臺灣博碩士論文加值系統

本論文提出兩種多輸入多輸出系統之智慧型控制器設計方法。首先對於線性化的多輸入多輸出系統，本文提出適應性回歸型模糊類神經控制器設計方法可以克服系統的參數變動及耦合現象。再者，利用可變結構滑動模式提出適應性模糊滑動模式控制器設計，應用於非線性多輸入多輸出系統。這兩種控制方法都基於李亞普諾夫定理推導出控制器參數調節機制，可以確保系統之穩定性。最後舉幾個應用實例進行模擬，證實所提出控制器的控制性能。

This thesis presents two intelligent controller designs for multi-input multi-output (MIMO) systems. First, for the linearized MIMO systems, the adaptive recurrent fuzzy neural network controller design method is developed to deal with the plant parameter variations and coupling problems. Then, based on the variable structure sliding mode, an adaptive fuzzy sliding mode controller is designed to deal with MIMO nonlinear systems. For these control system design, the adaptive laws of the controller parameters are derived based on Lyapunov function, so that the system stability can be guaranteed. Finally, several application examples are simulated to illustrate the effectiveness of the proposed design methods.

摘要 i
Abstract ii
誌謝 iii
Contents iv
List of Figures vi
Nomenclature vii
1. Introduction
1.1 General Remark and Overview of Previous Work 1
1.2 Organization of This Thesis 4
2. Adaptive Recurrent Fuzzy Neural Network Control for Linearized MIMO Systems
2.1 Overview 5
2.2 Problem Formulation 6
2.3 MIMO linearized system 7
2.4 Recurrent Fuzzy Neural Network Architecture 8
2.5 Recurrent Fuzzy Neural Network Controller Design 11
2.6 Stabilizing Adaptive Laws for RFNN 14
2.7 Simulation Result 18
2.8 Summary 23
3. Adaptive Fuzzy Sliding Mode Control for Nonlinear MIMO Systems
3.1 Overview 32
3.2 Problem formulation and sliding mode control 33
3.3 Design of the fuzzy sliding mode controller 36
3.4 Adaptive Fuzzy system 40
3.5 Learning algorithm 42
3.6 Simulation results 46
3.7 Summary 49
4. Conclusions and Suggestions for Future Research
4.1 Conclusions 56
4.2 Suggestions for Future Research 56
Reference 58
Autobiography 65

[1] C. C. Lee, “Fuzzy logic in control systems: Fuzzy logic controller, Part I,” IEEE Trans. Syst., Man, Cybern., vol. 20, no. 2, pp. 404—415, 1990.
[2] C. C. Lee, “Fuzzy logic in control systems: Fuzzy logic controller, Part II,” IEEE Trans. Syst., Man, Cybern., vol. 20, no. 2, pp. 419—435, 1990.
[3] S. I. Horikawa, T. Furuhashi, and Y. Uchikawa, “On fuzzy modeling using fuzzy neural networks with the back-propagation algorithm,” IEEE Trans. Neural Networks, vol. 3, no. 5, pp. 801—806, 1992.
[4] J. S. Jang, “ANFI: Adaptive-network-based fuzzy inference system,” IEEE Trans. Syst., Man, Cybern., vol. 23, no. 3, pp. 665—685, 1993.
[5] C. T. Lin, “Neural-network-based fuzzy logic control and decision system,” IEEE Trans. Comput., vol. 40, no. 12, pp. 1320—1336, 1991.
[6] L. X. Wang and J. M. Mendel, “Fuzzy basis functions, universal approximation, and orthogonal least-squares learning,” IEEE Trans. Neural Networks, vol. 3, no. 5, pp. 807—814, 1992.
[7] J. L. Castro, “Fuzzy logical controllers are universal approximators,” IEEE Trans. Syst., Man, Cybern., vol. 25, no. 4, pp. 629—635, 1995.
[8] B. S. Chen, C. H. Lee, and Y. C. Chang, “ tracking design of uncertain nonlinear SISO systems: Adaptive fuzzy approach,” IEEE Trans. Fuzzy Syst., vol. 4, no. 1, pp. 32—43, 1996.
[9] G. A. Rovithakis and M. A. Christodoulou, “Adaptive control of unknown plants using dynamical neural networks,” IEEE Trans. Syst., Man, Cybern., vol. 24, no. 3, pp. 400—412, 1994.
[10] K. S. Narendra and K. Parthasarathy, “Identification and control of dynamical systems using neural networks,” IEEE Trans. Neural Networks, vol. 1, no. 1, pp. 4—27, 1990.
[11] L. X.Wang, “Stable adaptive fuzzy control of nonlinear systems,” IEEE Trans. Fuzzy Syst., vol. 1, no. 2, pp. 146—155, 1993.
[12] L. X. Wang, Adaptive Fuzzy Systems and Control: Design and Stability Analysis, Prentice Hall, N.J., U.S.A, 1994.
