臺灣博碩士論文加值系統

本論文以智慧型運動控制平台為基礎，發展出具有高精準性與高穩定性之智慧型控制系統於串聯式定位平台。串聯式定位平台是由三台棒狀線性馬達(Tubular Linear Motors, TLMs)組合為一個X-Y-Y的結構，其中Y軸上有兩個動子，因此如需同時驅動Y軸上的動子，故同動控制逐漸成為研究串聯式定位平台之重要課題。有鑑於此，本論文提出一種改良自調正交叉耦合雙自由度PID控制策略於串聯式之棒狀線性馬達驅動階段。首先，設計獨立的單自由度PID控制和交叉耦合PID控制，分別去控制TLMs。隨後，進一步研究了獨立的雙自由度PID控制和交叉耦合雙自由度PID控制，以彰顯示雙自由度控制系統之增強控制性能。雖然交叉耦合雙自由度PID控制的結構可以提升交叉耦合PID控制的控制性能，但調整五個主要參數，包括比例增益、積分時間、微分時間，以及兩個補償的參數，包括比例和微分常數是艱難的。在這方面，開發了一個自校正交叉耦合雙自由度PID控制，並透過人工蜂群演算法(Artificial Bee Colony Algorithm, ABC)對所有控制參數進行動態優化。接著，為了加強人工蜂群演算法的搜索能力，使用粒子群演算法(Particle Swarm Optimization, PSO)的粒子移動方式混入到人工蜂群演算法的搜索公式上。從模擬和實作結果可知，與其他控制器相比，所提出的改良自校正交叉耦合雙自由度PID控制具有最小同動誤差和最佳追蹤性能。

Based on the intelligent Motion Control platform, the paper develops an intelligent control system with high precision and high stability in the series positioning platform. The series positioning platform is composed of three tubular linear motors as a X-Y-Y structure, of which there are two actuators on the Y axis, so the same-motion control is becoming animportant topic in the research of series positioning platform to drive the rotor at the same time. In view of this, this paper presents an improved self-tuning Cross-Coupled two-degree-of-freedom PID control strategy in series tubular linear motors (Tubular Linear Motors, TLMs) drive phase. Firstly, the independent PID control of single degree of freedom and the Cross-Couple PID control are designed to control TLMs respectively. Then, the independent two-degree-of-freedom PID control and the Cross-coupling two-degree-of-freedom PID control are further studied to show the enhanced control performance of the two-degree-of-freedom control system. Although the structure of Cross-Coupled two-degree-of-freedom PID control can improve the control performance of Cross-Coupled PID control, it is difficult to adjust five main parameters, including proportional gain, integration time, differential time, and two compensation parameters, including proportional and differential constants. In this respect, a self-tuning Cross-Coupled two-degree-of-freedom PID control is developed, and all control parameters are dynamically optimized through artificial colony algorithm (Artificial Bee Colony algorithm, ABC). Then, in order to enhance the searching ability of the artificial colony algorithm, the particle swarm algorithm (particle Swarm optimization, PSO) is applied to the search formula of the artificial colony algorithm. The simulation and practical results show that compared with other controllers, the proposed modified self-tuning Cross-Coupled two-degree-of-freedom PID control has the least error and the best tracking performance.

