進階搜尋


   電子論文尚未授權公開,紙本請查館藏目錄
(※如查詢不到或館藏狀況顯示「閉架不公開」,表示該本論文不在書庫,無法取用。)
系統識別號 U0026-2207201310433000
論文名稱(中文) 以具有輸入飽和限制預測型卡曼濾波器錯誤偵測為基礎的混沌通訊加密系統
論文名稱(英文) Chaotic Secure Communication System Based on Predictive Kalman Fault Estimator with Input Constraint
校院名稱 成功大學
系所名稱(中) 電機工程學系碩博士班
系所名稱(英) Department of Electrical Engineering
學年度 101
學期 2
出版年 102
研究生(中文) 郭芳誠
研究生(英文) Fang-Cheng Guo
學號 n26001084
學位類別 碩士
語文別 英文
論文頁數 65頁
口試委員 指導教授-蔡聖鴻
口試委員-郭淑美
口試委員-蔡宗吉
口試委員-林明宏
口試委員-杜彥頤
中文關鍵字 混沌系統  安全通信  數位再設計  錯誤檢測和診斷  線性二次類比追蹤器  輸入飽和限制 
英文關鍵字 Chaotic systems  Secure communications  Digital redesign  Fault detection and diagnosis  Linear quadratic analog tracker  Input constraint 
學科別分類
中文摘要 混沌系統通常應用於安全通信的加密,但它們可能無法提供高度的安全性。為了改善通訊的安全性,混沌系統需要增加其他的防護信號,但添加其他信號可能導致原始系統發散。本論文,我們重新設計通信架構,使其可以增加額外的安全信號,並使系統不發散。首先介紹了適用狀態空間適應觀測器的誤差判斷/估計及高性能追蹤器,以解決取樣線性時變系統在致動器/系統狀態有未預期到的衰變因素。接著介紹殘值產生的架構和自動調節切換增益機制,使所提出的方法適用於致動器和狀態故障的誤差檢測和診斷(FDD),以達高效能的追蹤目標。本論文也提出一種以進化規劃法為基礎的適應性觀測器應用於安全通信的問題。然而,已知的參考輸入在某些時間瞬間有劇烈的變動,導致某些物理系統的輸入過大以造成輸入飽和,為了克服這個缺點,改良的線性二次類比追蹤器(LQAT)可以在特定時間區間內有效地限制輸入控制力,並且維持可接受的追蹤性能。透過軌跡追踪模擬範例說明了所設計方法的有效性和效率。
英文摘要 Chaotic systems are often applied to encryption on secure communications, but they may not provide a high-degree security. In order to improve the communication of security, chaotic system needs to be add other secure signal, but additional dimensions or signals may cause signals to divergence. In this thesis, we redesign a communication scheme that could create secure signals with additional secure signals, and the scheme could keep system convergence. First, we introduce the universal state-space adaptive observer-based fault diagnosis/estimator and the high-performance tracker for the sampled-data linear time varying system with unanticipated decay factors in actuators/ system states. Second, a residual generation scheme and a mechanism for auto-tuning switched gain is also presented, so that the introduced methodology is applicable for the fault detection and diagnosis (FDD) for actuator and state faults to yield the high tracking performance recovery. The evolutionary programming-based adaptive observer is then applied to the problem of secure communication. However, since the given reference input has serious variation at some time instants, the tracker can easily induces the large input which might not conform to the input constraint of some physical systems. To overcome this disadvantage, the proposed modified linear quadratic analog tracker (LQAT) can effectively restrict the control input within the specified constraint interval, under the acceptable tracking performance. The effectiveness and efficiency of proposed design methodology are illustrated through tracking control simulation examples.
