跳到主要內容

臺灣博碩士論文加值系統

(44.200.82.149) 您好!臺灣時間:2023/06/11 01:55
字體大小: 字級放大   字級縮小   預設字形  
回查詢結果 :::

詳目顯示

: 
twitterline
研究生:盧俊明
研究生(外文):chun-ming Lu
論文名稱:以螞蟻群最佳化演算法設計模糊控制器及其軟/硬體實現
論文名稱(外文):Fuzzy Controller Design by Ant Colony Optimization Algorithm And Its Software/Hardware Implementation
指導教授:莊家峰
指導教授(外文):C.F.Juang
學位類別:碩士
校院名稱:國立中興大學
系所名稱:電機工程學系
學門:工程學門
學類:電資工程學類
論文種類:學術論文
論文出版年:2005
畢業學年度:93
語文別:英文
論文頁數:85
中文關鍵詞:學習法格子狀演算法產生器控制器
相關次數:
  • 被引用被引用:0
  • 點閱點閱:318
  • 評分評分:
  • 下載下載:59
  • 收藏至我的研究室書目清單書目收藏:0
本論文提出螞蟻群最佳化演算法應用於模糊控制器後件部的設計上,稱為ACO-FC,以增加模糊控制器設計效率及達到更好控制表現。在模糊控制器的設計上,我們先將前件部以格子狀切割完成,並列出每條法則所有後件部可挑選值。將一隻螞蟻走過的路徑當成整個模糊控制器後件部的一組組合。最佳後件部的選擇組合,則以螞蟻群最佳化法中的費洛蒙(pheromone)的濃度來決定。在倒單擺與溫度控制的模擬上,均顯示此法較基因法則的表現來的好。
所採用螞蟻群最佳化演算法並以硬體實現之。在此所採用的硬體為FPGA晶片。晶片内部主要包含有一個憶體單元,用以存放費洛蒙的濃度,一個16位元的亂數產生器,一個16位元除法器,和一些邏輯運算單元。為驗證晶片功能,我們將其應用於水溫控制的模擬上。
針對加強式模糊控制器的設計問題上,我們並將加強式模糊Q學習法結合到螞蟻群最佳化法中,簡稱FQ-ACO,以進一步增強螞蟻群最佳化法的表現。對每一條模糊法則可挑選的後件部值,我們均給定一個Q值,並以模糊Q學習法來條整Q值。整個控制器最佳後件部的組合,則同時根據費洛蒙及Q值來收尋。為了驗證FQ-ACO演算法的性能,我們分別模擬了水溫控制系統、磁浮系統及倒車入庫三個問題,並與單獨使用螞蟻群最佳化演算法及單獨使用模糊Q學習法作比較。而這些模擬結果都顯示FQ-ACO為一較有效的方法。
This thesis proposes the application of Ant Colony Optimization (ACO) algorithm to design the consequent parts of a fuzzy controller. This is called ACO-FC. The ACO-FC that is improved design efficiency and control performance of main objectives. For a fuzzy controller, we partition the antecedent part in grid-type, and then list all candidate consequent values of the rules. The path of an ant is regarded as one combination of consequent values selected from every rule. Searching of the best one among all combinations is based on thickness of the pheromone of ACO. Performance of the proposed method has been shown to be better than genetic algorithm on simulations of cart-pole balancing and temperature control problems.
The used ACO is hardware-implemented on FPGA (Field Programmable Gate Array) chip. The implemented chip contains one memory unit for depositing thickness of pheromone, one random number generator of 16 bits, one 16 bits divider, and some other logic operation units. To verify the performance of the chip, we have applied it on simulation of water bath temperature control.
For reinforcement fuzzy controller design problem, we propose the incorporation of Fuzzy-Q learning into ACO, called FQ-ACO, to further improve the performance of ACO. For all the candidates in the consequent part of a rule, we assign each one a corresponding Q-value. Update of the Q-value is based on fuzzy-Q learning. The best combination of consequent values of a fuzzy controller is searched according to both pheromone and Q-value. To verify the performance of FQ-ACO, reinforcement fuzzy control of water bath temperature control system, magnetic levitation control system, and truck back-upper control are simulated. Simulations on the three problems with ACO alone and fuzzy-Q alone are also performed, respectively. Performance of FQ-ACO is verified from the comparisons.
Abstract (in Chinese)………………………………………………….……i
Abstract (in English)…………………………………………………….ii
Acknowledgments………………………………………………....….…iv
Contents……..…………………………………………………………....v
List of Figures………………………………………………………….....ix
List of Tables……...………………………………………………………ix

Chapter 1: INTRODUCTION...…………...………………………1
1.1 Survey and Literature Review………………………………1
1.2 Thesis Organization……..……………………..………..6