中文摘要 i
英文摘要 ii
誌謝 iv
目錄 v
表目錄 vii
圖目錄 viii
第一章 緒論 1
1.1 研究背景與動機 1
1.2 文獻探討 2
1.3 研究目的 6
1.4 研究方法 7
1.5 研究架構 8
第二章 棒狀線性馬達實驗平台 9
2.1 棒狀線性馬達的結構 9
2.2 棒狀線性馬達動的動作原理 10
2.3 實驗平台設計 13
2.4 系統鑑別 21
2.4.1 X軸系統鑑別 23
2.4.2 Y1軸系統鑑別 24
2.4.3 Y2軸系統鑑別 25
2.4.4馬達數學模型 26
2.5 數位訊號處理器軟體規劃 27
第三章 基於雙自由度PID控制之棒狀線性馬達控制系統 28
3.1 簡介 28
3.1.1 雙自由度PID控制器之型式 28
3.2 雙自由度PID控制器設計 32
3.3 交叉耦合控制系統 34
3.3.1 交叉耦合控制器策略 34
第四章 基於人工蜂群演算法之棒狀線性馬達控制系統 36
4.1 簡介 36
4.2 傳統式人工蜂群演算法 37
4.3 改良式人工蜂群演算法 39
第五章 模擬結果與討論 42
5.1 雙自由度PID控制模擬實驗結果 42
5.2交叉耦合控制策略模擬實驗結果 45
5.3人工蜂群演算法模擬實驗結果 48
第六章 實驗結果與討論 59
6.1 實驗設置 59
6.2 雙自由度PID控制實驗結果 60
6.3 交叉耦合控制策略實驗結果 65
6.4 人工蜂群演算法實驗結果 72
6.5 X-Y雙軸軌跡規劃實驗結果 83
6.5.1正三角形軌跡實驗 85
6.5.2圓形軌跡實驗 107
6.5.3合成軌跡實驗 128
第七章 結論與未來展望 130
7.1 結論 130
7.2 未來展望 131
參考文獻 132

1.黃敬鈞，棒狀線性馬達之設計與製作，碩士論文，國立聯合大學機械工程學系，苗栗，2016。
2.陶永華，2003，新型PID控制及其應用，台北市:台灣高等教育出版社。
3.白東翠，嵌入式二自由度PID控制器的研究，碩士論文，安徽理工大學，中國，2011。
4.傑川公司，http://www.jclm.com.tw/front/bin/ptlist.phtml?Category=143343
5.名元弘公司，http://www.myhiwin.com.tw/index.aspx?u=mackaytest&i=28
6.佛山微利公司，http://weili520.com/product.asp?page=2&id=2&eid=11
7.陳泓宇，線性管狀直流無刷馬達研製，碩士論文，淡江大學機械與機電工程學系，台北，2007。
8.馬偉恭，高精密度管型線性馬達應用於定位平台之設計與控制，碩士論文，
臺灣師範大學機電科技學系，台北，2011。
9.F. Cupertion, E. Mininno, D. Naso, B. Turchiano, L. Salvatore, "Compact GAs for neural network online training in tubular linear motor control," Congress on Evolutionary Computation, Sept. 2007, vol. 1, no. 4,pp.25-28.
10.Q. Hu, J. Wang, D. Yu, J. Cui, " Robust h∞ controller of tubular linear induction motor with an artificial neural network compensator," 2007 IEEE International Conference on Automation and Logistics, Aug. 2007, pp.1988-1993.
11.E. Guney and M. Demir, "A Comparative Velocity Control Study of Permanent Magnet Tubular Linear DC Motor by Using PID and Fuzzy-PID Controllers,"ICCAD’17, Hammamet-Tunisia, Jan. 2017, pp.391-395.
12.何芝強，PID控制器參數整定方法及其應用研究，碩士論文，浙江大學，中國，2005。
13.M. Viteckova and A. Vitecek, "Two-degree of freedom controller tuning for integral plus time delay plants," ICIC Express Letters, An Intemational Jourmal of Research and Surveys, Sep. 2008, vol. 2, no. 3, pp. 225-229.
14.M. Li, P. Zhou, Z. Zhao, J. Zhang, " Two-degree-of-freedom fractional order-PID controllers design for fractional order processes with dead-time,"ISA Transactions, Mar. 2016, vol. 61, pp. 147-154.
15.M. Araki and H. Taguchi, "Two-degree-of-freedom-PID controllers," Intemational Jourmal of Control ,Automation, and Systems, Dec. 2003, vol. 1, no. 4, pp. 401-411.
16.R. Sharma, P. Gaur and A.P. Mittal "Performance analysis of two-degree of freedom fractional order PID controllers for robotic manipulator with payload," ISA Transactions, Sep. 2015, vol. 58, pp. 279-291.
17.N. Dong, X. Li and Z. Chen, " Research on two-degree-of-freedom PID controller of permanent magnet synchronous motor based on fuzzy inference,"2017 20th International Conference on Electrical Machines and Systems, Aug. 2017, no. 5, pp.11-14.
18.L. Lin, " Optimal design for 2-DOF PID controller based on Maximum Entropy Estimation of Distribution Algorithm, " Proceedings of 2008 3rd International Conference on Intelligent System and Knowledge Engineering , Nov. 2008, pp.1338-1342.
19.Z. Pan, F. Dong, J. Zhao, L. Wang, Y. Feng, "Combined Resonant Controller and Two-Degree-of-Freedom PID Controller for PMSLM Current Harmonics Suppression,"IEEE Transactions on Industrial Electronics, Jan. 2018, vol. PP, pp.1-11.
