Development of small scale unmanned aerial vehicle helicopter systems

DEVELOPMENT OF SMALL-SCALE UNMANNED-AERIAL-VEHICLE HELICOPTER SYSTEMS CAI GUO WEI (B.Eng, Tianjin University, China) A THESIS SUBMITTED FOR THE DEGREE OF DOCTOR OF PHILOSOPHY DEPARTMENT OF ELECTRICAL & COMPUTER ENGINEERING NATIONAL UNIVERSITY OF SINGAPORE 2008 Acknowledgements First and foremost, I like to express my heartfelt gratitude to my supervisors, Professor Ben M. Chen and Professor T. H. Lee. I will never forget it is Professor Chen who gives me this precious opportunity to pursue my PhD degree and introduces me to the marvelous research area on small-scale UAV helicopters. To me, he is not only an advisor on research, but also a mentor on life. Professor Lee provides me numerous constructive suggestions and invaluable guidance during the course of my PhD study. Without their guidance and support, it would have not been possible for me to complete my PhD program. Special thanks are given to the friends and fellow classmates in our UAV research group in the Department of Electrical and Computer Engineering, National University of Singapore. Particularly, I wound like to thank Dr. Kemao Peng, Dr. Miaobo Dong, and my fellow classmates Feng Lin, Ben Yun, Xiangxu Dong and Xiaolian Zheng. Without their help and support, I would not be able to make our UAV helicopters fly. I am much grateful to Dr. K. Y. Lum of Temasek Laboratories, National University of Singapore, and Dr. Chang Chen of DSO National Laboratories, for their suggestions, generous help, and vast of knowledge in the field of research. I would also like to extend my sincere thanks to all of the friends in Control and Simulation Lab of the ECE Department, with whom I have enjoyed every minute during the last five years. I would like to give my special thanks to the lab officers, Mr. Hengwei Zhang and Ms. Sarasupathi for helping me process numerous purchasing issues, and to Dr. Kok Zuea Tang for patiently providing me technical support. Last but certainly not the least, I owe a debt of deepest gratitude to my parents and my wife for their everlasting love, care and encouragement. i Contents Acknowledgements i Contents ii Summary vi List of Tables viii List of Figures x Nomenclature xv Introduction 1.1 General Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.2 Technical Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.2.1 Platform Development and Construction . . . . . . . . . . . . . . . . . 1.2.2 Dynamic Modeling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.2.3 Control Law Design and Implementation . . . . . . . . . . . . . . . . 1.3 Small-scale UAV Helicopter Research in NUS . . . . . . . . . . . . . . . . . . 1.4 Outline of This Thesis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 ii CONTENTS iii Systematic Design Methodology for Platform Construction 2.1 2.2 2.3 Design Methodology and the Implementation on SheLion . . . . . . . . . . . 14 2.1.1 Virtual Design Environment Selection . . . . . . . . . . . . . . . . . . 14 2.1.2 Hardware Components Selection . . . . . . . . . . . . . . . . . . . . . 15 2.1.3 Comprehensive Design and Integration . . . . . . . . . . . . . . . . . . 25 2.1.4 Ground and Flight Test Evaluation . . . . . . . . . . . . . . . . . . . . 33 Methodology Implementation on Other UAV Helicopter Family Members . . 41 2.2.1 Virtual Design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42 2.2.2 Hardware Component Selection . . . . . . . . . . . . . . . . . . . . . . 43 2.2.3 Comprehensive Design and Integration . . . . . . . . . . . . . . . . . . 43 2.2.4 Experimental Evaluation . . . . . . . . . . . . . . . . . . . . . . . . . 45 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48 Software System Design and Implementation 3.1 3.2 3.4 50 Onboard Software System . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51 3.1.1 Framework of Onboard Software System . . . . . . . . . . . . . . . . . 51 3.1.2 Task Management . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53 3.1.3 Implementation of Automatic Control . . . . . . . . . . . . . . . . . . 58 Ground Station Software . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67 3.2.1 3.3 13 3D View Development . . . . . . . . . . . . . . . . . . . . . . . . . . . 73 Software Evaluation and Test Results . . . . . . . . . . . . . . . . . . . . . . 77 3.3.1 Evaluation of Working Load of the Software System . . . . . . . . . . 78 3.3.2 Reliability Improvement . . . . . . . . . . . . . . . . . . . . . . . . . . 79 3.3.3 Actual Flight Test . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 88 CONTENTS iv Dynamic Modeling 4.1 4.2 4.3 4.4 Time-domain System Identification Modeling . . . . . . . . . . . . . . . . . . 92 4.1.1 Data Collection and Preprocessing . . . . . . . . . . . . . . . . . . . . 92 4.1.2 Model Structure Determination . . . . . . . . . . . . . . . . . . . . . . 100 4.1.3 Unknown Parameter Identification . . . . . . . . . . . . . . . . . . . . 