傳統可變結構系統中，加速到達模式之到達時間與降低滑動
模式之顫動現象是兩個重要卻相斥的課題，本研究採用指數趨近
模式與扇形區間滑動模式來解決這個問題。指數趨近控制係由設
計者自行規劃趨近過程之時間響應，可加速趨近時間並降低到達
模式受到系統參數變動及外部干擾的影響，以增加系統的強健性。
扇形區間滑動模式能有效的降低滑動過程的顫動現象及避免傳統
使用連續控制造成的系統穩態誤差。小腦模型控制器是一種以查
表方式獲得網路輸出的類神經計算技術，具備優越的區域類化能
力及快速的學習收斂速度。傳統小腦模型控制器採用輸入空間均
等量化方式無法實際反映函數在學習範圍內變化趨勢，本研究提
出結合資訊源熵與模糊推論之階層式多解析度量化策略，以獲得
良好的學習精準度、收斂性與較佳的記憶體使用效率。最後，本
研究提出一植基於扇形區間滑動模式之小腦模型控制器，其兼具
兩類控制法則的優點，以期提昇控制器之效能達到高性能的要求。

In the traditional variable structure system, hitting time reduction and chattering attenuation are two important but contradictory issues. The thesis employ exponential approach control rule and sector boundary sliding mode to resolve this conflict. A system should be reduced approach time and sensitivity to parameter variance and external disturbance by the exponential approach control rule. The dynamic response of the exponential approach time can be designed by the user himself. The control rule based on the sector boundary sliding mode can successfully attenuate the chattering phenomena and avoid steady-state of the system error. Cerebellar Mode Articulation Controller (CMAC) is a table look-up neuron-computing technique. It is good local generalization capability and convergence speed of learning is very fast. The conventional CMAC has the input space quantized into equal-size resolution without considering variation of the target function in different areas in the input space. In this study, an hierarchical quantization method with advantages of entropy and fuzzy inference is proposed for input space quantization. It is able to achieve better learning accuracy, convergence speed, and memory utilization efficiency. This thesis proposes a Cerebellar Mode Articulation Controller based sector boundary sliding mode. It combines the merits of the two control rules together. The demand of the high performance controller is achieved by using the design.

[1] U. Itkis , " Control systems of variable structure " , New York : John
Wieley , 1976.
[2] V. I. Utkin , " Sliding mode control design principles and applications to
electric drives " , IEEE Trans. on Indust. Elec. , vol. 40 , No. 1, pp. 23-
26 , 1993.
[3] V. I. Utkin ," Sliding mode in control and Optimization ", Springer
Verlag USA , 1992.
[4] V. I. Utkin , " Sliding modes and their applications in variable structure
system " , Moscow : MIR publishers , 1978.
[5] R. A. Decarlo, S. H. Zak , and G. P. Matthews," variable structure
control of nonlinear multivariable system：A tutorial ",Proceedings of
the IEEE, Vol. 76 , pp. 212-232 , 1988.
[6] J. J. E. Slotine and S. S. Sastry , " Tracking control of nonlinear systems
using sliding surfaces with application to robot manipulators " , Int. J.
Control , Vol. 38 , pp. 465-492 , 1983.
[7] Weibing Gao and James C. Hung , "Variable system Control of
Nonlinear systems : A new approach " , IEEE Trans. on Indust . Elec. ,
Vol. 40 , No. 1, pp.45-55 , 1993.
[8] John Y. Hung , Weibing Gao and James C. Hung , "Variable structure
control of : A survy " , IEEE Trans. on Indust . Elec. ,Vol. 40 , No. 1,
pp.2-22 , 1993.
[9] Fengxi Zhou and D.Grant Fisher, " Continuous sliding mode control " ,
INT. J. Control , vol. 55 , No. 2, pp. 313-386 , 1993.
[10] Kohonen T., "An Introduction to Neural Computer ", Neural Networks,
Vol. 1 , pp. 3-16 , 1988.
[11] Albus, J.S.,"A New Approach to Manipulator Control :The Cerebellar
Model Articulation Controller (CMAC) ", Journal of Dynamic Systems,
Measurement, and Control, Transactions of ASME, pp. 220-227 , 1975.
[12] Albus , J.S. ," Data Storage in the Cerebellar Model Articulation
Controller (CMAC) ",Journal of Dynamic Systems, Measurement, and
Controller, Transactions of ASME, pp. 228-233 , 1975.
