跳到主要內容

臺灣博碩士論文加值系統

(3.231.230.177) 您好!臺灣時間:2021/07/28 21:46
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

我願授權國圖
: 
twitterline
研究生:簡宜興
研究生(外文):Yi-Hsing Chien
論文名稱:線上混合式智慧型控制器設計與應用上之研究
論文名稱(外文):Study on Design and Applications of On-Line Hybrid Intelligent Controllers
指導教授:李祖添李祖添引用關係王偉彥王偉彥引用關係練光祐
口試委員:謝哲光蘇順豐王文俊
口試日期:2012-07-12
學位類別:博士
校院名稱:國立臺北科技大學
系所名稱:電機工程系研究所
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:2012
畢業學年度:100
語文別:英文
論文頁數:99
中文關鍵詞:模糊類神經模型投影更新法則非仿射非線性系統
外文關鍵詞:fuzzy-neural modelprojection-update lawnonaffine nonlinear system
相關次數:
  • 被引用被引用:0
  • 點閱點閱:160
  • 評分評分:
  • 下載下載:0
  • 收藏至我的研究室書目清單書目收藏:0
本論文針對某一類一般型非仿射非線性且包含未知函數與外部干擾之系統,提出了經由T-S模糊類神經模型之新穎的線上模組化與控制方法。雖然針對非仿射非線性系統,適應性T-S模糊類神經控制器已經被一些文獻提出了。但是針對較複雜的未知非線性系統卻較少被提出來討論。第一個控制器設計方案是使用T-S模糊類神經模型去近似一個具有模組化誤差與外部干擾系統即所謂虛擬線性系統。對於第二個設計方案,一個線上觀測器為主的T-S模糊輸出追蹤控制技術以及一個改良式一般型投影更新法則是被提出。此新穎的設計概念包含T-S模糊控制器、觀測器以及藉由類神經網路的調整演算法是被提出來去改善系統的效能。改良式一般型投影更新法則是被提出來去避免參數飄移並且確保調整參數位在特定的區間。全部的控制方案可以保證閉迴路系統的輸出變數會漸進地追蹤到期望的輸出軌跡。對於第三個設計方案,一個針對未知非線性多變數動態系統的有效時間架構之新穎線上混合式直接/間接適應性模糊類神經網路控制器及估測器是被提出。根據工廠模型資訊與控制資訊的重要性與可行性,我們利用一個權重因子去合併直接與間接適應性模糊類神經網路控制器。因此,在設計過程中,此控制器的設計方案是較有彈性的。最後,本文中提出了一些數學的模擬結果來驗證所提出的線上混合式智慧型控制器之有效性。

This dissertation proposes some novel methods of online modeling and control via the Takagi-Sugeno (T-S) fuzzy-neural model for a class of general nonaffine nonlinear systems with uncertain functions and external disturbances. Although studies about adaptive T-S fuzzy-neural controllers have been made on some nonaffine nonlinear systems, little is known about the more complicated uncertain nonlinear systems. For the first controller design, a T-S fuzzy-neural model is used to approximate a so-called virtual linearized system (VLS) of the system, which includes modeling errors and external disturbances. For the second scheme, an online observer-based T-S fuzzy-output tracking-control technique and an improved generalized projection-update law are proposed. The novel design concept combining the T-S fuzzy controller, observer, and tuning algorithm by neural networks is proposed to improve system performance. The improved generalized projection-update laws which prevent parameters drift and confine adjustable parameters to the specified regions are developed. The proposed overall control scheme guarantees that the outputs of the closed-loop systems asymptotically track the desired output trajectories. For the third scheme, a novel time-efficient structure for online hybrid direct/indirect adaptive fuzzy-neural network (FNN) controller with stare observer of uncertain nonlinear multivariable dynamical systems is presented. According to the importance and viability of plant knowledge and control knowledge, a weighting factor is utilized to sum together the direct and indirect adaptive FNN controllers. Therefore, the controller design methodology is more flexible during the design process. Finally, in order to illustrate the effectiveness of the proposed on-line hybrid intelligent controllers, numerical simulation results are given in this dissertation.