105 4.1.4 Model Validation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 106 Frequency-domain System Identification . . . . . . . . . . . . . . . . . . . . . 106 4.2.1 Data Collection and Preprocessing . . . . . . . . . . . . . . . . . . . . 110 4.2.2 Model Structure Determination . . . . . . . . . . . . . . . . . . . . . . 114 4.2.3 Unknown Parameter Identification . . . . . . . . . . . . . . . . . . . . 116 4.2.4 Model Validation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 118 First-principles Modeling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 118 4.3.1 Structure of the Nonlinear Model . . . . . . . . . . . . . . . . . . . . . 123 4.3.2 Parameter Identification . . . . . . . . . . . . . . . . . . . . . . . . . . 135 4.3.3 Model Validation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 145 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 148 Control Law Design and Implementation 5.1 91 154 Control Law Design Procedure . . . . . . . . . . . . . . . . . . . . . . . . . . 155 5.1.1 Inner-loop Control Law . . . . . . . . . . . . . . . . . . . . . . . . . . 155 5.1.2 Outer-loop Control Law . . . . . . . . . . . . . . . . . . . . . . . . . . 166 5.1.3 Flight Scheduling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 166 5.2 Simulation and Implementation Results . . . . . . . . . . . . . . . . . . . . . 168 5.3 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 169 CONTENTS v Conclusions 177 6.1 Contributions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 177 6.2 Future Works . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 179 Bibliography 181 Appendix: Publication List 190 Summary Unmanned aerial vehicle (UAV) helicopters have aroused great interest worldwide in the last several decades. Some unique features, such as fixed-point hovering, vertical takeoff and landing, flying at low altitude and highly agile maneuverability, make the UAV helicopter an ideal platform for both military and civil applications. Its unlimited potential in diverse practical implementations motivates our NUS UAV research team to carry out a comprehensive study and exploration on small-scale UAV helicopters from 2003. The overall procedure consists of four key stages, including: (1) UAV helicopter platform construction; (2) software system development; (3) dynamic modeling; and (4) control law design and implementation. The fundamental of the UAV helicopter research is building reliable platforms. During the last five years, we have constructed several small-scale UAV helicopters, which consist of our UAV helicopter family. One systematic and effective design methodology, for constructing the small-scale UAV helicopter platforms with minimum complexity and time cost, has been summarized. To ensure the overall UAV helicopter system work harmoniously, we have developed an efficient software system, which consists of two parts: (1) the onboard software system for performing multiple flight-control-related tasks such as hardware driving, device management, control algorithm execution, wireless communication and data logging; and (2) the ground station software system for receiving onboard information, sending commands to the onboard system, and monitoring the inflight status of the small-scale UAV helicopters. vi SUMMARY vii After the aforementioned two stages, our small-scale UAV helicopters can serve as the reliable platforms for various research purposes. We then move to the dynamic modeling stage, in which the reliable mathematic models with high fidelity are derived. Diverse dynamic modeling methods have been implemented. Specifically, we have applied the timedomain system identification method to our first-born UAV helicopter, namely HeLion, and derived the linearized models for a number of essential flight conditions. To obtain the linearized model in a more systematic and reliable way, we have further implemented the frequency-domain system identification method for the second-generation UAV helicopter called SheLion. Based on the achievements of linearized model identification, we have extended our research interest to the small-scale UAV helicopters’ aerodynamics in the full flight envelope. A minimum-complexity nonlinear model, which is universally compatible to our UAV helicopter family, has been derived and verified. With the identified models in hand, we proceed to the fourth stage: control law design and implementation. The main aim of this stage is to realize the automatic control of the small-scale UAV helicopters in the full flight envelope which consists of takeoff, landing, and other essential flight motions. It is achieved by implementing an advanced nonlinear flight control technique, named composite nonlinear feedback (CNF) control, associated with dynamic inversion technique and a carefully design flight scheduling. The efficiency and reliability of the flight control law have been successfully verified in actual flight tests. To conclude this work, we will summarize our research contributions and address some prospective research directions of small-scale UAV helicopters. List of Tables 2.1 Specifications of Raptor 90 helicopter . . . . . . . . . . . . . . . . . . . . . . . 