論文目次 中文摘要...I
Abstract...II
Acknowledgments...IV
List of Contents...V
List of Figures...VII
Chapter
1.Introduction...1
2.An Improved Kalman Filter-based Adaptive Observer for State Estimation and Actuator Fault Detection and Diagnosis...5
2.1Adaptive observer...6
2.2Kalman filter-based adaptive observer...6
2.3An improved Kalman filter-based adaptive observer...10
3.Auto-tuning Switched Mechanism for Sampled-data Nonlinear
Time-varying System Against Actuator and State Fault...18
3.1Actuator fault detection and performance recovery of nonlinear systems...20
3.1.1Optimal linearization of nonlinear systems...20
3.1.2Actuator and state fault detection and performance recovery of nonlinearv(slowly) time-varying systems with optimal linearization...22
3.2Residual-generation-based auto-tuning switched mechanism for detection and diagnosis of actuator and state faults...27
4High-performance Digital Redesign Tracker without Actuator/State Faults...32
4.1Linear quadratic analog tracker design for healthy actuator/state...33
4.2Digital redesign of the linear quadratic analog tracker for healthy state...34
4.3Adaptive observer/tracker: An evolutionary programming approach...36
4.3.1 Quasi-random sequences (QRS)...37
4.3.2 Tuning gain of the digital redesigned adaptive tracker with observer...37
4.4 Digital redesign of optimal control for sampled-data systems under input constraint...42
4.4.1 Motivation of the modified optimal control scheme...42
4.4.2 Detailed procedure of the modified LQAT design...46
5 Application on Secure Communication...49
5.1 Secure communication based on discrete-time system...50
5.2 Application of the adaptive fault estimator to secure communications...51
6 An Illustrative Example...54
7 Conclusion...61
References...62
參考文獻 [1]Computer Controlled Systems: Theory and Design(3rd Edition).Pretice-Hall, 1996.
[2]Bodson, M. and Groszkiewicz, J.,“Multivariable adaptive algorithms for reconfigurable flight control,” IEEE Transactions on Control Systems Technology, vol. 5(2), pp. 217-229, 1997.
[3]Caglayan, A. K. and Lancraft, R. E.,“A separated bias identification and state estima-tion algorithm for nonlinear systems,” Automatica, vol. 19(5), pp. 561-570, 1983.
[4]Edwards, C., Spurgeon, S. K., and Patton, R.J., “Sliding mode observers for fault detection and isolation, ” Automatica, vol. 36(4), pp. 541-553, 2000.
[5]Fekih, A., Xu, H., and Chowdhury, F. N., “Neural networks based system identification techniques for model based fault detection of nonlinear systems,” International Journal of Innovative Computing Information and Control, vol. 3(5), pp. 1073-1085, 2007.
[6]Gauthier, J. P. and Kupka, A. K., “Observability and observers for nonlinear systems,” SIAM J. Control Optim, vol. 32(4), pp. 975-994, 1994.
[7]Guo, S. M., Shieh, L. S., Chen, G., and Lin, C. F., “Effective chaotic orbit tracker: a prediction-based digital redesign approach,” IEEE Transaction on Circuits and Systems–I, Fundamental Theory and Application, vol. 47(11), pp. 1557-1570, 2000.
[8]Guo, S. M. and Peng, Z. H., “An observer-based decentralized tracker for sampled-data systems: an evolutionary programming approach,” International Journal of General Systems, vol. 34(4), pp. 421-449, 2005.
[9]Halton, J. H., “On the efficiency of certain quasi-random sequences of points in evaluating multidimensional integrals,” Numerische mathematik, vol. 2(1), pp. 84-90, 1960.
[10]Huang, S. and Tan, K. K, “Fault detection and diagnosis based on modeling and estimation methods,” IEEE Transactions on Neural Networks, vol. 20(5), pp. 872-881, 2009.
[11]Jiang, B., Staroswiecki, M., and Cocquempot, V. “Fault accommodation for nonlinear dynamic systems,” IEEE Transactions on Automatic Control, vol. 51(9), pp. 1578-1583, 2006.
[12]Jiang, T., Khorasani, K., and Tafazol, S., “Parameter estimation-based fault detection, isolation and recovery for nonlinear satellite models,” IEEE Transactions on Control Systems Technology, vol. 16(4), pp. 799-808, 2008.
[13]Luders, G. and Narendra, K., “An adaptive observer and identifier for a linear system,” IEEE Transactions on Automatic Control, vol. 18(5), pp. 496-499, 1973.
[14]Liu, L., Logan, K, Cartes, D., and Srivastava, S., “Fault detection, diagnostics, and prognostics: Software agent solutions,” IEEE Transactions on Vehicular Technology, vol. 56(4), pp. 1613-1622, 2007.