ABSTRACT (In Chinese) i
ABSTRACT (In English) ii
ACKNOWLEDGEMENT iii
CONTENTS iv
LIST OF TABLES v
LIST OF FIGURES vi

CHAPTER 1 Introduction 1
1.1 Background and Motivation 1
1.2 Major Works 3
1.3 Dissertation Overview 4

CHAPTER 2 On-Line Intelligent Controller Design Using T-S Fuzzy-
Neural Modeling Approach 5
2.1 T-S Fuzzy-Neural Model for Virtual Linearized System (VLS) 5
2.2 Controller Design for On-Line Modeling and Robust Tracking 10
2.3 Simulation Results 19

CHAPTER 3 Observer-Based Intelligent Control Using T-S Fuzzy-
Neural Modeling and Generalized Projection-Update Laws 32
3.1 Problem Formulation and Takagi-Sugeno Fuzzy Model 32
3.2 Design of Takagi-Sugeno Fuzzy Observer 37
3.3 Improved Generalized Projection-Update Laws 40
3.4 Simulation Results 46

CHAPTER 4 Time-Efficient Structure for Observer-Based Direct/
Indirect Fuzzy-Neural Controller 57
4.1 Problem Formulation and Preliminary 57
4.2 Description of Time-Efficient Structure for Fuzzy-Neural
Network Systems 60
4.3 Hybrid Direct/Indirect Adaptive FNN Controller with Observer 62
4.4 Simulation Results 69

CHAPTER 5 Conclusions and Future Works 89
5.1 Conclusions 89
5.2 Suggestions for Further Research 90