Chapter 2 : Design of Fuzzy System by Ant Colony
Optimization…………………………………..... 7
2.1 Ant Colony Optimization (ACO)………………..…………7
2.2 Fuzzy System Design by Ant Colony Optimization (ACO-FC)…………………………………………………12
2.3 Simulations……………………………………………...22

Chapter 3 : FPGA Implementation……………………..…….36
3.1 Ant Algorithms for hardware Implementation..….…….37
3.2 Hardware Implementation………………………………...40
3.3 Experiment by FPGA-Based Ant algorithms……………...48

Chapter 4 : Reinforcement Fuzzy System Design by Incorporating Fuzzy Q-learning into
ACO……………………………..…..…….……..51
4.1 Learning Algorithms of Fuzzy Q-learning…..….……….51
4.2 Incorporation of Fuzzy Q-learning into ACO (FQ-ACO)...56

Chapter 5 : Simulations….…………………………………….64
5.1 Water temperature control……………………………….65
5.2 Magnetic levitation control ……………………………….68
5.3 Truck backer-upper control ……………………………….75

Chapter 6 : Conclusions…………...………………………….81
Bibliography………………………………………………….82
[1] D. E. Goldberg, Genetic Algorithms in Search Optimization and Machine Learning. Reading, MA:Addison-Wesley, 1989.
[2] J. K. Koza, Genetic Programming: On The Programming of Computers by Means of Natural Selection, MIT Press, Cambridge, MA, 1992.
[3] L. J. Fogel, “Evolutionary programming in perspective: The top-down view,” Computational Intelligence: Imitating Life, J. M. Zurada, R. J. Marks II and C. Goldberg, Eds, IEEE Press, Piscataway, NJ, 1994.
[4] I. Rechenberg, “Evolution strategy,” Computational Intelligence: Imitating Life, J. M. Zurada, R. J. Marks II and C. Goldberg, Eds, IEEE Press, Piscataway, NJ, 1994.
[7] O. Cord on, F. Herrera, F. Hoffmann and L. Magdalena, Genetic Fuzzy Systems: Evolutionary Tuning and Learning of Fuzzy Knowledge Bases, volume 19 of Advances in Fuzzy Systems – Applications and Theory, World Scientific, 2001.
[8] C. L. Karr, “Design of an adaptive fuzzy logic controller using a genetic algorithm,” Proc. the Fourth Int. Conf. Genetic Algorithms, pp. 450-457, 1991.
[9] A. Homaifar and E. McCormick, “Simultaneous design of membership functions and rule sets for fuzzy controllers using genetic algorithms,” IEEE Trans. Fuzzy Systems, vol. 3, no. 2, pp. 129-139, 1995.
[10] M. Dorigo, V. Maniezzo, and A. Colorni, “Ant System: Optimization by a Colony of Cooperating Agents,” IEEE Trans. on Systems, man, and cybernetics, Part B: Cybernetics, vol. 26, no. 1, February 1996.
[11] M. Dorigo, and L.M. Gambardella, “Ant Colony System: A Cooperative Learning Approach to the Traveling Salesman Problem” IEEE Trans. on Evolutionary Computation, vol. 1, no. 1, April 1997.
[12] M. Dorigo, and G. Di Caro, “Ant Colony Optimization: A new meta-heuristic” In P. J. Angeline, Z. Michalewicz, M. Schoenauer, Xin Yao, and A. Zalzala, editors, proceedings of the congress on Evolutionary Computation, vol.2, pages 1470-1477. IEEE Press, 1999.
[13] M. Dorigo, L.M. Gambardella, and G. Di Caro, “Ant Algorithms for Discrete Optimization” Artificial Life, vol.5, no 2, pp 137-172, 1999.
[14] A. Colorni, M. Dorigo, and V. Maniezzo, “Distributed optimization by ant colonies,” in Proc. ECAL91-Eur. Conf. Artificial Life, pp. 134-142. 1991.
[15] S. Lin and B. W. Kernighan, “An effective heuristic algorithm for the traveling salesman problem,” Oper. Res., vol. 21, pp. 498–516, 1973.
[16] V. Maniezzo, A. Colorni, and M. Dorigo, “The ant system applied to the quadratic assignment problem,” Universit´e Libre de Bruxelles, Belgium, Tech. Rep. IRIDIA/94-28, 1994.
[17] L. M. Gambardella, E. Taillard, and G. Agazzi, “Ant colonies for vehicle routing problems,” In D. Corne, M. Dorigo, and F. Glover, editors, New Ideas in Optimization. McGraw-Hill, 1999.
[18] L. F. Escudero, “An inexact algorithm for the sequential ordering problem,” European Journal of Operations Research, pp. 232–253, 1988.
[19] I. Watanabe, and S. Matsui, “Improving the performance of ACO algorithms by adaptive control of candidate set,” IEEE, Evolutionary Computation, conf., vol. 2, pp. 1355-1362, 2003.
[20] K. M. Sim, and W. H. Sun., “Ant colony optimization for routing and load-balancing: survey and new directions,” IEEE, on Systems, Man, and Cybernetics, Part A, vol. 33, no. 5, pp. 560-572, Sept. 2003.
[21] L. Jouffe, “Fuzzy inference system learning by reinforcement methods,” IEEE Trans. on Systems, Man, and Cybernetics, Part C, vol. 28, no. 3, pp. 338-355, Aug .1998.
[22] P.Y. Glorennec, and L. Jouffe, “ Fuzzy Q-learning ,” Proc. 6nd IEEE Int. Conf. Fuzzy Systems, vol. 2, pp. 659-617 July 1997.
[23] C. F. Juang, “Q-value based genetic reinforcement learning for fuzzy controller design,” The 12th IEEE Conf., Fuzzy Systems, vol. 1, pp. 185-189 May 2003.
[24] H. R. Berenji, “Fuzzy Q-learning: a new approach for fuzzy dynamic programming,” The 3th IEEE Int. Conf., Fuzzy Systems, vol. 1, pp. 486-491 June 1994.
[25] T. Hendtlass and M. Randall, “ A survey of ant colony and particle swarm meta-heuristics and their application to discrete optimization problems,” Proc. of The Inaugural Workshop on Artificial Life, pp. 15-25, 2001.
[26] Meng Joo Er, Chang Deng, “Online tuning of fuzzy inference systems using dynamic fuzzy Q-learning,” IEEE Trans. on Systems, Man and Cybernetics, Part B, vol. 34, on 3, pp. 1478 – 1489, June 2004.
[27] M. Guntsch, M. Middendorf, B. Scheuermann, O. Diessel, ElGindy, H. Schmeck, and K. So, “ Population based ant colony optimization on FPGA,” IEEE Int. Conf.Proc. Field-Programmable Technology, 2002 (FPT). pp. 125-132 Dec. 2002.
[28] D. Nguyen, B. Widrow, “ The truck backer-upper: An example of self-learning in neural network,” IEEE Contr. Syst. Mag., vol. 10, no.3, pp. 18-23, 1990.
QRCODE
 