[13] C. H. Wang, W. Y. Wang, T. T. Lee, and P. S. Tseng, “Fuzzy B-spline membership function (BMF) and its applications in fuzzy-neural control,” IEEE Trans. Syst., Man, Cybern., vol. 25, no. 5, pp. 841—851, 1995.
[14] Y. G. Leu, T. T. Lee, and W. Y. Wang, “Robust adaptive fuzzy-neural controllers for uncertain nonlinear systems,” IEEE Trans. Robot. Automat., vol. 15, no. 5, pp. 805—817, 1999.
[15] J. T. Spooner and K. M. Passino, “Stable adaptive control using fuzzy systems and neural networks,” IEEE Trans. Fuzzy Syst., vol. 4, no. 3, pp. 339—359, 1996.
[16] X. J. Ma and Z. Q. Sun, “Output tracking and regulation of nonlinear system based on Takgi-Sugeno fuzzy model,” IEEE Trans. Syst., Man, Cybern., vol. 30, no. 1, pp. 47—59, 2000.
[17] A. S. Park, W. Yu, E. N. Sanchez, and J. P. Perez, “Nonlinear adaptive trajectory tracking using dynamic neural networks,” IEEE Trans. Neural Networks, vol. 10, no. 6, pp. 1402—1411, 1999.
[18] H. Lee and M. Tomizuka, “Robust adaptive control using a universal approximator for SISO nonlinear systems,” IEEE Trans. Fuzzy Syst., vol. 8, no. 1, pp. 95—106, 2000.
[19] C. Y. Su and Y. Stepanenko, “Adaptive control of a class of nonlinear systems with fuzzy logic,” IEEE Trans. Fuzzy Syst., vol. 2, no. 4, pp. 285—294, 1994.
[20] C. H. Lee and C. C. Teng, “Identification and control of dynamic systems using recurrent fuzzy neural networks,” IEEE Trans. Fuzzy Syst., vol. 8, no. 4, pp. 349-366, 2000.
[21] P. A. Mastorocostas and J. B. Theocharis, “A recurrent fuzzy-neural model for dynamic system identification,” IEEE Trans. Syst., Man, Cybern. B, vol. 32, no. 2, pp. 176-190, 2002.
[22] C. M. Lin and C. F. Hsu, “Recurrent neural network adaptive control of wing-rock motion,” J. Guid., Contr., Dyna., vol.25, no. 6, pp.1163-1165, 2002.
[23] S. C. Sivakumar, W. Robertson and W. J. Philips, “On-line stabilization of block-diagonal recurrent neural networks,” IEEE Trans. Neural Networks, vol. 10, no.1, pp. 167-175, 1999.
[24] Y. Li, N. Sundararajan and P. Saratchandran, “Stable neuro-flight-controller using fully tuned radial basis function neural networks,” J. Guid., Contr., Dyna., vol.24, no. 4, pp.665-674, 2001.
[25] Y. Gao and M. J. Er, “Adaptive intelligent control of MIMO nonlinear systems based on generalized fuzzy neural network,” Int. Joint Conf. Neural Networks, vol. 3, pp. 2333-2338, 2002.
[26] S. V. Emelyanov, “Control of first order delay systems by means of an astatic controller and nonlinear correction,” Autom. Remote Control, no. 8, pp. 983—991, 1959.
[27] V. I. Utkin, “Variable structure systems with sliding modes,” IEEE Trans. Automat. Contr., vol. AC-22, pp. 212—222, 1977.
[28] K. D. Young, V. I. Utkin, and U. Ozguner, “A control engineer’s guide to sliding mode control,” IEEE Trans. Contr. Syst. Technol., vol. 7, pp. 328—342, May 1999.
[29] J. Y. Huang, W. Gao, and J. C. Hung, “Variable structure control: A survey,” IEEE Trans. Ind. Electron., vol. 40, pp. 1—9, Feb. 1993.
[30] A. S. I. Zinober, Variable Structure and Lyapunov Control. Berlin, Germany: Springer-Verlag, 1994.
[31] K. K. Young, Variable Structure Control for Robotics and Aerospace Systems. Amsterdam, The Netherlands: Elsevier, 1993.
[32] K. S. Narendra and S. Mukhopadhyay, “Adaptive control using neural networks and approximate models,” IEEE Trans. on Neural Networks, vol. 8, no. 3, pp. 475-485, 1997.
[33] J. J. E. Slotine and W. Li, Applied Nonlinear Control, Prentice-Hall, Englewood Cliffs, NJ, 1991.
[34] D. E. Williams and B. Friedland, “Modern control theory for design of autopilots for bank-to-turn missiles,’’ Amer, Contr. Conf., pp. 1130-1136, 1986.
[35] D. M. McDowell, G. W. Irwin, G. Lightbody, and G. McConnell, “Hybrid Neural adaptive control for bank-to-turn missiles,’’ IEEE Trans. Contr. Syst., vol. 5, no. 3, pp. 297-308, 1997.
