臺灣博碩士論文加值系統

本篇論文的主題為實係數不確定參數之估測與分析。利用線性規劃的幾何概念，我們提出兩種估測方式：批次處理與遞迴演算。批次處理的方式可很容易得到不確定參數的範圍，而遞迴演算則可得到適用性較佳的範圍集合。最後利用所得到的不確定參數估測法則，對HP DJ400彩色噴墨列表機直流噴墨馬達系統做實際估測與分析。最後在本篇論文的這些估測法則可以很容易的轉換成電腦輔助設計程式，並且可由實際系統的輸入輸出資料來取得較佳的參數估測。

The objective of the thesis is to analyze and estimate the real uncertain parameters of linear systems. Using the geometric concepts of linear programming, we offer two ways of estimation: the batch algorithm and the recursive algorithm.
The batch algorithm could get the exact range of uncertain parameters but with heavier computational load. The recursive algorithm could reduce the amount of computations but only to get the an estimated range set of uncertain parameters.
We demonstrate our algorithms via a practical example: estimating the uncertain parameters of HP DJ400 color inkjet printer''s DC motor system. It is shown that we can indeed get the parametric estimation from I/O data of real system.
At last, it can be mentioned that the estimation laws in this thesis can be easily transformed into CAD programs for further analysis.

第一章 簡介 2
第二章 研究背景與目的 4
2.1 傳統系統判別法則 4
2.2 強健系統判別與傳統判別 8
第三章 批次參數估測 12
3.1 離散系統架構 12
3.2 線性規劃 14
3.3 批次系統判別 18
3.4 批次判別的探討 24
3.5 強健系統進階分析 32
第四章 遞迴參數估測 34
4.1 橢圓體的幾何概念 34
4.2 遞迴判別法則 39
4.3 遞迴判別的應用 42
4.4 遞迴判別的探討 44
4.5 橢圓體與強健系統的關係 50
第五章 實際應用與展望 51
5.1 物理模式架構的建立 51
5.2 參數估測的結果 53
5.3 結論與展望 54

A. Helmicki, C. Jacobson and C. Nett, ''Control Oriented System Identification: A Worst-Case Deterministic Approach in '''', IEEE Transactions on Automatic Control, Vol. 36, pp. 1163-1176, 1991.
B. R. Barmish, New Tools for Robustness of Linear Systems, Macmillan Publishing Co. , New York, NY, 1994.
D. G. Luenberger, Introduction to Linear and Nonlinear Programming, Addison-Wesley, 1973.
E. Fogel and Y. F. Huang, ''On the Value of Information in System Identification: Bounded Noise Case '''', Automatica, pp. 229-238, 1987.
E. Walter and H. Piet-Lahanier, ''Exact Recursive Polyhedral Description of the Feasible Parameter SET for Bounded-Error Models'''', IEEE Transactions on Automatic Control, Vol. 34, No. 8, AUGUST 1989.
F. C. Schweppe, Uncertain Dynamical Systems, Prentice Hall, 1973.
G. Belforte, B. Bona and V. Cerone, ''Parameter Estimation Algorithms for a Set-membership Description of Uncertainty'''', Automatica, pp. 887-898, 1990.
H. Karloff, Linear Programming, Birkhauser, 1991.
H. Kwakernaak and R. Sivan, Linear Optimal Control Systems, New York: Wiley, 1972.
H. Piet-Lahanier, and E. Walter, ''Exact Description of the Feasible Parameter Sets and Minimax Estimation'''', International Journal of Adaptive and Singal Processing, Vol. 8, pp. 5-14, 1994.
I. D. Landau, System Identification and Control Design, Prentice Hall, 1990.
J. P. Norton, An Introduction to Identification, Academic Press, 1986.
J. P. Norton, ''Identification and Application of Bounded-Parameter Models'''', Automatica, pp. 497-507, 1987.
L. Ljung, System Identification, Prentice Hall, 1987.
Man-Fung Cheung, Stephen Yurkovich, and Kevin M. Passino, '' An Optimal Volume Ellipsoid Algorithm for Parameter Set Estimation'''', IEEE Transactions on Automatic Control, Vol. 38, No. 8, AUGUST 1993.
M. Milanese and A. Vicino, ''Optimal Estimation Theory for Dynamic Systems with Set Membership Uncertainty: An Overview'''', Automatica, pp. 997-1009, 1991.
R. C. Younce and C. E. Rohrs, ''Identification with Nonparametric Uncertainty'''', IEEE Transactions on Automatic Control, Vol. 37, pp. 715-728, 1992.
R. Johansson, System Modeling and Identification, Prentice Hall, 1993.
R. L. Kosut, M. K. Lau and S. P. Boyd, ''Set-Membership Identification of Systems with Parametric and Nonparametric Uncertainty'''', IEEE Transactions on Automatic Control, Vol. 37, pp. 929-941, 1992.
S. Boyd and L. Vandenberghe, Convex Optimization, Stanford University Course Reader, 1999.
S. C. Fang and S. Puthenpura, Linear Optimization and Extensions: Theory and Algorithms, Prentice Hall, 1993.