19 2.2 Specifications of MNAV100CA . . . . . . . . . . . . . . . . . . . . . . . . . . 22 2.3 Selection of hardware components for SheLion . . . . . . . . . . . . . . . . . . 25 2.4 Power consumption list for SheLion UAV helicopter . . . . . . . . . . . . . . 31 2.5 Hardware configuration for HengLion and key specifications . . . . . . . . . . 43 2.6 Hardware configuration for BabyLion and key specifications . . . . . . . . . . 44 3.1 QNX Run-Time Functions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56 3.2 Control Components . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62 3.3 Behaviors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64 3.4 Actions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85 3.5 Events . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 88 4.1 Trim values for the tested flight conditions . . . . . . . . . . . . . . . . . . . . 99 4.2 Physical meanings of the state and input variables. . . . . . . . . . . . . . . . 101 4.3 Identified parameters of the linearized models of HeLion . . . . . . . . . . . . 107 4.4 Selected frequency slots (Hz) for SheLion’s hovering model identification . . . 115 4.5 Identified parameters with actuary analysis metrics . . . . . . . . . . . . . . . 120 viii LIST OF TABLES ix 4.6 Parameters identified by direct measurements . . . . . . . . . . . . . . . . . . 136 4.7 Parameters relative to CG location . . . . . . . . . . . . . . . . . . . . . . . . 136 4.8 Measured moment of inertia values . . . . . . . . . . . . . . . . . . . . . . . . 137 4.9 Parameters identified by main rotor flapping test . . . . . . . . . . . . . . . . 138 4.10 Parameters identified by servo actuator tests . . . . . . . . . . . . . . . . . . 138 4.11 Identification derivatives using CIFER . . . . . . . . . . . . . . . . . . . . . . 142 4.12 Parameters identified by flight tests . . . . . . . . . . . . . . . . . . . . . . . . 143 4.13 Lift curve slopes tuned by theoretical calculation . . . . . . . . . . . . . . . . 144 4.14 Parameters by empirical setting . . . . . . . . . . . . . . . . . . . . . . . . . . 144 Chapter Conclusions This research aims to carry out a comprehensive study on small-scale UAV helicopters. Specifically, we first build up the reliable small-scale UAV helicopters for practical experiments and implementations. Based on the specific hardware configuration on the UAV helicopter platforms, we are required to design an efficient software system to ensure the UAV helicopter to work stably. Next, we need to obtain the high-fidelity dynamic model which is essential for control law design, based on experimental method or theoretical derivation. Finally, we need to implement suitable flight control law to realize the automatic control of the small-scale UAV helicopters in the designated flight conditions or envelope. 6.1 Contributions The research work contributes towards the study on the small-scale UAV helicopter design in the following four aspects. First, we have summarized and proposed a comprehensive design methodology for the small-scale UAV helicopter platform construction. As mentioned in Chapter 2, building a small-scale UAV helicopter is generally challenging and labor/time-intensive. Since no 177 CHAPTER 6. 178 uniform, time-saving and effective design methodology can be found in the literature, researchers who tend to build a small-scale UAV helicopter are required to spend a lot of time for the literature survey and exploring the suitable construction-method. In our proposed methodology, we standardize the overall design procedure. Furthermore, we illustrate the qualitative requirements for hardware components selection based on the case of SheLion. With the guidance of the proposed methodology, the interested researchers could have reliable small-scale UAV helicopters ready in hand with minimum time and labor cost. Secondly, we have developed an uniform software system which is compatible for the members of our UAV helicopter family. For both the onboard and ground station parts, the software is highly modulized and can be easily (1) upgraded to a more advanced version and (2) ported to any other platform even including the fixed wing UAV or unmanned ground vehicle (UGV). Particularly for the onboard computer software, the design concepts on (1) general framework, (2) scheduling of task management and (3) behavior-based control algorithm implementation, are universal to any UAV/UGV onboard software design. Such feature enables any interested researcher could follow our design concepts, ideas and software structure to develop their own software systems for UAV/UGV research purpose. Thirdly, the modeling work for our small-scale UAV helicopters have been conducted comprehensively in Chapter 4. Three mainstream identification method, including timedomain system identification, frequency-domain system identification and first-principles modeling approach, have been implemented. Our successful experience ensures the interested researchers to choose any of the three methods to obtain the reliable dynamic model for their automatic control law design. The modeling procedure for system identification in both time- and frequency-domain has been unified and thoroughly introduced. As for the first-principles modeling approach, we propose an efficient and universal nonlinear structure with minimum complexity involved and then summarize a five-step aerodynamics-parameter estimation scheme which is well suited to small-scale UAV helicopter. Based on our proposed first-principles modeling procedure, interested researchers could derive the reliable CHAPTER 6. 