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DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.advisor | 顏家鈺(Jia-Yush Yen) | |
dc.contributor.author | Liu-Hsu Lin | en |
dc.contributor.author | 林柳絮 | zh_TW |
dc.date.accessioned | 2021-06-08T06:56:18Z | - |
dc.date.copyright | 2011-08-26 | |
dc.date.issued | 2011 | |
dc.date.submitted | 2011-08-22 | |
dc.identifier.citation | [1]Ziegler, J.G and Nichols, N. B., “Optimum settings for automatic controllers,” Transactions of the ASME, 64. pp. 759–768, 1942.
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Grimble, “ controllers with a PID structure,” Trans. ASME J. Dynam. Syst. Meas. Control, vol. 112, pp. 325-330, 1990. [16]J. Bao, J. F. Forbes, and P. J. McLellan, “Robust multiloop PID controller design: a successive semidefinite programming approach,” Ind. Eng. Chem. Res., vol. 38, pp. 3407-3413, 1999. [17]S. Miyamoto, “Robust controller design: A coprime factorization and LMI approach,” Ph.D. dissertation, St. Edmund’s College, Univ. Cambridge, Cambridge, U.K.,1997. [18]M. Ho and C. Lin, “PID Controller Design for Robust Performance,” IEEE Trans. Automatic Control, vol. 48, No. 8, pp. 1404-1409, 2003. [19]M. Ho, “Synthesis of PID Controllers: A Parametric Approach,” Automatica, vol. 39, No. 6, pp.1069-1075, 2003. [20]J.W. Dong and G. B. Brosilow, “Design of robust multivariable PID controllers via IMC,” Proc. American Control Conference, Albuquerque, NewMexico, pp. 3380-3384, 1997. [21]W. Tan, J. Z. Liu, and P. K. S. Tam, “PID tuning based on loop-shaping control,” IEE Proc. on Control and Applications, vol.145, pp. 485-490, 1998. [22]Doyle, J.C., B.A. Francis, and A.R. Tannenbaum, Feedback Control Theory, 1992, New York. [23]Glover, K. and D.C. McFarlane, Robust Controller Design Using Normalized Coprime Factor Plant Descriptions, Springer-Verlag New York, Inc. 217, 1989. [24] D.C. McFarlane and Glover, K., “A loop shaping design procdure using synthese,” IEEE Transactions on Automatic Control, AC-37:749-769,1992 [25]Georgiou, T.T. and M.C. Smith, “Optimal Robustness in the Gap Metric,” Automatic Control, IEEE Transactions on, 35(6): p. 673-686, 1990. [26]Eberhart, R.C. and Kennedy, J. ,“A new optimizer using particle swarm theory,” Proc. Sixth International Symposium on Micro Machine and HumanScience, Nagoya, Japan, pp.39-43, 1995. [27]Eberhart, R.C. and Shi. Y., “Comparison between genetic algorithms and particle swarm optimization,” 1998 Annual Conference on Evolutionary Programming, San Diego, 1998. [28]Eberhart, R.C. and Shi, Y., “Particle swarm optimization: developments, app- lications and resources,” Proc. IEEE Int. Conf. On Evolutionary Computation, pp.81-86, 2001. [29]Fukuyama, Y. and Yoshida, H., “A particle swarm optimization for reactive