[36] L. X. Wang, A Course in Fuzzy Systems and Control, Englewood Cliffs, NJ: Prentice-Hall, 1997.
[37] J. Yeh and R. Langari, Fuzzy Logic- Intelligence, Control and Information, Englewood Cliffs, NJ: Prentice-Hall, 1999.
[38] H. O. Wang, K. Tanaka, and M. F. Griffin, “An approach to fuzzy control of nonlinear systems: stability and design issues,” IEEE Trans. Fuzzy Systems, vol. 4, no. 1, pp. 14-23, 1996.
[39] R. Palm, “Robust control by fuzzy sliding mode,” Automatica, vol. 30, no. 9, pp. 1429-1437, 1994.
[40] S. W. Kim and J. J. Lee, “Design of a fuzzy controller with fuzzy sliding surface,” Fuzzy Sets and Systems, vol. 71, no. 3, pp.359-369, 1995.
[41] X. Yu, Z. Man, and B. Wu, “Design of fuzzy sliding-mode control systems,” Fuzzy Sets and Systems, vol. 95, no. 3, pp. 295-306, 1998.
[42] B. J. Choi, S. W. Kwak, and B. K. Kim, “Design of a single-input fuzzy logic controller and its properties,” Fuzzy Sets and Systems, vol. 106, no. 3, pp. 299-308, 1999.
[43] B. S. Chen and C. H. Lee, “H∞ tracking design of uncertain nonlinear SISO systems: adaptive fuzzy approach,” IEEE Trans. Fuzzy Systems, vol. 4, no. 1, pp. 32-43, 1996.
[44] C. K. Lin and S. D. Wang, “Robust self-tuning rotated fuzzy basis function controller for robot arms,” IEE Pro,. Control Theory and Applications, vol. 144, no. 4, pp. 293-298, 1997.
[45] C. C. Wong, B. C. Huang, and J. Y. Chen, “Rule regulation of indirect fuzzy controller design,” IEE Pro, Control Theory and Applications, vol. 145, no. 6, pp. 513-518, 1998.
[46] C. C. Wong and J. Y. Chen, “Fuzzy control of nonlinear systems using rule adjustment,” IEE Proc, Control Theory and Applications, vol. 146, no. 6, pp. 578-584, 1999.
[47] Y. C. Chang and B. S. Chen, “Robust tracking designs for both holonomic and nonholonomic constrained mechanical systems: adaptive fuzzy approach,” IEEE Trans. Fuzzy Systems, vol. 8, no. 1, pp. 46-66, 2000.
[48] H. Lee and M. Tomizuka, “Robust adaptive control using a universal approximator for SISO nonlinear systems,” IEEE Trans. Fuzzy Systems, vol. 8, no. 1, pp. 95-106, 2000.
[49] S. D. Wang and C. K. Lin, “Adaptive tuning of the fuzzy controller for robots,” Fuzzy Sets and Systems, vol. 110, no. 3, pp. 351-363, 2000.
[50] Y. C. Chang, “Robust tracking control for nonlinear MIMO systems via fuzzy approaches,” Automatica, vol. 36, no. 9, pp. 1535-1545, 2000.
[51] C. L. Hwang and C. Y. Kuo, “A stable adaptive fuzzy sliding-mode control for affine nonlinear systems with application to four-bar linkage systems,” IEEE Trans. Fuzzy Systems, vol. 9, no. 2, pp. 238-252, 2001.
[52] V. I. Utkin, ‘‘Variable structure systems with sliding modes,’’ IEEE Trans. Autom. Control, vol. 22, no. 2, pp. 212-222, 1997.
[53] V. Utkin, J. Guldner, and J. Shi, Sliding Mode Control in Electromechanical systems, Taylor and Francis, London UK, 1999.
[54] J. J. E. Slotine and W. LI, Applied nonlinear control, Prentice-Hall, Englewood Cliffs, New Jersey, 1991.
[55] R. A. Horn and C. R. Johnson, Matrix Analysis, Cambridge University Press, Cambridge, 1985.
[56] Y. R. Hwang and M. Tomizuka,“Fuzzy smoothing algorithms for variable structure systems,”IEEE Trans. Fuzzy Syst., vol. 2, no. 4, pp. 277-284, 1994.
[57] L. Shi and S. K. Singh,“Decentralized adaptive controller design for large-scale systems with higher order interconnections,”IEEE Trans. Automat. Contr., vol. 37, no. 8, pp. 1106-1118, Aug. 1992.
[58] D. M. McDowell, G. W. Irwin, G. Lightbody, and G. McConnell, “Hybrid Neural adaptive control for bank-to-turn missiles,’’ IEEE Trans. Contr. Syst., vol. 5, no. 3, pp. 297-308, 1997.
[59] D. Kim and Y. Kim, “Robust variable structure controller design for fault tolerant flight control,” J. Guid., Contr., Dyna., vol. 23, no. 3, pp. 430-437, 2000.