179 dynamic model without conducting the challenging or dangerous flight experiments. Finally, for the flight control law design addressed in Chapter 5, we are the first group who has successfully implemented and verified the advanced CNF control law on the actual small-scale UAV helicopters. The control law structures, for all of the three hierarchical loops, have been standardized for easy reference and following. Our flight control law design is instrumental and could be further implemented by other researchers on their own custom-assembled UAV helicopters. To sum up, we have successfully carried out the comprehensive study on the small-scale UAV helicopters, based on our self-instrumented helicopter platforms. The overall research procedure and achievements have been sequentially documented in Chapter to 5. To any researchers who are starting or in the middle process of their UAV research, our experience is greatly instrumental. 6.2 Future Works Although we have carried out a comprehensive study on small-scale UAV helicopters, it is only the beginning of our UAV research. Considering the requirements on various practical implementations, it should be meaningful to extend the small-scale UAV research in the following directions. Formation Control on Multiple UAV Helicopters The research and study we have completed in the last five years solely focus on single smallscale UAV helicopter. Currently the practical flight missions are becoming more and more complicated. In many situations multiple UAV helicopters are required to cooperate with each other or, further, form a group to cooperate with other type of unmanned/manned vehicles to fulfill the tasks. As such, formation control for multiple UAV helicopters will definitely become a hot topic in the next stage. Currently our NUS research group is CHAPTER 6. 180 exploring the potential in this area via combining the achievements on single small-scale UAV helicopter and hybrid control algorithm. Urban Area Implementation Urban area is generally with limited space, complicated environment, and various uncertainties. As such, small-scale UAV helicopter is the most suitable platform for the surveillance purpose. To facilitate the implementation in this aspect, we need to combine the current small-scale UAV helicopters with the research results in other regions such as visual-based navigation and obstacle-avoidance. Indoor Implementation Indoor implementation for small-scale UAV helicopters is with great potential but still at the very initial stage due to the lack of reliable platform and efficient localization sensor and algorithm in the capsuled environment without GPS reference signal. Currently the whole NUS UAV research team is undergoing the challenging development of the qualified and suitable micro-aerial-vehicle (MAV) helicopter platforms and practical navigation methodologies for indoor navigation and further practical implementations. Bibliography [1] AutoCopter Express, url: http://www.neural-robotics.com/Products/Express.html, 2008. [2] AutoCopter gunship project, url: http://www.defensereview.com/article846.html, 2008. [3] J. S. Bendat, A. G. Piersol, Random Data: Analysis and Measurement Procedures, 2nd ed., Wiley, New York, 1986. [4] Bogdanov A. and E. Wan, “SDRE control with nonlinear feed forward compensation for a small unmanned helicopter,” Proceedings of the 2nd AIAA Unmanned Unlimited Systems, Technologies, and Operations Conference, San Diego, CA, AIAA Paper Number: 2003-6512, 2003. [5] A. R. S. Bramwell, Brawell’s Helicopter Dynamics, AIAA, Reston, VA, 2001. [6] G. Cai, A. K. Cai, B. M. Chen and T. H. Lee, “Construction, modeling and control of a mini autonomous UAV helicopter,” Proceedings of the IEEE International Conference on Automation and Logistics, Qingdao, China, September 2008. [7] G. Cai, B. M. Chen, T. H. Lee and M. Dong, “Design and implementation of a hardware-in-the-loop simulation system for small-scale UAV helicopters,” Proceedings of the IEEE International Conference on Automation and Logistics, Qingdao, China, September 2008. 