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研究生：	潘欣長 Pan, Shin-Jang
論文名稱：	基因演算法在某類資料取樣系統控制之應用 Applications of Genetic Algorithms on Control of Some Classes of Sampled-Data Systems
指導教授：	蔡聖鴻 Tsai, Sheng-Hong Jason
學位類別：	博士 Doctor
系所名稱：	電機資訊學院 - 電機工程學系 Department of Electrical Engineering
論文出版年：	2011
畢業學年度：	99
語文別：	英文
論文頁數：	121
中文關鍵詞：	基因演算法、殊異擾動系統、數位再設計、演化式規劃
外文關鍵詞：	genetic algorithm, singular system, digital-redesign, evolutionary programming
相關次數：	點閱：93 下載：1
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針對某類資料取樣系統，本論文提出應用基因演算法在以觀測器為基礎之控制器設計。本文涵蓋四個主題：第一主題，提出基因演算法應用於具離散多時延奇異系統之控制器設計。首先產生相對於原系統之快、慢子系統，並應用基因演算法設計各子系統對應之控制器，再藉由合成子系統控制器產生適合原系統之狀態回授控制器。原系統穩定度之確認方面，在系統參數滿足某些條件時，可藉由各子系統穩定度的確認而獲得。在第二主題中，提出針對離散多時延奇異系統，應用基因演算法設計以觀測器為基礎之特定圓穩定(Disk stability)控制器，並將第一主題中有關控制與穩定度之分析範圍由單位圓內擴展至特定圓內。另外，提出與原系統擾動參數有關之穩定度條件，以確保在以觀測器為基礎之合成控制器控制下原系統之穩定度。在第三主題提出，針對未知但具時延之取樣互聯大尺度線性殊異系統，建構其分散線性模式，並設計以觀測器為基礎的追蹤器。首先經由離線觀測器/卡爾門濾波器辨識，產生較低階分散控制線性觀測器，然後求出相對應之具高增益線性二次式次最佳化類比觀測器及追蹤器，使得受控之閉迴路具有分散解耦的特性。接著利用以預測為基礎之數位再設計方法，得到實務上可執行之數位觀測器及追蹤器。最後，藉由演化式規劃獲得各分散觀測器更適合之權重調整，以改善以觀測器為基礎之追蹤器效能。第四主題則對某類雙線性控制系統提出狀態回授控制器，使得系統輸出為穩定週期解，成為可調振幅之震盪器。當系統未知時，設計以觀測器為基礎的追蹤器，並藉由基因演算法改善追蹤器效能。

This dissertation is dedicated to develop applications of genetic algorithm (GA) on controller design for some classes of sampled-data systems. It covers four topics: First, an application of GA on control for discrete multiple time-delayed singular system is proposed. The compact state feedback controllers for the slow and the fast subsystems are separately designed by a GA and then a composite state feedback controller is synthesized. Stability of original system is confirmed by establishing that of its corresponding slow and fast subsystems if any one criteria of the condition is satisfied. Secondly, a GA application is extended to the observer-based Disk-stability controller design for the system in first topic. Moreover, a -dependent upon stability condition is proposed to guarantee the stability of the original system under the composite observer-based controller. The third topic is to propose the modeling of decentralized linear observers and trackers for the unknown sampled-data interconnected large-scale linear singular system with time-delayed. Through the off-line observer / Kalman filter identification, the appropriate order decentralized linear observers are determined. Then, the corresponding high-gain linear quadratic suboptimal analogue observer and tracker are proposed such that the system has closed-loop decoupling property. Subsequently, the prediction-based digital redesign method is utilized to obtain practically implemental digital observer and tracker for the sampled-data system. Finally, appropriate weighting of the each decentralized observer can be obtained to improve the performance of observer-based tracker by the evolutionary programming. The fourth topic is to propose a feedback control for a class of bilinear systems and the exponentially stable periodic solutions are guaranteed. If the system is unknown, we first construct the observer-based tracker and use GA to tune the observer gain to improve the tracking performance.

摘要		i
Abstract	ii
Acknowledgment	iii
Contents	iv
List of Figures	vii
Symbols and Abbreviations	x
Chapter 1	Introduction 	1
1.1	Literature survey and motivation	1
1.2	Organization of the dissertation	6
Chapter 2	Application of Genetic Algorithm on Control of Discrete Multiple  Time-Delayed Singular Perturbation Systems 	8
2.1	Introduction	8
2.2	Discrete multiple time-delayed singular perturbation systems	9
	2.2.1  Derivation of slow subsystem and fast subsystem	10
2.3	State feedback controller design for the slow and the fast subsystems	11
	2.3.1  State feedback controller design for the slow subsystem	11
	2.3.2  State feedback controller design for the fast subsystem	13
2.4	Composite state feedback controller design for the original system	14
2.5	The GA for designing control gains	15
2.6	Summary	16
Chapter 3	Application of Genetic Algorithm on Observer-Based D-stability Control for Discrete Multiple Time-Delayed Singular Perturbation Systems 	18
3.1	Introduction	18
	3.1.1  Basic observer equation	19
3.2	GA on the observer-based controller design of the subsystems	20
	3.2.1  Controller design for the slow subsystem	21
	3.2.2  Design procedure of GA	24
	3.2.3  Controller design for the fast subsystem	25
3.3	Composite observer-based controller design for the original system	28
3.4	An illustrative example	35
3.5	Summary	43
Chapter 4	Modeling of Decentralized Linear Observers and Trackers for the  Unknown Sampled-data Interconnected Large-Scale Linear Singular System with Time-Delayed 	45
4.1	Introduction	45
4.2	Observer/Kalman filter identification	47
	4.2.1  Basic observer equation	48
	4.2.2  Computation of observer Markov parameters	50
	4.2.3  Eigensystem realization algorithm	51
4.3	Quadratic suboptimal tracker and observer for unknown sampled-data linear singular systems	53
	4.3.1  Suboptimal state-feedback tracker for the regular system	53
	4.3.2  Prediction-based linear quadratic digital tracker	55
	4.3.3  Prediction-based digital observer	57
4.4	Evolutionary programming (EP) based quadratic suboptimal tracker and observer for unknown sampled-data linear singular systems	60
	4.4.1  Quasi-random sequences (QRS)	60
	4.4.2  Tuning the observer gain for the digital redesigned adaptive tracker	61
4.5	Design procedure	63
4.6	Illustrative examples	66
	Example 4.1	66
	Example 4.2	76
4.7	Summary	91
Chapter 5	Application of Genetic Algorithm on Observer-Based Tracker Design for Unknown Sampled-Data Systems 	92
5.1	Introduction	92
5.2	Problem formulation and main results	93
5.3	Quadratic suboptimal tracker and observer for unknown sampled-data systems	98
5.4	Design procedure	99
5.5	Illustrative examples	100
	Example 5.1	100
	Example 5.2	105
5.6	Summary	108
Chapter 6	Conclusions 	109
	Further Research Directions	110
 References		111
 Appendix		117
 Biography		121


                                    

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