淡江大學覺生紀念圖書館 (TKU Library)
進階搜尋


下載電子全文限經由淡江IP使用) 
系統識別號 U0002-2807201413241700
中文論文名稱 基於FPGA之硬體實現T-S模糊小腦模型控制應用於音量控制
英文論文名稱 FPGA Implementation of Takagi-Sugeno Fuzzy Cerebellar Model Articulation Volume Control
校院名稱 淡江大學
系所名稱(中) 電機工程學系碩士班
系所名稱(英) Department of Electrical Engineering
學年度 102
學期 2
出版年 103
研究生中文姓名 陳彥融
研究生英文姓名 Yen-Jung Chen
學號 601460263
學位類別 碩士
語文別 英文
口試日期 2014-07-03
論文頁數 42頁
口試委員 指導教授-劉寅春
委員-邱謙松
委員-李世安
中文關鍵字 T-S模糊  線性矩陣不等式  小腦模型控制器  現場可編程邏輯陣列  音量控制 
英文關鍵字 T-S fuzzy  Linear Matrix Inequalities (LMIs)  Field-programmable gate array (FPGA)  CMAC  Volume control 
學科別分類 學科別應用科學電機及電子
中文摘要 在本篇論文中,我們使用T-S模糊小腦模型控制器去追蹤控制因環境噪音而需要調整的音量大小。此控制器有下列幾項優點:
1. 利用LMI求出控制增益,使CMAC初始權重提升了準確性。
2. 基於LMI設計具有自適應能力的CMAC,允許時變參數在系統中。
3. 控制器能夠快速並且反覆的修正控制量。
最後在實驗階段,以FPGA做為實現的平台。將T-S模糊小腦模型控制器實現在FPGA上,並且應於蜂鳴器的音量控制。從實驗結果可知,系統表現良好的追蹤效能。
英文摘要 In this study, we use Takagi-Sugeno fuzzy cerebellar model articulation controller (T-S CMAC) for tracking volume which is need to adjusted due to environmental noise. This controller has the following advantages:
1. Using linear matrix inequalities (LMI) to calculate the control gain, it improves the accuracy which is CMAC of the initial weights.
2. In order to track the time-varying parameter in CMAC, we designed the controller via LMI which has strong adaptive ability.
3. It can quickly and repeatedly correction amount of control.
Finally, this study will use the field-programmable gate array (FPGA) to implement T-S CMAC algorithm in experiment. It will apply to adjust volume. In experiment results, we can see the tracking ability is well.
論文目次 Contents
Abstract in Chinese I
Abstract in English II
Contents III
List of Figures V
List of Tables VII
1 INTRODUCTION 1
1.1 Research Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2
1.1.1 Fuzzy system . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2
1.1.2 Linear matrix inequalities . . . . . . . . . . . . . . . . . . . . . . . . . . 3
1.1.3 Cerebellar model articulation controller with T-S fuzzy model . . . . . 4
1.2 Literature Review . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11
1.3 Problem Formulation and Motivations . . . . . . . . . . . . . . . . . . . 13
1.4 Organization of Thesis . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14
2 HARDWARE/SOFTWARE CO-DESIGN PLATFORM 15
2.1 DE0-Nano Platform . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15
2.2 DE0-Nano Hardware/Software Co-design . . . . . . . . . . . . . . . . . . 18
3 TAKAGI-SUGENO FUZZY CEREBELLAR MODEL ARTICULA-
TION CONTROLLER 20
3.1 Nominal Tracking Controller . . . . . . . . . . . . . . . . . . . . . . . . 20
3.2 Overall Controller Design . . . . . . . . . . . . . . . . . . . . . . . . . . 23
4 SYSTEM FLOW AND HARDWARE CIRCUIT DESIGN 27
4.1 Sound Sensor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28
4.2 Analog-to-Digital Converter . . . . . . . . . . . . . . . . . . . . . . . . . 29
4.3 Controller . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29
4.4 PWM Module and Buzzer . . . . . . . . . . . . . . . . . . . . . . . . . 32
4.4.1 PWM module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32
4.4.2 Buzzer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32
5 EXPERIMENT 34
5.1 Experiment Environment . . . . . . . . . . . . . . . . . . . . . . . . . . 34
5.2 Experiment Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34
6 CONCLUSIONS AND FUTURE WORKS 38
6.1 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38
6.2 Future Works . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38
References 40

List of Figures
1.1 CMAC basic structure . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
1.2 CMAC separate each input to each memory region . . . . . . . . . . . 6