181 BIBLIOGRAPHY 182 [8] G. Cai, B. M. Chen, T. H. Lee and K. Y. Lum, “Comprehensive nonlinear modeling of an unmanned-aerial-vehicle helicopter,” Proceedings of the AIAA Guidance, Navigation, and Control Conference and Exhibit, AIAA-2008-7414, Hawaii, USA, August 2008. [9] G. Cai, B. M. Chen, K. Peng, M. Dong and T. H. Lee, “Modeling and control of the yaw channel of a UAV helicopter,” IEEE Transactions on Industrial Electronics, Vol. 55, No. 9, pp. 3426-3434, September 2008. [10] G. Cai, B. M. Chen, K. Peng, M. Dong and T. H. Lee, “Modeling and control system design for a UAV helicopter,” Proceedings of the 14th Mediterranean Conference on Control and Automation, pp. 600-606, Ancona, Italy, 2006. [11] G. Cai, F. Lin, B. M. Chen and T. H. Lee, “Systematic design methodology and construction of UAV helicopters,” Mechatronics, Vol. 18, No. 10, pp. 545-558, December 2008. [12] G. Cai, K. Peng, B. M. Chen and T. H. Lee, “Design and assembling of a UAV helicopter system,” Proceedings of the 5th International Conference on Control and Automation, pp. 697-702, Budapest, Hungary, 2005. [13] B. M. Chen, T. H. Lee, K. Peng, and V. Venkataramanan, “Composite nonlinear feedback control for linear systems with input saturation: theory and an application,” IEEE Transaction on Automatic Control, Vol. 48, No. 3, pp. 427–439, 2003. [14] B. M. Chen, T. H. Lee, and V. Venkataramanan, Hard Disk Drive Servo Systems, Springer-Verlag, New York, 2002. [15] R. P. Cheng, M. B. Tischler and G. J. Schulein, “R-MAX helicopter state-space model identification for hover and forward-flight”, Journal of American Helicopter Society, Vol. 51, No. 2, pp. 202-210, 2006. BIBLIOGRAPHY 183 [16] M. L. Civita, W. Messner and T. Kanade, “Modeling of small-scale helicopters with integrated first-principles and integrated system identification techniques”, Presented at 58th Forum of American Helicopter Society, Montreal, Canada, 2002. [17] M. L. Civita, G. Papageorgiou, W. C. Messner and T. Kanade, “Integrated modeling and robust control for full-envelope flight of robotic helicopters,” Proceedings of the 2003 IEEE International Conference on Robotics and Automation, Vol. 1, pp. 552-557, Taipei, Taiwan, September 2003. [18] A. Conway, “Autonomous control of an Unstable helicopter using carrier phase GPS only,” Ph.D. thesis, Stanford University, 1994. [19] M. Dong, B. M. Chen, G. Cai and K. Peng, “Development of a real-time onboard and ground station software system for a UAV helicopter,” Journal of Aerospace Computing, Information, and Communication, Vol. 4, No. 8, pp. 933-955, 2007. [20] M. Dong and Z. Sun, “A behavior-based architecture for unmanned aerial vehicles,” Proceedings of International Symposium on Intelligent Control, pp. 149-155, Taipei, Taiwan, 2004. [21] R. Enns, and J. Si, “Helicopter flight control design using a learning control approach,” Proceedings of the 39th IEEE Conference on Decision and Control, pp. 1754-1759, Sydney, Australia, 2000. [22] R. Enns, and J. Si, “Helicopter trimming and tracking control using direct neural dynamic programming,” IEEE Transactions on Neural Networks, Vol. 14, pp. 929-939, 2003. [23] A. H. Fagg, M. A. Lewis, J. F. Montgomery, and G. A. Bekey, “The USC autonomous flying vehicle - an experiment in real-time behavior-based control,” Proceedings of the 1993 IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 1173-1180, Yokohama, Japan, 1993. BIBLIOGRAPHY 184 [24] Flying-Cam helicopter, url: http://www.flying-cam.com/products.php, 2007. [25] V. Gavrilets, I. Martinos, B. Mettler and E. Feron, “Aggressive maneuvering of small autonomous helicopters: a human-centered approach”, International Journal of Robotics Research, pp. 795-807, October 2001. [26] V. Gavrilets, B. M. Mettler, and E. Feron, “Nonlinear model for a small-size acrobatic helicopter,” Presented at the AIAA Guidance, Navigation, and Control Conference and Exhibit, Montreal, Canada, 2001. [27] P. E. Gill, W. Murray, and R. A. Pitfield, “The implementation of two revised quasinewton algorithms for unconstrained optimization,” National Physical Lab., Div. of Numerical Analysis and Computing, NPL-NAC-11, Middlesex, UK, August 1972. [28] U. B. Hald, M. V. Hesselbek, and M. Siegumfeldt, Nonlinear Modeling and Optimal Control of a Miniature Autonomous Helicopter, Master Thesis, 2006. [29] J. A. Ham, C. K. Gardner and M. B. Tischler, “Flight-testing and frequency-domain analysis for rotorcraft handling qualities”, Journal of the American Helicopter Society, 1995. [30] C. Harris, Shock and Vibration Handbook (edited), McGraw-Hill, New York, 1996. [31] F. D. Harris, “Articulated rotor blade flapping motion at low advance ratio”, Journal of American Helicopter Society, January, 1972. [32] Y. He, B. M. Chen, and C. Wu, “Composite nonlinear control with state and measurement feedback for general multivariable systems with input saturation,” Systems and Control Letters, Vol. 54, No. 5, pp. 455–469, 2005. [33] R. K. Heffley and M. A. Mnich, “Minimum-complexity simulation math model”, Prepared for Aeroflightdynamics Directorate U.S. Army Research and Technology, California, 1988. BIBLIOGRAPHY 185 [34] HORNET UAS, url: www.adaptiveflight.com/docs/AF Hornet 4.pdf, 2008. [35] A. Isidori, L. Marconi and A. Serrani, “Robust nonlinear motion control of a helicopter,” IEEE Transactions