurements Systems and applications Lugano, Switzerland, 29-31 July 2003: P119-P123.
[87]T. John Koo and Shankar Sastry. Output Tracking Control Design of a Helicopter Model Based on Approximate Linearization [J]. Proceedings of the 37th IEEE Conference on Decision & Control Tampa, Florida USA December 1998:P3635-P3640.
[88] D. J. Wallcer, M. C. Turner, AJ. Smerlas. Robust Control of the Longitudinal and Lateral Dynamics of the BELL 205 Helicopter[J],Proceedings of the American Control Conference San Diego,California June 1999:P2742-P2746.
[89]I.Rojas,H.Pomares,F.J.Pelayo,M.Anguita,E.Ros.New methodology for the development of adaptive and self-learning fuzzy controllers in real time[C].International Journal of Approximate Reasoning 21(1999)109-136.
[90]H.Pomares *,I.Rojas,J.Gonz_alez,F.Rojas,M.Damns,A two-stage approach to self-learning direct fuzzy controllers[C].International Journal of approximate Reasoning 29(2002) 267-289.
[91]董绪荣等.《GPS/INS组合导航定位及其应用》[M].北京:国防工业出版社,1998年.
[92]王惠南.《GPS导航原理与应用》[M].北京:科学出版社,2003年.
[93]梁秋僮,程维明.超小型飞行器GPS自主导航算法的研究[J].无线电工程,2002(12):P27-P30.
[94]龚真春,宋执环,李平.超小型无人机GPS导航中的坐标转换[J].武器装备自动化,2005:P29-P30.
[95]王永生,李翔鹏.无人驾驶飞机GPS导航系统的设计与实现[J].西北工业大学学报,1996(3):P481-P484.
[96]吴蕾,王壬林.一类无人直升机的导航与控制[J].飞机设计2004(1):P60-P65.
[97]崔麦会,严德斌.GPS在无人机导航中的应用.现代防御技术.1999(3):P39-P40.
[98]王永林,黄一敏.虑侧风情况下的无人机自主导航控制技术研究[J].沈阳航空工业学院学报.2005(5):P7-P11.
[99]Ioannis K.Nikolos,Kimon P.Valavanis,Evolutionary Algorithm Based Offline/Online Path Planner for UAV Navigation[C].IEEE TRANSACTIONS ON SYSTEMS,MAN,AND CYBERNETICS—PART B:CYBERNETICS,VOL.33,NO.6,DECEMBER 2003:P898-P912.
[100]Guang Yang,Vikam kapila.Optimal Path Planning for Unmanned Air Vehicles with Kinematic and Tactical Constraints[C].in proceedings of the 41st IEEE Conference on Decision and Control Las Vegas,Navanda USA,December 2002:P1301-P1306
© 2004-2018 中国地质图书馆版权所有 京ICP备05064691号 京公网安备11010802017129号 地址：北京市海淀区学院路29号 邮编：100083 电话：办公室：(+86 10)66554848；文献借阅、咨询服务、科技查新：66554700 |