 
 
 
 
                                                                                                                                                                                                                                                                                                                                                                                                               
第一頁 上一頁 下一頁 最後一頁 top
1. ‧ 莊素娥,〈純藝術的反叛者─顏水龍〉,《台灣美術全集6─ 顏水龍》,台北,藝術家出版社,1992。
2. ‧顏娟英,〈台灣早期西洋美術的發展〉,《藝術家雜誌》,台北,藝術家出版社,1989年五月號。
3. ‧謝里法,《日據時代台灣美術運動史》,台北,藝術家出版社,1992。
4. ‧席慕蓉,〈真山真水真畫圖─山川真貌的詮釋者陳慧坤〉,《台灣美術全集17─陳慧坤》,台北,藝術家出版社,1995。
5. ‧賴明珠,〈日治時期的「地方色彩」理念─以鹽月桃甫及石川欽一郎對「地方色彩」理念的詮釋與影響為例〉,《視覺藝術第三期》,台北,台北師院視覺藝術研究所,民89年5月。
6. ‧林惺嶽,〈跨越時代鴻溝的彩虹─論廖繼春的生涯及藝術〉,《台灣美術全集 4 廖繼春》,台北,藝術家出版社,1992,頁22。
7. ‧巴東,〈台灣西洋現代美術之發展源起〉,《國立歷史博物館學報 第11期》,台北,87年12月出版。
8. ‧王秀雄,〈台灣第一個近代雕塑家黃土水的藝術與風格探釋〉,《東海學報37卷》,台中,東海大學出版,民85年7月。
9. ‧黃朝謨,〈林克恭繪畫研究〉,《台灣美術全集─16 林克恭》,台北,藝術家出版社,1995。
10. ‧石守謙,〈人世美的紀錄者─陳進畫業研究〉,《台灣美術全集 2 陳進》,台北,藝術家出版社,1992。
11. ‧顏娟英,〈勇者的畫像─陳澄波〉,《台灣美術全集 1 陳澄波》,台北,藝術家出版社,1992,頁35。
12. ‧蔣勳,〈勞動者的頌歌─礦工畫家洪瑞麟〉,《台灣美術全集12─洪瑞麟》,台北,藝術家出版社,1993。
13. ‧林柏亭,〈典雅與鄉土兼融─郭雪湖的膠彩世界〉,《台灣美術全集9─郭雪湖》,台北,藝術家出版社,1993。
14. ‧王秀雄,〈台灣第一位近代雕刻家─黃土水的生涯與藝術〉,《台灣美術全集 19 黃土水》,台北,藝術家出版社,1996,頁34~35。
15. ‧顏娟英,〈展覽會上的畫家─呂基正〉,《台灣美術全集21─呂基正》,台北,藝術家出版社,1998。