on Automatic Control, vol. 48, issue 3, pp. 413-426, 2003. [36] J. S. Jang and D. Liccardo, “Small UAV automation using MEMS”, Aerospace and Electronic Systems Magazine, IEEE, Vol 22, Issue 5, pp. 30-34, 2007. [37] B. Kadmiry, “Fuzzy control for an autonomous helicopter,” Thesis No. 938 for the degree of Licenciate of Engineering, Linkoping, Sweden, May 2002. [38] S. K. Kim and D. M. Tilbury, “Mathematical modeling and experimental identification of an unmanned helicopter robot with flybar dynamics”, Journal of Robotic Systems, No. 3, Vol. 21, pp. 95-116, 2004. [39] T. J. Koo and S. Sastry, “Output tracking control design of a helicopter model based on approximate linearization,” Proceedings of the 37th IEEE Conference on Decision and Control, Tampa, FL, 1998. [40] R. Krten, Getting Started with QNX Neutrino - A Guide for Real-time Programmers, PARSE Software Devices, Kanata Ontario, 1999. [41] D. J. Kruglinski, Inside Visual C++ (4th edition), Microsoft Press, Redmond, Washington, 1995. [42] J. G. Leishman, Principles of Helicopter Aerodynamics, 2nd edition, Cambridge University Press, 2006. [43] Z. Lin, M. Pachter and S. Banda, “Toward improvement of tracking performance Nonlinear feedback for linear system,” International Journal of Control, Vol. 70, pp. 1-11, 1998. [44] L. Ljung, System Identification: Theory for the User, Prentice Hall, 2002. BIBLIOGRAPHY 186 [45] A. D. Mali, “On the behavior-based architectures of autonomous agency,” IEEE Transactions on Systems, Man and Cybernetics, Vol. 32, No. 3, pp. 231–242, 2002. [46] L. Mak et. al, “Design and development of the micro aerial vehicles for search, tracking and reconnaissance (MAVSTAR) for MAV08,” 1st US-Asian Demonstration and Assessment of Micro-aerial and Unmanned Ground Vehicle Technology (MAV08), Agra, India, March 2008. [47] B. Mettler, Identification, Modeling and Characteristics of Miniature Rotorcraft, Kluver Academic Publishers, Boston, MA, 2002. [48] B. M. Mettler, M. B. Tischler, and T. Kanade, “System identification of small-size unmanned helicopter dynamics”, Presented at the American Helicopter Society 55th Forum, May, 1999. [49] B. M. Mettler, M. B. Tischler and T. Kanade, “System identification modeling of a small-scale unmanned rotorcraft for control design”, Journal of the American Helicopter Society, No. 47, Vol. 1, pp. 50-63, 2002. [50] B. Mettler, M. B. Tischler, and W. Messner, “Attitude control optimization for a smallscale unmanned helicopter,” Proceedings of AIAA Guidance, Navigation and Control Conference, Denver, Colorado, 2000. [51] J. C. Morris, M. Nieuwstadt, and P. Bendotti, “Identification and control of a model helicopter in hover,” Proceedings of the American Control Conference, pp. 1238-1242, Baltimore, Maryland, USA, June 1994. [52] M. Musial, U. W. Brandenburg and G. Hommel, “Inexpensive system design: The flying robot MARVIN,” Proceedings of the 16th International UAVs Conference on Unmanned Air Vehicle Systems, pp 23.1C23.12, Bristol, UK, 2001. [53] NAV420 Series User’s Manual, Crossbow Technology Inc., 2004. BIBLIOGRAPHY 187 [54] G. D. Padfield, Helicopter Flight Dynamics: The Theory and Application of Flying Qualities and Simulation Modeling, AIAA Education Series, Reston, VA, 1996. [55] K. Peng, G. Cai, B. M. Chen, M. Dong, K. Y. Lum, and T. H. Lee, “Design and implementation of an autonomous flight control law for a UAV Helicopter,” Journal of Automatica, provisionally accepted, August 2008. [56] K. Peng, M. Dong, B. M. Chen, G. Cai, K. Y. Lum and T. H. Lee, “Design and implementation of a fully autonomous flight control system for a UAV helicopter,” Proceedings of the 26th Chinese Control Conference, Vol. 6, pp. 662-667, Zhangjiajie, Hunan, China, July 2007. [57] J. V. R. Prasad, A. J. Calise and J. E. Corban, “Implementation of adaptive nonlinear controller for flight test on an unmanned helicopter,” Proceedings of the 37th IEEE Conference on Decision and Control, Tampa, FL, 1998. [58] QNX Momentics (v6.3 SP2) Documentation, QNX Software Systems Corporation, available: http://www.qnx.com/developers/docs/index.html, 2008. [59] M. Scheutz, and V. Andronache, “Architectural mechanisms for dynamic changes of behavior selection strategies in behavior-based systems,” IEEE Transactions on Systems, Man and Cybernetics - Part B: Cybernetics, Vol. 34, No. 6, pp. 2377–2395, 2004. [60] D. H. Shim, H. J. Kim and S. Sastry, “Control system design for rotorcraft-based unmanned aerial vehicle using time-domain system identification,” Proceedings of the 2000 IEEE Conference on Control Applications, pp. 808-813, Anchorage, Alaska, USA, 2000. [61] D. H. Shim, H. J. Kim, and S. Sastry, “Decentralized nonlinear model predictive control of multiple flying robots,” Proceedings of the 42nd IEEE Conference on Decision and Control, vol. 4, pp. 3621-3626, Maui, Hawaii, USA, 2003. BIBLIOGRAPHY 188 [62] J. Shin, K. Nonami, D. Fujiwara and K. Hazawa, “Model-based optimal attitude and positioning control of small-scale unmanned helicopter”, Journal of Robotica, Vol. 23, pp. 51-63, 