(3.236.222.124) 您好!臺灣時間:2021/05/13 02:01
字體大小: 字級放大   字級縮小   預設字形  
回查詢結果

詳目顯示:::

我願授權國圖
: 
twitterline
研究生:柯昆緯
研究生(外文):Kun-wei Ko
論文名稱:以小腦模型估測PID控制器參數及其無人直升機失速之穩定降落應用
論文名稱(外文):CMAC-BASED PID CONTROLLER FOR CONTROL OF POWERLESS UNMANNED HELICOPTER STABLE LANDING
指導教授:呂虹慶
指導教授(外文):Hung-Ching Lu
口試委員:呂虹慶
口試委員(外文):Hung-Ching Lu
口試日期:2013-07-31
學位類別:碩士
校院名稱:大同大學
系所名稱:電機工程學系(所)
學門:工程學門
學類:電資工程學類
論文種類:學術論文
論文出版年:2013
畢業學年度:102
語文別:英文
論文頁數:72
中文關鍵詞:小腦模型控制器差分-積分-微分控制器自轉李亞普諾夫
外文關鍵詞:PIDAutorotationLyapunovCMAC
相關次數:
  • 被引用被引用:1
  • 點閱點閱:125
  • 評分評分:系統版面圖檔系統版面圖檔系統版面圖檔系統版面圖檔系統版面圖檔
  • 下載下載:0
  • 收藏至我的研究室書目清單書目收藏:0
本篇論文提出具有強健控制器之自我調變小腦模型控制器的差分-積分-微分控制器來控制自主垂直自轉的無人直升機以保證地面人員的安全。所提出的控制器透過改變主轉子來完成控制無人直升機的下降速度。由於差分-積分-微分控制器的參數很難去定義,因此加入小腦模型控制器來解決。然而,不同狀態下的動態會對應到不同差分-積分-微分控制器的參數。基於小腦模型控制器的差分-積分-微分控制器應用在調整差分-積分-微分參數以處裡不同情況下的動態。 此方法將使小腦模型的差分-積分-微分控制器擁有自我調整的能力。而所提出的方法將使任何直升機狀態下花上少許的時間來到所設定的目標速度。三個一維的小腦模型控制器以及強健控制器將運用在此研究上。此控制器的穩定度藉由李亞普諾夫方法來證明。模擬結果可證明所提出的控制器是有效的。
This thesis propose a self-tuning cerebellar model articulation controller based proportional-integral-derivative (CMAC-PID) controller with a robust controller to realize the autonomous vertical autorotation control for a unmanned helicopter to guarantee the security of ground staff. The proposed controller can control the sink rate of the unmanned helicopter by adjusting the main rotor’s pitch. However, the parameters of the PID controllers are difficult to be determined and the fixed parameters of the PID controller are not suitable for all conditions of the system’s dynamic. The PID controller based on the CMAC estimator is applied to solve the problem. This arrangement would lead the CMAC-PID controller has the ability of self-tuning. The present control technique can use less time for reaching the target speed in any helicopter states. Three one-dimension CMAC estimators and a robust controller are adopted in the thesis. By utilizing the Lyapunov theory, the stability of the proposed controller can be guaranteed. The simulation result is implemented to demonstrate the effectiveness of the proposed controller.
ACKNOWLEDGEMENTS i
ABSTRACT (IN ENGLISH) ii
ABSTRACT (IN CHINESE) iii
CONTENTS iv
LIST OF TABLES vi
LIST OF FIGURES vii
LIST OF SYMBOLS ix
CHAPTER
1 Introduction 1
2 Hardware 5
2.1 Unmanned Aerial Helicopter 6
2.2 ArduPilot-Mega 2.5 8
2.3 3DR radio 9
2.4 others 10
2.5 Mission Planner 11
3 PID and CMAC Neural Network 12
3.1 PID Controller 12
3.2 basic CMAC 13
3.3 One-Dimensional CMAC 14
4 Controller Design 19
4.1 Controller design 20
4.2 Stability Theorem 22
5 Simulation Result 26
5.1 Vertical Autorotation Model 26
5.2 Simulation result 30
6 Experiment 49
7 Conclusions 55
REFERENCES 56
[1] V.J. Gawron, Human factors issues in the development, evaluation, and operation of uninhabited aerial vehicles. AUVSI 98, Alabama, 1998, pp. 431-438.
[2] D.A. Wiegmann and S.A. Shappell, A human error approach to aviation accident analysis: the human factors analysis and classification system, England, Ashgate publishing company, 2003.
[3] S. A. Shappell and D. A. Wiegmann, “Human factors analysis and classification system - HFACS.” Department of Transportation, Federal Administration: Washington, DC. DOT/FAA/AM-00/7, Feb. 2000, pp 1-15.
[4] Department of Defense, “Unmanned aerial vehicles roadmap,” 2000-2025, Office of the Secretary of Defense, Department of Defense, Washington, DC, April 2001, pp 3-12.
[5] Department of Defense, “Unmanned aerial vehicle reliability study,” Office of the Secretary of Defense, Washington, DC, Feb. 2003, pp 1-21.
[6] A. P. Tvaryanas, “USAF UAV mishap epidemiology”, 1997-2003, Human Factors of Uninhabited Aerial Vehicles First Annual Workshop, Phoenix, Arizona, May 2004
[7] J. G. Leishman, Principles of helicopter aerodynamics, The press syndicate of the university of Cambridge, England, 2000.