1.3 CMAC structure with T-S fuzzy model . . . . . . . . . . . . . . . . . . 7
1.4 Hardware architecture . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13
2.1 The DE0-Nano board PCB and component diagram (top view) . . . . 17
2.2 The DE0-Nano board PCB and component diagram (bottom view) . . 17
2.3 SOPC design architecture . . . . . . . . . . . . . . . . . . . . . . . . . . 18
2.4 SOPC system design flow . . . . . . . . . . . . . . . . . . . . . . . . . . 19
4.1 Volume control architecture . . . . . . . . . . . . . . . . . . . . . . . . . 27
4.2 Sound sensor: (a) top view (b) bottom view . . . . . . . . . . . . . . . 28
4.3 Sound sensor circuit . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28
4.4 ADC signal conversion . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29
4.5 Range of human hearing . . . . . . . . . . . . . . . . . . . . . . . . . . . 30
4.6 System Structure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31
4.7 Magnetic buzzer (AC type) . . . . . . . . . . . . . . . . . . . . . . . . . 33
4.8 Buzzer driving circuit . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33
5.1 Tracking ability . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35
5.2 Response time . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35
5.3 Error value . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36
5.4 PWM signal in different situations . . . . . . . . . . . . . . . . . . . . 37

List of Tables
4.1 Electrical characteristics of buzzer . . . . . . . . . . . . . . . . . . . . . 33
參考文獻 [1] Y. Fu, H. Li, and M. Kaye, “Hardware/software codesign for a fuzzy autonomous road-following system,” IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews, vol. 40, no. 6, pp. 690–696, 2010.
[2] C.-F. Juang, C.-M. Lu, C. Lo, and C.-Y. Wang, “Ant colony optimization algorithm for fuzzy controller design and its fpga implementation,” IEEE Transactions on Industrial Electronics, vol. 55, no. 3, pp. 1453–1462, 2008.
[3] A. Rubaai, A. Ofoli, and D. Cobbinah, “Dsp-based real-time implementation of a hybrid h adaptive fuzzy tracking controller for servo-motor drives,” IEEE Trans- actions on Industry Applications, vol. 43, no. 2, pp. 476–484, 2007.
[4] L. Zadeh, “Fuzzy sets,” Information and control, vol. 8, no. 3, pp. 338–353, 1965. [5] R. Isermann, “On fuzzy logic applications for automatic control, supervision, and fault diagnosis,” IEEE Transactions on Systems, Man and Cybernetics, Part A: Systems and Humans, vol. 28, no. 2, pp. 221–235, 1998.
[6] F. S. Lin, “Integral fuzzy control and application on power converter,” Master’s
thesis, CYCU, 2003.
[7] K. Tanaka and M. Sugeno, “Stability analysis and design of fuzzy control systems,” Fuzzy Sets and Systems, vol. 45, no. 2, pp. 135–156, 1992.
[8] S. Boyd, L. El Ghaoui, E. Feron, and V. Balakrishnan, Linear matrix inequalities in system and control theory. Society for Industrial Mathematics, 1994, vol. 15.
[9] J. S. Albus, “A new approach to manipulator control: The cerebellar model articulation controller,” in (CMAC), Trans. Asme, Series G. Journal of Dynamic
System, Measurement and Control. Citeseer, 1975.
[10] C. shin Lin and C.-T. Chiang, “Learning convergence of cmac technique,” IEEE Transactions on Neural Networks, vol. 8, no. 6, pp. 1281–1292, 1997.
[11] Y. Kim and F. Lewis, “Optimal design of cmac neural-network controller for robot manipulators,” IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews, vol. 30, no. 1, pp. 22–31, 2000.
[12] T. Takagi and M. Sugeno, “Fuzzy identification of system and its applications to modelling and control,” IEEE Trans. Syst., Man, and Cyber, vol. 15, pp. 116–132, 1985.