20.D. Karaboga, An idea based on honey bee swarm for numerical optimization, technical report, University of Erciyes , 2005.
21.H. Narasimha, " Parallel artificial bee colony (PABC) algorithm, " World Congress on Nature and Biologically Inspired Computing, Coimbatore, Dec. 2009, pp.306-311.
22.Y. Cheng, " Modified ABC Algorithm in Virus Evolution, " 2016 International Symposium on Computer, Consumer and Control, July, 2016, pp.805-808.
23.張鈞彥，運用全域最佳訊息與活化策略改良人工蜂群演算法，碩士論文，中原大學資訊管理學系，桃園，2011。
24.黃少村，二次跳躍改良人工蜂群演算法，碩士論文，中原大學資訊管理學系，桃園，2011。
25.蔡宛庭，運用多樣性策略改良人工蜂群演算法，碩士論文，中原大學資訊管理學系，桃園，2011。
26.陳毅，運用差分策略改良人工蜂群演算法於高維度問題，碩士論文，中原大學資訊管理學系，桃園，2011。
27.M. Tuba, N, Bacanin, " Artificial Bee Colony Algorithm Hybridized with Firefly Algorithm for Cardinality Constrained Mean-Variance Portfolio Selection Problem, " Appl. Math. Inf. Sci. Nov. 2014, pp.2831-2844.
28.F. J. Lin, H. J. Hsieh, P. H. Chou, Y. S. Lin, " Digital signal processor-based cross-coupled synchronous control of dual linear motors via functional link radial basis function network," IET Control Theory & Applications , Mar. 2011, vol. 5, no. 4, pp. 552-564.
29.P. H. Chou, C. S. Chen, F. J. Lin, " DSP-Dased Synchronous Control of Dual Linear Motors via Sugeno Type Fuzzy Neural Network Compensator," Journal of the Franklin Institute , Apr. 2012, vol. 349, pp. 792-812.
30.L. Wang, Z. Zhang, X. Li, " The IT2FNN synchronous control for H-type gantry stage driven by dual linear motors," 2017 29th Chinese Control And Decision Conference , Jul. 2017, pp. 4716-4721.
31.李秉倫，線性永磁電機之最佳化設計與分析，博士論文，逢甲大學電機與通訊工程學系，台中，2013。
32.FileZilla FTP 伺服器，https://filezilla-project.org/
33.斯凱益公司，http://www.skyey.com.tw/product.php?pid=91
34.上銀公司， http://www.hiwinmikro.tw/hiwintree/Product_SubType.aspx?type=LMT2
35.上銀公司， http://www.hiwinsh.com/upload/1514336494_.pdf
36.上銀公司, http://www.hiwinmikro.tw/hiwintree/Product_SubType.aspx?type=D1
37.物理園，http://www.hk-phy.org/main.html
38.林志鴻，永磁線型同步馬達之驅動與智慧型控制，博士論文，私立中原大學電機工程學系，桃園，2001。
39.周柏寰，智慧型同動控制之龍門是定位平台，博士論文，國立東華大學電機工程學系，花蓮，2011。
40.李維平、李元傑、謝明勳，「以群中心略改良人工蜂群演算法」，資訊管理學報，第二十一卷，第一期，2014，第25-44頁。
41.Z. Liang, K. Hu, Q. Zhu, Z. Zhu, " An enhanced artificial bee colony algorithm with adaptive differential operators," Applied Soft Computing, Sep. 2017, vol. 58, pp. 480-494.
42.L. Cui, G. Li, Z. Zhu, Q. Lin, Z. Wen, N. Lu, K.C. Wong, J. Chen, " A novel artificial bee colony algorithm with an adaptive population size for numerical function optimization," Information Sciences, Nov. 2017, vol. 414, pp. 53-67.
43.G.R. Hank, F.G. Lobo, D.E. Goldberg, "The compact genetic algorithm," IEEE Trans. on Evolutionary Computation, Nov. 1999, vol. 3, pp. 287-297.
44.X. Gao, L. Sun, C.X. Zhang, S. Yang, " A Modified Particle Swarm Optimization Algorithm Based on Improved Chaos Search Strategy," International Symposium Computational Intelligence and Design, Chin, 2008, pp. 331-335.
45.林庭煥，自適應模糊滑模PI控制在XY平台軌跡應用，碩士論文，國立雲林科技大學電機工程學系，雲林，2017。