power and voltage control in electric power systems,” Congress Evolutionary Computation, Vol 1, pp.87-93, 2001. [30]Kennedy, J. and Eberhart, R.C., “Particle swarm optimization,” Proc. IEEE International Conference on Neural Networks, (Perth, Australia), IEEE Service Center, Piscataway, NJ, pp. IV:1942-1948, 1995. [31]Dorigo, M. and Maniezzo, V. and Colorni, A. “The ant system: Optimizatoin by a colony of cooperating agents,” IEEE Transactions on Systems and Cybernetics - Part B, Vol 26-1, pp.29-41, 1996. [32]Shi, Y. and Eberhart, R.C. “Parameter selection in particle swarm optimization,” The 7th Annual conference on evolutionary programming, San Diego, USA , 1998 [33]A. Carlisle and G. Dozier, “An off-the-shelf pso,” in The Particle Swarm Optimization Workshop, pp. 1–6, 2001. [34]M. T. Ho and Yi-Wei Tu,“PID Controller Design for a Flexible-Link Manipulator,” Proceedings of the 44th IEEE Conference on Decision and Control, pp. 6841 - 6846, Dec. 2005. [35]陳炫綜,多變數強韌控制理論在質子交換膜燃料電池上的應用,國立台灣大學機械工程研究所博士論文,2009。 [36]周銘城,質子交換膜燃料電池控制及整合,國立台灣大學機械工程研究所碩士論文,2009。 [37]黃志偉,系統識別和Hinf強韌控制在質子交換膜燃料電池上的應用,國立台灣大學機械工程研究所碩士論文,2006年。 | |
dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/25852 | - |
dc.description.abstract | 本文提出了一種新的強健控制器設計方法,採用粒子群最佳化(Particle Swarm Optimization,PSO)來合成強健比例-積分-微分(Proportional-Integral-Derivative,PID)控制器。強健控制在處理系統不確定性和干擾的能力是眾所周知。但是,採用傳統Hinf強健控制理論所設計出來的控制器,其往往是高階和複雜的結構,是很難落實在實際應用中。另一方面,PID控制器因為具有結構簡單、可靠性高與控制性能佳等優點,已廣泛應用在不同控制工程領域中,但他們缺乏厚實的理論基礎在處理系統不確定性和干擾。因此,本文結合強健控制理論與PID控制器這兩種控制的優勢,使用粒子群最佳化設計PID結構控制器,使控制系統滿足強健性能。在文中,首先簡要介紹強健控制理論和粒子群最佳化演算法。然後,採用粒子群最佳化來合成強健PID控制器,並使用四個數值例子進行電腦模擬來說明設計程序。最後,將所設計的控制器上應用在質子交換膜燃料電池(PEMFC)控制系統上作實驗驗證,並與傳統的Hinf強健控制器進行比較。從模擬和實驗結果顯示,本文所提出的強健PID控制器是有效的與實用的。 | zh_TW |
dc.description.abstract | This paper proposes a novel method to synthesize robust proportional-integral-derivative (PID) controllers using particle swarm optimization (PSO). Robust control is well known for its ability in dealing with system uncertainties and disturbances. Standard robust control design, however, can result in controllers that are high-order and complicated and can be difficult to implement in practical applications. PID controllers are advantageous because of their simple structures and wide acceptance in engineering practice, but they lack profound theorems in dealing with system uncertainties and disturbances. Therefore, combining the advantages of these two control algorithms, robust PID-structure controllers are proposed to optimize system performance using PSO. In this work, we first briefly introduce Hinf robust control theory and particle swarm optimization algorithm. Then, the particle swarm optimization algorithm is used to synthesize robust PID controllers and four numerical examples are used to illustrate the design procedures. Finally, the designed controller was implemented on a Proton Exchange Membrane Fuel Cell (PEMFC) control system for experimental verifications and compared with conventional Hinf controllers. From the simulation and experimental results, the proposed robust PID controller is effective and practical. | en |