REFERENCES 91

VITA 96

PUBLICATION LIST 97

[1] H. J. Lee, H, Kim, Y. H. Joo, W. Chang and J. B. Park, "A new intelligent digital redesign for T-S fuzzy system global approach," IEEE Transactions on Fuzzy Systems, vol. 12, no. 2, 2004, pp. 274-284.
[2] X. Liu and Q. Zhang, "Approaches to quadratic stability conditions and H-infinity control designs for T-S fuzzy systems," IEEE Transactions on Fuzzy Systems, vol. 11, no. 6, 2003, pp. 830-839.
[3] G. Feng, S. G. Cao, N. W. Rees and C. K. Chak, "Design of fuzzy control systems with guaranteed stability," Fuzzy Sets and Systems, vol. 85, 1997, pp. 1-10.
[4] S. G. Cao, N. W. Rees and G. Feng, "Stability analysis and design for a class of continuous-time fuzzy control systems," Int. J. Control, vol. 64, no. 6, 1996, pp. 1069-1087.
[5] C. W. Park and Y. W. Cho, "T-S model based indirect adaptive fuzzy control using online parameter estimation," IEEE Transactions on Systems, Man and Cybernetics-Part B, vol. 34, no. 6, 2004, pp. 2293-2302.
[6] N. Manamanni, B. Mansouri, A. Hamzaoui and J. Zaytoon, "Relaxed conditions in tracking control design for a T-S fuzzy model," Journal of Intelligent and Fuzzy Systems, vol. 18, no. 2, 2007, pp. 185-210.
[7] R.-J. Wai and Z.-W. Yang, "Adaptive Fuzzy Neural Network Control Design via a T-S Fuzzy Model for a Robot Manipulator Including Actuator Dynamics," IEEE Trans. on System Man and Cybernetics-Part B, vol. 38, no. 5, 2008, pp. 1326-1346.
[8] K. Tanaka and M. Sugeno, "Stability analysis and design of fuzzy control systems," Fuzzy Sets Systems, vol. 45, no. 2, 1992, pp. 135-156.
[9] H. O. Wang, K. Tanaka and M. F. Griffin, "An approach to fuzzy control of nonlinear systems: Stability and design issues," IEEE Transactions on Fuzzy Systems, vol. 4, 1996, pp. 14-23.
[10] H. Zhang, C. Li and X. Liao, "Stability analysis and H-infinity controller design of fuzzy large-scale systems based on piecewise Lyapunov functions," IEEE Transactions on Systems, Man and Cybernetics-Part B, vol. 36, no. 3, 2006, pp. 685-698.
[11] L. X. Wang, "Stable adaptive fuzzy control of nonlinear systems," IEEE Transactions on Fuzzy Systems, vol. 1, 1993, pp. 146-155.
[12] L. X. Wang, Adaptive Fuzzy Systems and Control: Design and Stability Analysis, Englewood Cliffs, NJ: Prentice-Hall, 1994.
[13] Y.-G. Leu, W.-Y. Wang and T.-T. Lee, "Observer-based direct adaptive fuzzy-neural control for nonaffine nonlinear systems," IEEE Transactions on Neural Networks, vol. 16, no. 4, 2005, pp. 853-861.
[14] I-H. Li and L.-W. Lee, "A hierarchical structure of observer-based adaptive fuzzy-neural controller for MIMO systems," Fuzzy Sets and Systems, vol. 185, no. 1, 2011, pp. 52-82.
[15] Y.-G. Leu and W.-Y. Wang, "Output feedback adaptive fuzzy control for manipulators," Dynamics of Continuous, Discrete and Impulsive Systems Series B, Applications and Algorithms, vol. 3, 2007, pp. 1194-1198.
[16] Y.-C. Hsueh, S.-F. Su, C. W. Tao and C.-C. Hsiao, "Robust L2-Gain Compensative Control for Direct-Adaptive Fuzzy-Control-System Design," IEEE Transactions on Fuzzy Systems, vol. 18, no. 4, 2010, pp. 661-673.
[17] W.-Y. Wang, Y.-H. Chien and I-H. Li, "An On-Line Robust and Adaptive T-S Fuzzy-Neural Controller for More General Unknown Systems," International Journal of Fuzzy Systems, vol. 10, no. 1, 2008, pp. 33-43.
[18] W.-Y. Wang, Y.-H. Chien, Y.-G. Leu and T.-T. Lee, "Adaptive T-S fuzzy-neural modeling and control for general MIMO unknown nonaffine nonlinear systems using projection update laws," Automatica, vol. 46, 2010, pp.852-863.
[19] Y.-G. Leu, T.-T. Lee and W.-Y. Wang, "Observer-based adaptive fuzzy-neural control for unknown nonlinear dynamical systems," IEEE Transactions on Systems, Man, and Cybernetics-Part B, vol. 29, no. 5, 1999, pp. 583-591.
[20] Y.-S. Lee, W.-Y. Wang and T.-Y. Kuo, "Soft computing for battery state-of-charge (BSOC) estimation in battery string systems," IEEE Transactions on Industrial Electronics, vol. 55, no. 1, 2008, pp. 229-239.
[21] Y.-J. Chen, W.-J. Wang and C.-L. Chang, "Guaranteed cost control for an overhead crane with practical constraints: fuzzy descriptor system approach," Engineering Applications of Artificial Intelligence, vol. 22, 2009, pp. 639-645.