[8] K. Dalamagkidis, K. P. Valavanis, and L. A. Piegl, “Nonlinear model predictive control with neural network optimization for autonomous autorotation of small unmanned helicopters,” IEEE Trans. Control Syst. Techn., vol. 19, no. 4, pp 818-831, JULY 2011.
[9] F. C. Chen and C. H. Chang, “Practical stability issues in CMAC neural network control system,” IEEE Trans. Control Syst. Techn., vol. 4, no. 1, pp. 86-91, Sep. 1996.
[10] J. S. Albus, “Data storage in the cerebellar model articulation controller (CMAC),” J. Dyn. Syst. Meas. Control, Trans. ASME vol. 97, no. 3,pp. 228-233, June 1975.
[11] J. S. Albus, “A new approach to manipulator control: The cerebellar model articulation controller (CMAC),” J. Dyn. Syst. Meas. Control, Trans. ASME, vol. 97, pp. 220-227, 1975.
[12] H. C. Lu, J. C. Chang, and M. F. Yeh, “Design and analysis of direct-action CMAC PID controller,” Neurocomputing, vol. 70, no 16-18, pp. 2615-2625, Oct. 2007.
[13] R. J. Wai, C.M. Lin, and Y. F. Peng, “ Robust CMAC neural network control for LLCC resonant driving linear piezoelectric ceramic motor,” IEE Proc. Control Theory Appl., vol. 150, no. 3, pp. 221-232, May 2003.
[14] Y. F. Peng, R. J. Wai, and C.M. Lin, “Implementation of LLCC-resonant driving circuit and adaptive CMAC neural network control for linear piezoelectric ceramic motor,” IEE Trans. Ind. Electron., vol. 50, no. 1, pp. 35-48, Feb. 2004.
[15] S. H. Lane, D. A. Handelman, and J. J. Gelfand, “Theory and development of higher-order CMAC neural networks,” IEE Control Syst. Mag., vol. 12, no. 2, pp. 23-30, Apr. 1992.
[16] T. F. Wu, P. S. Tsai, F. R. Chang, and L.S. Wang, ”Adaptive fuzzy CMAC control for a class of nonlinear systems with smooth compensation,” IEE Proc. Control Theory Appl., vol. 153, no. 6, pp. 647-657, Nov 2006.
[17] H. C. Lu, J. C. Chang, and M. F. Yeh, “Design of a hybrid adaptive CMAC with supervisory controller for a class of nonlinear system,” Neurocomputing, vol. 72, no. 7-9, pp. 1920-1933, Mar. 2009.
[18] D. A. Handelman, S. H. Lane, and J. J. Gelfand, “Integrating neural networks and knowledge-based systems for intelligent robotic control,” IEEE Control Syst. Mag., vol. 10, no. 3, pp. 77-87, Apr. 1990.
[19] F. H. Glanz and W. T. Miller, “Deconvolution and nonlinear inverse filtering using a neural network,” IEEE Int. Symp. Intell. Control, vol. 4, Glasgow, UK, pp. 2349-2352, May 1989.
[20] Y. Iiguni, “Hierarchical image coding via cerebellar model arithmetic computers,” IEEE Trans. Image Processing, vol. 5, no. 10, pp. 1393-1401, Oct. 1996.
[21] H. Shiraishi, S. L. Ipri, and Dong-il D. Cho, “CMAC neural network controller for fuel-injection systems,” IEEE Trans. Control Syst. Techn., vol. 3, no. 1, pp. 32-38, Mar. 1995.
[22] John Y. Hung, Weibing Gao, and W. P. Hung, “Variable structure control: a survey,” IEEE Trans. Ind. Electron., vol. 40, no. 1, pp. 2-22, Feb. 1993.
[23] H. Hu and P. Y. Woo, “Fuzzy supervisory sliding-mode and neural-network control for robotic manipulators,” IEEE Trans. Ind. Electron., vol. 53, no. 3, pp. 929-940, June 2006.
[24] J. J. E. Slotine and W. Li, Applied nonlinear control, Prentice-Hell, New Jersey, 1991, pp 1-13.
[25] J. Y. Hung, W. Gao, and J. C. Hung, “Variable structure control: a survey,” IEEE Trans. Ind.Electron., vol. 40, no. 1, pp. 2-22, Feb. 1993.
[26] L. Y. Sun, S. Tong, and Y. Liu, “Adaptive Backetstepping sliding mode control of static var compensator,” IEEE Trans. Control Syst. Techn., vol. 19, no. 5, pp. 1178-1185, Sept. 2011.
[27] L. X. Wang, “Fuzzy systems are universal approximators,” IEEE Int. Conf. on Fuzzy System, pp. 1163-1170, Mar. 1992.
[28] W. Johnson, Helicopter optimal descent and landing after power loss, NASA TM 73244, pp 1-19, May 1977.
[29] Range Commanders Council (RCC), “Common risk criteria standards for national test ranges: Supplement,” Deptment of Defense, standard 321-07, Jun. 2007.
QRCODE
 
