| 研究生: |
陳奕嘉 Chan, Yi-Jia |
|---|---|
| 論文名稱: |
數據化控制誤差之降低:不同設計法則的測試與比較 Error Reduction in Data-Based Control Synthesis:Tests and Comparisons of Various Design Techniques |
| 指導教授: |
陳正宗
Chan, Jenq-Tzong Hermann |
| 學位類別: |
碩士 Master |
| 系所名稱: |
工學院 - 航空太空工程學系 Department of Aeronautics & Astronautics |
| 論文出版年: | 2006 |
| 畢業學年度: | 94 |
| 語文別: | 中文 |
| 論文頁數: | 71 |
| 中文關鍵詞: | 濾除器 、數據化控制器 、最佳控制 |
| 外文關鍵詞: | auto-regression sequence annihilator, DBCS, optimal control |
| 相關次數: | 點閱:104 下載:1 |
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傳統的線性最佳化控制(LQ)面臨著二大問題:一是系統的狀態必須隨時可測得,另一為系統模式估測所牽涉到的估測誤差。而數據化最佳控制(DBLQ)已解決了傳統設計法所面臨之問題。但在數據化設計過程中,對於所取得的開迴路實驗數據若含有雜訊,將會直接影響控制器設計的準確性,所以雜訊的濾除就顯的相當重要。因此本論文目的就是先將所取得的一組實驗數據,應用一般性自迴序列濾除器加以濾除,再進行數據化控制器設計,與實驗數據未經一般性自迴序列濾除器處理直接進行數據化控制器設計相互比較,研究哪一種方法會有較佳之性能。
The traditional linear quadratic (LQ) design faces two problems : the system state
must be measured at alltime and the system model need to be estimated with inevitable estimate error. The data-based linear quadratic (DBLQ) design has solved these problem. However during the process of data-based controller synthesis (DBCS), if the plant experimental data has been corrupted with noise signal, the well being of the synthesized controller will be in trouble.Therefore, it is important that we filter out the noise signal before the data is need for the data-based controller design. The purpose of this paper is to get one set of experimental data, filtering it through a generalized auto-regression sequence annihilator (GARSA), and then processing the filted data through DBCS. The merit of the GARSA-based noise filter is measured by comparing the resulting design with the designs which uses un-filted test data.
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