2005. [63] D. Shreiner, OpenGL Reference Manual, Addison-Wesley, Boston, 1992. [64] D. Shreiner, M. Woo, J. Neider and T. Davis, OpenGL Programming Guide, AddisonWesley, Boston, 1997. [65] SR200 UAV helicopter, url: http://www.rotomotion.com/ prd UAV SR200.html, 2008. [66] M. Sugeno, I. Hirano, S. Nakamura, S. Kotsu, “Development of an intelligent unmanned helicopter,” Proceedings of 1995 IEEE International Conference on Fuzzy Systems, pp. 33-34, Yokohama, Japan, 1995. [67] M. B. Tischler, J. W. Fletcher, V. L. Diekmann, R. A. Williams and R. W. Cason, “Demonstration of frequency-sweep test technique using a Bell-214-ST helicopter,” NASA TM 89422, ARMY TM 87-A-1, April 1987. [68] M. B. Tischler and M. G. Cauffman, “Frequency-response method for rotorcraft system identification: flight application of BO-105 coupled rotor/fuselage dynamics”, Journal of the American Helicopter Society, pp. 3-17, 1992. [69] M. B. Tischler and R. K. Remple, Aircraft and Rotorcraft System Identification – Engineering Methods with Flight Test Examples, AIAA Educational Series, AIAA, Reston, VA, 2006. [70] E. A. Wan and A. A. Bogdanov, “Model predictive neural control with applications to a DOF helicopter model,” Proceedings of the 2001 American Control Conference, pp. 488-493, Arlington, Virginia, USA, 2001. BIBLIOGRAPHY 189 [71] M. W. Weilenmann, U. Christen and H. P. Geering, “Robust helicopter position control at hover,” Proceedings of American Control Conference, pp. 2491-2495, Baltimore, MD, June-July 1994. [72] M. W. Weilenmann and H. P. Geering, “A test bench for the rotorcraft hover control,” Proceedings of AIAA Guidance Navigation and Control Conference, Monterey, CA, 1993. [73] Yamaha RMAX helicopter, url: http://www.yamaha-motor.co.jp/global/industrial/ sky/solution/rmax/index.html, 2005. [74] B. Yun, K. Peng, B. M. Chen, “Enhancement of GPS signals for automatic control of a UAV helicopter system,” Proceedings of IEEE International Conference on Control and Automation, pp. 1185-1189, Guangzhou, China, 2007. Published/Submitted Papers Refereed Journal Articles: 1. G. Cai, B. M. Chen, K. Peng, M. Dong and T. H. Lee, “Design and implementation of a nonlinear flight control law for the yaw channel of a UAV helicopter,” IEEE Transactions on Control Systems Technology, Vol. 55, No. 9, pp. 34263434, September 2008. 2. G. Cai, B. M. Chen, M. Dong and T. H. Lee, “Design and implementation of a hardware-in-the-loop simulation system for small-scale UAV helicopters,” provisionally accepted for publication in Special Issue on Hardware-in-the-loop Simulation: Theory, Practice and Future Developments, Mechatronics. 3. G. Cai, F. Lin, B. M. Chen and T. H. Lee, “Systematic design methodology and construction of UAV helicopters,” Mechatronics, Vol. 18, No. 10, pp. 545-558, December 2008. 4. M. Dong, B. M. Chen, G. Cai and K. Peng, “Development of a real-time onboard and ground station software system for a UAV helicopter,” Journal of Aerospace Computing, Information, and Communication, Vol. 4, No. 8, pp. 933-955, August 2007. 190 APPENDIX: PUBLICATION LIST 191 5. K. Peng, G. Cai, B. M. Chen, M. Dong, K. Y. Lum, and T. H. Lee, “Design and Implementation of an Autonomous Flight Control Law for a UAV Helicopter,” provisionally accepted for publication in Automatica. International Conference Articles: 1. G. Cai, A. K. Cai, B. M. Chen and T. H. Lee, “Construction, modeling and control of a mini autonomous UAV helicopter,” Proceedings of the IEEE International Conference on Automation and Logistics, Qingdao, China, pp. 449-454, September 2008. 2. G. Cai, B. M. Chen, T. H. Lee and M. Dong, “Design and implementation of a hardware-in-the-loop simulation system for small-scale UAV helicopters,” Proceedings of the IEEE International Conference on Automation and Logistics, Qingdao, China, pp. 29-34, September 2008. 3. G. Cai, B. M. Chen, T. H. Lee, and K. Y. Lum, “Comprehensive nonlinear modeling of an unmanned-aerial-vehicle helicopter,” Proceedings of the AIAA Guidance, Navigation, and Control Conference and Exhibit, AIAA-2008-7414, Hawaii, USA, August 2008. 4. G. Cai, B. M. Chen, K. Peng, M. Dong and T. H. Lee, “Design and implementation of a nonlinear flight control law for the yaw channel of a UAV helicopter,” Proceedings of the 46th IEEE Conference on Decision and Control, New Orleans, Louisiana, USA, pp. 1963-1968, December 2007. 5. G. Cai, B. M. Chen, K. Peng, M. Dong and T. H. Lee, “Modeling and control system design for a UAV helicopter,” Proceedings of the 14th Mediterranean Conference on Control and Automation, Ancona, Italy, pp. 1-6, June 2006. APPENDIX: PUBLICATION LIST 192 6. G. Cai, K. Peng, B. M. Chen and T. H. Lee, “Design and assembling of a UAV helicopter system,” Proceedings of the 5th International Conference on Control and Automation, Budapest, Hungary, pp. 697-702, June 2005. 7. K. Peng, G. Cai, B. M. Chen, M. Dong and T. H. Lee, “Comprehensive modeling and control of the yaw dynamics of a UAV helicopter,” Proceedings of the 25th Chinese Control Conference, Harbin, China, pp. 2087-2092, August 2006. 