以模糊小腦模型為基底之智慧型控制系統設計與硬體實現

Design and Hardware Implementation of Fuzzy CMAC-Based Intelligent Control Systems

李欣懌(Hsin-Yi Li)

指導教授 ： 林志民

元智大學/電機通訊學院/電機工程學系/博士(2012年)

摘要

本論文提出了多種以模糊小腦模型控制器為基底之智慧型控制系統的設計方法，分別為模糊小腦模型控制器、小波模糊小腦模型控制器、自組識小波模糊小腦模型控制器以及Takagi-Suegeno-Kang (TSK)模糊小腦模型控制器。此外並結合模糊控制、適應性控制、步階回歸控制與強健控制理論發展具適應性與強健性智慧型控制系統來控制含有不確定項之非線性系統。在穩定度方面，考慮到步階回歸控制特有漸進性穩定特性，因此一個基於模糊小腦模型的步階回歸同步控制系統被提出，並對含有不確定項之非線性系統進行控制。上述中所提出的各種智慧型控制系統利用了最陡坡降法及李亞普諾夫穩定定理推導出系統參數的學習法則，因此可保證經由線上調整系統參數後均能使得系統趨向於穩定。最後，將所提出之智慧型控制系統分別應用於雙軸壓電陶瓷馬達、音圈馬達、Duffing混沌系統及Gyro混沌系統，經由硬體實作以及軟體模擬展示其追蹤控制效能及強健性。經由各種模擬與實做結果顯示，本論文所提出的智慧型控制系統在這些非線性控制系統能均達到令人滿意的控制性能。

關鍵字

模糊小腦模型 ； 李亞普諾夫穩定定理 ； 非線性系統

並列摘要

This dissertation proposes several fuzzy cerebellar-model-articulation-controller (CMAC) design methods, including fuzzy CMAC; wavelet fuzzy CMAC; self-organizing wavelet fuzzy CMAC and Takagi-Suegeno-Kang (TSK) fuzzy CMAC. Moreover, fuzzy control, adaptive control, backstepping control and robust control methods are integrated with fuzzy CMAC for the control applications of uncertain nonlinear systems. For the stability analysis, the backstepping method is a kind of gradual stability theory, hence fuzzy CMAC based backstepping control system is proposed for uncertain nonlinear systems. All the parameter learning algorithms of these fuzzy CMAC based intelligent control systems are derived based on the gradient descent method and Lyapunov stability theorem, thus the system stability can be guaranteed. Moreover, in order to demonstrate the tracking performance and robustness, these developed control systems are applied to some nonlinear control systems including the two-axis linear piezoelectric ceramic motor (LPCM), voice coil motor (VCM), Duffing chaotic system, and Gyro chaotic system. From the simulation and experimental results, the control schemes proposed in this dissertation have been shown to achieve satisfactory control performance for the considered nonlinear systems.

並列關鍵字

Fuzyy cerebellar model articulation controller ； Lyapunov stability theorem ； nonlinear systems

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