[13] Chiman Kwan; Xu, R.; Wei Liu; Tan, R. ,"Nonlinear control of missile
dynamics Decision and Control ", Proceedings of the 37th IEEE
Conference, on Vol. 4 , pp. 4685 -4690 , 1998.
[14] Miller, T. W., Glanz, F. H. Kraft & L. G.," Application of a General
Learning Algorithm to the Control of Robotic Manipulators", The
International Journal of Robotic Research,Vol. 6,No.2, pp.84-98, 1987.
[15] Miller , W. T. & Aldrich , " Rapid Learning Using CMAC Neural
Networks: Real Time Control of an Unstable System",Proceedings of
the 5th IEEE International Symposium on Intelligent Control 1990,
Philadelphia, PA. , pp. 465-470 , 1990.
[16] Moody, J. , " Fast Learning in Multi- resolution Hierarchies ", Advance
in Neural Information Processing System, Vol. 1,(ed),D.S. Touretzky
, Morgan Kanfmann Publishers, pp. 29-38 , 1989.
[17] GAO Xiaozhi ; Wang Changhong; Gao, X.M.; Ovaska, S.J.," A New
CMAC Neural Network Model with Adaptive Quantization Input
Layer" , Signal Processing, 3rd International Conference, on Vol. 2 ,
pp.1417 -1420 , 1996.
[18] Kim, H. ; Lin , C.-S. , " Use of adaptive resolution for better CMAC
learning Neural Networks", IJCNN, International Joint Conference ,on
Vol. 1 , pp. 517 -522 , 1992.
[19] Menozzi, A.; Chow, M.-Y.," On the training of a multi-resolution
CMAC neural network. Industrial Electronics", ISIE '97., Proceedings
of the IEEE International Symposium ,on Vol. 3, pp. 1201 -1205 , 1997.
[20] Chih-Ming Chen, Hahn-Ming Lee & Yu-Rong Hsieh,"A New Learning
Model of Hierarchical CMAC Neural Networks", Proceedings of
Fourth National Conference on Artificial Intelligence and Applications,
pp.17-22 , 1999.
[21] D.Knuth,"Sorting and searching", The Art of Computer Programming
. Menlo Park, Calif. : Addison Wesley, Vol. 3, pp.506 , 1973.
[22] Ching-Tsan Chiang and Chun-Shin Lin, "CMAC with General Basis
Function ", Neural Network , Vol. 9 , No. 7 , pp. 1199-1211 , 1996.
[23] Shannon, C. E. ,"A Mathematical Theory of Communication.", Bell
System Technical Journal , pp. 27, 379-423, 623, 656. , 1948.
[24] Elias, P. ," Information Theory and Coding.", N. A bramson, Ed. New
York, NY : Mc graw-hill. , 1963.
[25] L. A. Zedah ," Fuzzy Sets ", Information and Control, Vol. 8, No. 3,
pp. 338-353 , 1965.
[26] 陳永平, "可變結構控制設計", 全華 , 民國八十八年九月
[27] 高為炳, "變結構控制理論基礎", 中國科學技術出版社
[28] 蘇崇彥, "無顫動積分式可變結構系統之設計", 碩士論文 , 國立
台灣師範大學工業教育研究所 , 民國八十三年六月
[29] 郝維華, "雙滑動模式控制" , 碩士論文 , 國立台灣師範大學工
業教育研究所, 民國八十三年六月.
[30] 王進德，蕭大全, "類神經網路與模糊控制理論入門", 全華 , 民
國八十三年九月
[31] 葉怡成,"類神經網路模式應用與實作", 儒林 ,民國八十九年三月
[32] 陳志銘, "植基於遺傳演算法之小腦模型直流伺服馬達控制系統設
計", 碩士論文 , 國立台灣師範大學工業教育研究所, 民國八十
六年六月.
[33] 邱棚護, "資料結構基礎", 儒林 , 民國七十九年一月
[34] 戴顯權, "資料壓縮", 松崗 , 民國八十九年二月
[35] 吳樂南，徐孟俠, "資料壓縮的原理與應用", 儒林 , 民國八十五
年五月
[36] 向墊正男，劉天祥，佟中仁, " FUZZY理論入門", 中國生產力中
心 , 民國八十六年四月
[37] 孫宗瀛，楊英魁, " FUZZY控制理論、實作與應用", 全華 , 民
國八十八年十二月