[15]Mayberck, P. S., “Multiple model adaptive algorithms for detecting and compensating sensor and actuator/surface failures in aircraft flight control systems,”International Journal of Robust and Nonlinear Control, vol. 9(14), pp. 1051-1070, 1999.
[16]Rodrigues, M., Theilliol, D., Aberkane, S., and Sauter, D., “Fault tolerant control design for polytopic lpv systems,” International Journal of Applied Mathematics and Computer Science, vol. 17(1), pp. 27-37, 2007.
[17]Rodrigues, M., Theilliol, D., Adam-Medina, M., and Sauter, D., “A fault detection and isolation scheme for industrial systems based on multiple operating models,” Control Engineering Practice, vol. 16(2), pp. 225-239, 2008.
[18]Teixeira, M. C. M. and Zak, S. H.,“Stabilizing controller design for uncertain nonlinear systems using fuzzy models,” IEEE Transaction on Fuzzy System, vol.7(2), pp. 133-142, 1997.
[19]Tsai, J. S. H., Yu, J. M., Canelon, J. I., and Shieh, L.S.,“Extended-Kalman-filter-based chaotic communication,” IMA Journal of Mathematical Control and Information, vol. 22(1), pp. 58-79, 2005.
[20]Tange, X. D., Tao, G., and Joshi, S. M., “Adaptive actuator failure compensation for nonlinear mimo systems with an aircraft control application,” Automatica, vol. 43(11), pp. 1869-1883, 2007.
[21]Tsai, J. S. H., Lin, M. H., Zheng, C. H., Guo, S. M., and Shieh, L. S., “Actuator fault detection and performance recovery with kalman filter-based adaptive observer,” International Journal of General Systems, vol. 36(4), pp. 375-398, 2007.
[22]Tsai, J. S. H., Wei, C. L., Guo, S. M., Shieh, L. S., and Liu, C. R., “Ep-based adaptive tracker with observer and fault estimator for nonlinear time-varying sampled-data systems against actuator failures,” Journal of the Franklin Institute-engineering and Applied Mathematics, vol. 345(5), pp. 508-535, 2008.
[23]Tsai, J. S. H., Du, Y. Y., Zhuang, W. Z., Guo, S. M., Chen, C. W., and Shieh, L. S., “Optimal anti-windup digital redesign of multi-input multi-output control systems under input constraints,” IET Control Theory Applications, vol. 5(21), pp. 447-464, 2011.
[24]Veillette, R., Medanic, J., and Perkins, W., “Design of reliable control systems,” IEEE Transactions on Automatic Control, vol. 37(3), pp. 290-304, 1992.
[25]Wu, N.E., Zhang, Y. M., and Zhou, K. M., “Detection, estimation, and accommodation of loss of control effectiveness,” International Journal of Adaptive Control and Signal Processing, vol. 14(7), pp. 775-795, 2000.
[26]Wei, C. L., Tsai, J. S. H., Guo, S. M., and Shieh, L. S., “Universal predictive Kalman filter-based fault estimator and tracker for sampled-data nonlinear time-varying systems,” IET Control Theory & Applications, vol. 5(1), pp. 203-220,2011.
[27]Zhang, Y. and Jiang, J., “ Integrated active fault-tolerant control using imm approach,” IEEE Transactions on Aerospace and Electronic Systems, vol. 37(4), pp. 1221-1235, 2001.
[28]Zhang, Q., “Adaptive observer for multiple-input-multiple-output (mimo) linear time- varying systems,” IEEE Transactions on Automatic Control, vol. 47(3), pp. 525-529, 2002.
[29]Zhang, X., Parisini, T., and Polycarpou, M., “Adaptive fault-tolerant control of nonlinear uncertain systems: an information-based diagnostic approach,” IEEE Transactions on Automatic Control, vol. 49(8), pp. 1259-1274, 2004.
[30]Zhang, K., Jiang, B., and Shi, P., “A new approach to observer-based fault-tolerant controller design for Takagi-sugeno fuzzy systems with state delay,” Circuits Systems and Signal Processing, vol. 28(5), pp. 679-697, 2009.
論文全文使用權限
  • 同意授權校內瀏覽/列印電子全文服務,於2023-12-31起公開。


  • 如您有疑問,請聯絡圖書館
    聯絡電話:(06)2757575#65773
    聯絡E-mail:etds@email.ncku.edu.tw