 
 
 
 
                                                                                                                                                                                                                                                                                                                                                                                                               
第一頁 上一頁 下一頁 最後一頁 top
1. 8. 何志峰、高玉芬(1999)。產學合作之控制機制設計。技術及職業教育雙月刊,53,25-27。
2. 13. 吳淑鶯(1996)。二年制商專學生對教學與學習之相關意見探討。商業職業教育季刊,64,24-35。
3. 35. 胡夢蕾(1999)。三明治教學法中實務教學設計的研究-以餐飲管理科課程為例。景文技術學院學報,9(2),235-266。
4. 39. 高玉芬、何志峰(1996)。由策略聯盟剖析建教合作。技術及職業教育雙月刊,35,51-54。
5. 56. 曹勝雄、容繼業、劉麗雲(2000)。專科餐旅教育「三明治教學制度」實施認知之研究─從教師觀點。高雄餐旅學報,3,53-68。
6. 57. 莊煥銘、王淑娟(2004)。資訊系統採用行為意向之研究-以某大學為例。商管科技季刊,4(3),239-259。
7. 59. 許國雄(1996)。加強技職體系建教合作制度之研究。東方工商學報,19,1-22。
8. 63. 郭德賓、莊明珠(2006)。校外實習課程衝突影響因素對學生就業意願影響之研究:以國立高雄餐旅學院餐飲管理科系學生為例。餐旅暨家政學刊,1(3),113-131。
9. 64. 陳嘉彌(1998)。師徒式教育實習(一位實習教師省思之剖析與詮釋)。教育實習輔導季刊,3(4),41-48。
10. 73. 劉修祥、陳麗文(2000)。高雄市高職餐飲管理科應屆畢業生就業意向之探討。技術及職業教育雙月刊,58,31-37。
 
系統版面圖檔 系統版面圖檔