8. K. Peng, M. Dong, B. M. Chen, G. Cai, K. Y. Lum and T. H. Lee, “Design and implementation of a fully autonomous flight control system for a UAV helicopter,” Proceedings of the 26th Chinese Control Conference, Zhangjiajie, Hunan, China, Volume 6, pp. 662-667, July 2007. [...]... the final goal of controlling small- scale UAV helicopter: fully autonomy with the human-intelligence level CHAPTER 1 1.3 9 Small- scale UAV Helicopter Research in NUS The research on small- scale UAV helicopters in National University of Singapore (NUS) has started from year 2003 During the last five years, our NUS UAV research team has successfully constructed multiple small- scale UAV helicopters, developed... small- scale UAV helicopters Thirdly, the design and implementation of the automatic flight control law for the small- scale UAV helicopters are addressed CHAPTER 1 1.2.1 3 Platform Development and Construction During the last decade the small- scale UAV helicopters have experienced a rapid development Many research institutes, universities and companies have designed and constructed their own small- scale. .. its full -scale counterpart, small- scale UAV helicopter has the following three extra advantages: 1 The cost for building a small- scale UAV helicopter is very low (generally less than 50,000 USD) The maintenance fee is also much lower than that for a full -scale UAV helicopter 2 Small- scale UAV helicopter provides much more agility and maneuverability in the practical applications due to its small size... achieved, the development and application of UAV helicopters are still at their initial stage The unlimited potential of UAV helicopters is still waiting for people to explore In recent years the rapid development in manufacturing technology and martial science makes the processing units and sensors much smaller, lighter, and cheaper than before As such, the development of small- scale UAV helicopters... aerodynamics 3 The small- scale UAV helicopter is easier to assemble, transport, maintain and repair As such, small- scale UAV helicopters have been a hot topic within the last one to two decades in both academic circle and industry area In what follows of this chapter, we first provide a brief technical background of the small- scale UAV helicopter in Section 1.2 In Section 1.3, a general overview of the work... is initially not recommended for the nonlinear model derivation of the small- scale UAV helicopters In recent five to ten years, the aerodynamics of the full flight envelope for the small- scale CHAPTER 1 7 UAV helicopter has become one key research focus One high-fidelity nonlinear model which could comprehensively cover the small- scale UAV helicopter s dynamics in the full flight envelope is greatly instrumental... (3) processor/sensor unit selection; and (4) vibration isolation Note that the development of this type of UAV helicopter is still at its very initial stage As such, only a few successful examples (see, e.g., [46, 34]) can be found in the literature 1.2.2 Dynamic Modeling Throughout the overall development of small- scale UAV helicopters, deriving the linear and nonlinear dynamic models which could accurately... of Singapore PEM prediction error method RC radio-controlled RPM rotations per minute SISO single-input/single output TPP tip-path-plane UAV unmanned aerial vehicle 2D two-dimensional 3D three-dimensional xxiv Chapter 1 Introduction 1.1 General Overview Unmanned aerial vehicle (UAV) helicopters have aroused great interest worldwide in the last two to three decades Compared with fixed-wing UAV, UAV helicopter. .. is extremely difficult or even impractical As such, a number of research groups have started developing suitable nonlinear models based on their self-constructed small- scale UAV helicopters For instance, in [26], a seventeen-state nonlinear model is derived for their constructed X-Cell60 small- scale unmanned helicopter However, the accuracy of partial measured/estimated key aerodynamic parameters can... small- scale UAV helicopters In general, any small- scale UAV helicopter can be regarded as a small- size rotorcraft equipped with an integrated onboard computer system However, considering the specific requirements on the flight missions, each small- scale UAV helicopter has its own uniqueness Based on three key performance indices including: (1) flight time; (2) overall payload; and (3) difficulty of the onboard-system . DEVELOPMENT OF SMALL- SCALE UNMANNED- AERIAL- VEHICLE HELICOPTER SYSTEMS CAI GUO WEI (B.Eng, Tianjin University, China) A THESIS SUBMITTED FOR THE DEGREE OF DOCTOR OF PHILOSOPHY DEPARTMENT OF. research directions of small- scale UAV helicopters. List of Tables 2.1 Specifications of Raptor 90 helicopter . . . . . . . . . . . . . . . . . . . . . . . 19 2.2 Specifications of MNAV100CA . . fundamental of the UAV helicopter research is building reliable platforms. During the last five years, we have constructed several small- scale UAV helicopters, which consist of our UAV helicopter