[22] A. Mirzaei, M. Moallem, B. M. Dehkordi and B. Fahimi, "Design of an Optimal Fuzzy Controller for Antilock Braking Systems," IEEE Transactions on Vehicular Technology, vol. 55, no. 6, 2006, pp. 1725-1730.
[23] C. W. Tao, J. S. Taur, T. W. Hsieh and C. L. Tsai, "Design of a Fuzzy Controller With Fuzzy Swing-Up and Parallel Distributed Pole Assignment Schemes for an Inverted Pendulum and Cart System," IEEE Transactions on Control Systems Technology, vol. 16, no. 6, 2008, pp. 1277-1288.
[24] C. L. P. Chen and S. Xie, "Freehand drawing system using a fuzzy logic concept," Computer-Aided Design, vol. 28, no. 2, 1996, pp. 77-89.
[25] C. L. P. Chen and Y. H. Pao, "An Integration of Neural-Network and Rule-Based Systems for Design and Planning of Mechanical Assemblies," IEEE Transactions on Systems, Man and Cybernetics, vol. 23, no. 5, 1993, pp. 1359-1371.
[26] C. Lin, Q.-G. Wang and T. H. Lee, "H-infinity Output Tracking Control for Nonlinear Systems via T-S Fuzzy Model Approach," IEEE Transactions on Systems, Man and Cybernetics-Part B, vol. 36, no. 2, 2006, pp. 450-457.
[27] H. K. Lam and E. W. S. Chan, "Stability analysis of sampled-data fuzzy-model-based control systems," International Journal of Fuzzy Systems, vol. 10, no. 2, 2008, pp. 129-135.
[28] Y.-B. Zhao, G.-P. Liu and D. Rees, "Modeling and Stabilization of Continuous-Time Packet-Based Networked Control Systems," IEEE Transactions on Systems, Man and Cybernetics-Part B, vol. 39, no. 6, 2009, pp. 1646-1652.
[29] Y.-G. Leu, W.-Y. Wang and T.-T. Lee, "Robust Adaptive Fuzzy-Neural Controllers for Uncertain Nonlinear Systems," IEEE Transactions on Robotics and Automation, vol. 15, no. 5, 1999, pp. 805-817.
[30] N. Hovakimyan, E. Lavretsky and Chengyu Cao, "Dynamic inversion of multi-input nonaffine systems via time-scale separation," Proceedings of the 2006 American Control Conference, 2006, pp. 3594-3599.
[31] Y.-C. Hsueh and S.-F. Su, "Fuzzy Sliding Controller Design with Adaptive Approximate Error Feedback," International Journal of Fuzzy Systems, vol. 11, no. 1, 2009, pp. 36-43.
[32] Y.-J. Huang, T.-C. Kuo and S.-H. Chang, "Adaptive Sliding-Mode Control for Nonlinear Systems with Uncertain Parameters," IEEE Transactions on Systems, Man and Cybernetics-Part B, vol. 38, no. 2, 2008, pp. 534-539.
[33] M. C. Hwang and X. Hu, "A Robust Position/Force Learning Controller of Manipulators via Nonlinear H-infinity Control and Neural Networks," IEEE Transactions on Systems, Man and Cybernetics-Part B, vol. 30, no. 2, 2000, pp. 310-321.
[34] C. H. Lee, J. C. Chien, H. H. Chang, C. T. Kuo and H. H. Chang, "Direct adaptive backstepping control for a class of MIMO non-affine systems using recurrent neural networks," International Multi Conference of Engineers and Computer Scientists, vol. 1, 2009.
[35] X. Jia, D. Zhang, X. Hao and N. Zheng, "Fuzzy H-infinity Tracking Control for Nonlinear Networked Control Systems in T-S Fuzzy Model," IEEE Transactions on Systems, Man and Cybernetics-Part B, vol. 39, no. 4, 2009, pp. 1073-1079.
[36] C.-J. Lin, C.-H. Chen and C.-T. Lin, "A Hybrid of Cooperative Particle Swarm Optimization and Cultural Algorithm for Neural Fuzzy Networks and Its Prediction Applications," IEEE Transactions on Systems, Man, and Cybernetics- Part C: Applications and Reviews, vol. 39, no. 1, 2009, pp. 55-68.
[37] F.-J. Lin, S.-Y. Chen, L.-T. Teng and H. Chu, "Recurrent Functional-Link-Based Fuzzy Neural Network Controller with Improved Particle Swarm Optimization for a Linear Synchronous Motor Drive," IEEE Transactions on Magnetics, vol. 45, no. 8, 2009, pp. 3151-3165.
[38] C. W. Tao, M. L. Chan and T. T. Lee, "Adaptive fuzzy sliding mode controller for linear systems with mismatched time-varying uncertainties," IEEE Transactions on Systems, Man and Cybernetics-Part B, vol. 33, no. 2, 2003, pp.283-294.
[39] H. H. Choi, "LMI-Based Nonlinear Fuzzy Observer-Controller Design for Uncertain MIMO Nonlinear Systems," IEEE Transactions on Fuzzy Systems, vol. 15, no. 5, 2007, pp. 956-971.
[40] S. H. Kim and P. G. Park, "Observer-Based Relaxed H-infinity Control for Fuzzy Systems Using a Multiple Lyapunov Function," IEEE Transactions on Fuzzy Systems, vol. 17, no. 2, 2009, pp. 477-484.
[41] R.-J. Wai and C.-M. Liu, "Design of dynamic Petri recurrent fuzzy neural network and its application to path-tracking control of nonholonomic mobile robot," IEEE Trans. on Industrial Electronics, vol. 56, no. 7, 2009, pp. 2667-2683.