dc.description.provenance | Made available in DSpace on 2021-06-08T06:56:18Z (GMT). No. of bitstreams: 1 ntu-100-D91522021-1.pdf: 1808767 bytes, checksum: 89b524d7bc81d96676cfa60cff3b1a30 (MD5) Previous issue date: 2011 | en |
dc.description.tableofcontents | 口試委員會審定書..i
誌謝..ii 摘要..iii Abstract..iv 目錄..v 圖目錄..ix 表目錄..xiv 符號表..xv 第一章 緒論..1 1.1 研究動機與目的..1 1.2 文獻回顧..2 1.3 論文架構..3 第二章 傳統強健控制理論介紹和設計..5 2.1 範數定義..5 2.1.1訊號及系統的範數表示..5 2.2 系統不確定性..6 2.3 強健控制結構的一般化..9 2.4 強健控制之穩定性與性能規範..10 2.4.1小增益定理..10 2.4.2加法型擾動系統..11 2.4.3乘法型擾動系統..12 2.4.4互質分式型擾動系統..12 2.4.5控制性能..13 2.5 常態系統的選擇..16 2.6 最佳化Hinf強健性控制器設計..17 2.7 迴路整形設計..19 第三章 粒子群最佳化介紹..22 3.1 引言..22 3.2 粒子群最佳化演算法..22 3.3 PSO參數設定..26 第四章基於粒子群最佳化之強健PID控制器設計粒..28 4.1 成本函數..28 4.1.1靈敏度最佳化問題..28 4.1.2強健穩定最佳化問題..29 4.1.3強健性能最佳化問題..29 4.1.4混合頻域與時域性能最佳化問題..30 4.2 粒子群最佳化強健PID控制設計程序..31 第五章 電腦模擬與分析..32 5.1 範例一:具乘法不確定性之SISO控制系統例..32 5.1.1問題描述..32 5.1.2強健PID控制器設計:使用粒子群最佳化..33 5.1.3強健Hinf控制器設計:使用Hinf控制理論..37 5.1.4模擬結果之分析比較..39 5.2 範例二:具左互質因子不確定性之MIMO控制系統例..42 5.2.1問題描述..42 5.2.2強健PID控制器設計:使用粒子群最佳化..43 5.2.3強健 控制器設計:使用迴路整型設計法..45 5.2.4模擬結果之分析比較..45 5.3 範例三:具有右半平面極點與零點之SISO控制系統例..50 5.3.1問題描述..50 5.3.2強健PID控制器設計:使用粒子群最佳化..52 5.3.3強健Hinf控制器設計:使用混合靈敏度設計法..56 5.3.4模擬結果之分析比較..60 5.4 範例四:PSO-PID控制器與降階Hinf控制器設計例..64 5.4.1問題描述..64 5.4.2強健PID控制器設計:使用粒子群最佳化..65 5.4.3強健Hinf控制器設計:使用混合靈敏度設計法..69 5.4.4降階Hinf控制器設計..72 5.4.5模擬結果之分析比較..78 第六章 工程實例:PEMFC系統..83 6.1 前言..83 6.2 實驗設備..84 6.3 質子交換模燃料電池模型與鑑別..90 6.4 強健控制器設計:使用Hinf迴路整型設..94 6.5 強健PID控制器設計:使用粒子群最佳化..95 6.6 模擬與實驗結果..97 6.6.1模擬結果..97 6.6.2定電壓與負載實驗..98 6.6.3定負載變電壓實驗..101 6.7 實驗結果討論..104 第七章 結論與未來展望..106 7.1 結論..106 7.2 未來展望..106 參考文獻..108 附錄..112 | |
dc.language.iso | zh-TW | |
dc.title | 基于粒子群最佳化之強健PID控制器設計與應用 | zh_TW |
dc.title | Design of a Robust PID Controller Using Particle Swarm Optimization and its Applications | en |
dc.type | Thesis | |
dc.date.schoolyear | 99-2 | |
dc.description.degree | 博士 | |
dc.contributor.coadvisor | 王富正(Fu-Cheng Wang) | |
dc.contributor.oralexamcommittee | 陽毅平(Yee-Pien Yang),陳希立(Sih-Li Chen),譚俊豪 | |
dc.subject.keyword | 強健控制,PID,粒子群最佳化,質子交換膜燃料電池, | zh_TW |
dc.subject.keyword | Robust control,PID,particle swarm optimization,PEMFC, | en |
dc.relation.page | 113 | |
dc.rights.note | 未授權 | |
dc.date.accepted | 2011-08-23 | |
dc.contributor.author-college | 工學院 | zh_TW |
dc.contributor.author-dept | 機械工程學研究所 | zh_TW |
顯示於系所單位: | 機械工程學系 |
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