[13] K. Lian, T. Chiang, C. Chiu, and P. Liu, “Synthesis of fuzzy model-based designs to synchronization and secure communications for chaotic systems,” IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, vol. 31, no. 1, pp. 66–83, 2001.
[14] A. Jadbabaie, A. Titli, and M. Jamshidi, “Fuzzy observer-based control of nonlinear systems,” in IEEE Conference on Decision and Control., Proceedings of the 36th, vol. 4. IEEE, 1997, pp. 3347–3349.
[15] K. Tanaka, T. Kosaki, and H. Wang, “Backing control problem of a mobile robot with multiple trailers: fuzzy modeling and lmi-based design,” IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews, vol. 28, no. 3, pp. 329–337, 1998.
[16] C. Kung and C. Liao, “Fuzzy-sliding mode controller design for tracking control of nonlinear system,” in American Control Conference, vol. 1. IEEE, 1994, pp. 180–184.
[17] H. Lam, F. Leung, and P. Tam, “Fuzzy control of dc-dc switching converters
based on ts modeling approach,” in Industrial Electronics Society. IECON'98.
Proceedings of the 24th Annual Conference of the IEEE, vol. 2. IEEE, 1998, pp. 1052–1054.
[18] D. Job, V. Shankararaman, and J. Miller, “Combining cbr and ga for designing fpgas,” in Third International Conference on Computational Intelligence and Multimedia Applications. ICCIMA '99. Proceedings. Third International Conference on, 1999, pp. 133–137.
[19] A. Savran and S. Unsal, “Hardware implementation of a feedforward neural network using fpgas,” in EGE University, Department of Electrical and Electronics Engineering, 2003.
[20] A. Ucar and A. Z. Alkar, “Hw/sw codesign of fpga-based neural networks,” in Proceedings of the Fifteenth Turkish Symposium on Arti_cial Intelligence and Neural Networks, 2006.
[21] Altera, “De0 nano development board website.” [Online]. Available:
http://www.altera.com/education/univ/materials/boards/de0-nano/unv-de0-nano-board.html?GSA pos=1&WT.oss r=1&WT.oss=de0%20nano
[22] Terasic, “Terasic website.” [Online]. Available: http://www.terasic.com.tw/tw/
[23] Altera, “De0-nano user manual.” [Online]. Available: ftp://ftp.altera.com/up/pub/Altera Material/12.1/Boards/DE0-Nano/DE0 Nano User Manual.pdf
[24] C.-S. Lin and C.-T. Chiang, “Learning convergence of cmac technique,” IEEE
Transactions on Neural Networks, vol. 8, no. 6, pp. 1281–1292, 1997.
[25] R.-J. Wai and L.-C. Shih, “Design of voltage tracking control for dc-dc boost converter via total sliding-mode technique,” IEEE Transactions on Industrial Electronics, vol. 58, no. 6, pp. 2502–2511, 2011.
[26] H. Wang, K. Tanaka, and M. Griffin, “An approach to fuzzy control of nonlinear systems: stability and design issues,” IEEE Transactions on Fuzzy Systems, vol. 4, no. 1, pp. 14–23, 1996.
[27] S. studio, “Loudness sensor sku:sen02281p.” [Online]. Available: http://www.seeedstudio.com/depot/Grove-Loudness-Sensor-p-1382.html?cPath=25 128
[28] W. hsiao ch’uan, Speech Signal Processing (Revised edition). Chuan Hwa Book Co., 2009.
[29] H. INC., “Magnetic buzzer (ac type).” [Online]. Available: http://www.hitpoint-buzzer.com/index.php?product=spec&series=pb
ac&db=pb series&id=92
[30] ——, “Magnetic buzzer (pb-0540mk-bq).” [Online]. Available: http://www.hitpoint-buzzer.com/download/PB-0540MK-BQ.pdf
論文使用權限
  • 同意紙本無償授權給館內讀者為學術之目的重製使用,於2014-07-29公開。
  • 同意授權瀏覽/列印電子全文服務,於2014-07-29起公開。


  • 若您有任何疑問,請與我們聯絡!
    圖書館: 請來電 (02)2621-5656 轉 2281 或 來信