[42] T. Takagi and M. Sugeno, "Fuzzy identification of systems and its application to modeling and control," IEEE Transactions on Systems, Man and Cybernetics, vol. 15, 1985, pp. 116-132.
[43] L.-H. Chien, W.-Y. Wang, I-H. Li and S.-F. Su, "T-S Fuzzy Control for Uncertain Nonlinear Systems Using Adaptive Fuzzy Approach," IEEE International Conference on Fuzzy Systems, 2006, pp. 800-805.
[44] C.-A. Chen, H.-K. Chiang and J.-C. Shen, "Fuzzy Sliding Mode Control of a Magnetic Ball Suspension System," International Journal of Fuzzy Systems, vol. 11, no. 2, 2009, pp. 97-106.
[45] Y.-G. Leu, T.-T. Lee and W.-Y. Wang, "On-line tuning of fuzzy-neural network for adaptive control of nonlinear dynamical systems," IEEE Transactions on Systems, Man, and Cybernetics-Part B, vol. 27, 1997, pp. 1034-1043.
[46] P. A. Ioannou and J. Sun, Robust Adaptive Control, Englewood Cliffs, NJ: Prentice-Hall, 1996.
[47] Y.-Y. Hou, T.-L. Liao and J.-J. Yan, "Stability Analysis of Takagi-Sugeno Fuzzy Cellular Neural Networks with Time-Varying Delays," IEEE Transactions on Systems, Man and Cybernetics-Part B, vol. 37, no. 3, 2007, pp. 720-726.
[48] B. S. Chen, C. H. Lee and Y. C. Chang, "H-infinity tracking design of uncertain nonlinear SISO systems: Adaptive fuzzy approach," IEEE Transactions on Fuzzy Systems, vol. 4, 1996, pp. 32-43.
[49] S. I. Grossman and W. R. Derrick, Advanced Engineering Mathematics, Happer & Row, 1998.
[50] M. Vidyasagar, Nonlinear Systems Analysis, Prentice-Hall, 1993.
[51] C. T. Chen, Linear Systems Theory and Design, Holt, Rinehart & Winston, 1999.
[52] W.-Y. Wang, Y.-G. Leu and C.-C. Hsu, "Robust Adaptive Fuzzy-Neural Control of Nonlinear Dynamical Systems Using Generalized Projection Update Law and Variable Structure Controller," IEEE Transactions on Systems, Man and Cybernetics-Part B, vol.31, no.1, 2001, pp.140-147.
[53] P. A. Ioannou and A. Datta, "Robust Adaptive Control: A Unified Approach," Proceedings of the IEEE, vol. 79, no. 12, 1991, pp. 1736-1768.
[54] K. Hornick, M. Stinchcombe and H. White, "Multilayer feed-forward networks are universal approximators," Neural Networks, vol. 2, 1989, pp. 359-366.
[55] W.-Y. Wang, I-H. Li, L.-C. Chien and S.-F. Su, "On-line Modeling and Control via T-S Fuzzy Models for Nonaffine Nonlinear Systems Using A Second Type Adaptive Fuzzy Approach," International Journal of Fuzzy Systems, 2007, pp. 152-161.
[56] Martin T. Hagan, Howard B. Demuth and Mark Beale, Neutral Network Design, PWS Publishing Company, 1996.
[57] W.-Y. Wang, I-H. Li, M.-C. Chen, S.-F. Su and S.-B. Hsu, "Dynamic slip ratio estimation and control of antilock braking systems using an observer-based direct adaptive fuzzy-neural controller," IEEE Transactions on Industrial Electronics, vol. 56, no. 5, 2009, pp. 1746-1756.
[58] D. G. Luenberger, Linear and Nonlinear Programming. Reading, MA: Addison-Wesley, 1984.
[59] M. Vidyasagar, Nonlinear System Analysis, Englewood Cliffs, NJ: Prentice-Hall, 1993.
[60] F. Da, "Decentralized sliding mode adaptive controller design based on fuzzy neural networks for interconnected uncertain nonlinear systems," IEEE Transactions on Neural Network, vol. 11, no. 6, 2000, pp. 1471-1480.
[61] J. S. R. Jang, "ANFIS: Adaptive-network-based fuzzy inference systems," IEEE Transactions on Systems, Man, and Cybernetics, vol. 23, no. 3, 1993, pp. 665-685.
[62] C.-H. Wang, T.-C. Lin, T.-T. Lee and H.-L. Liu, "Adaptive hybrid intelligent control for uncertain nonlinear dynamical systems," IEEE Transactions on Systems, Man and Cybernetics-Part B, vol. 32, no. 5, 2002, pp. 583-597.
[63] T.-C. Lin and M.-C. Chen, "Adaptive hybrid type-2 intelligent sliding mode control for uncertain nonlinear multivariable dynamical systems," Fuzzy Sets and Systems, vol. 171, 2011, pp. 44-71.

QRCODE
 
 
 
 
 
                                                                                                                                                                                                                                                                                                                                                                                                               
第一頁 上一頁 下一頁 最後一頁 top