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研究生:洪瑞鴻
研究生(外文):HORNG, JUI HONG
論文名稱:類神經網路應用於某類未知參數非線性系統適應控制之研究
論文名稱(外文):Research on the adaptive control of a class of unknown nonlinear systems using neural networks
指導教授:謝哲光謝哲光引用關係
指導教授(外文):HSIEH, JER GUANG
學位類別:博士
校院名稱:國立中山大學
系所名稱:電機工程研究所
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:1996
畢業學年度:84
語文別:中文
論文頁數:1
中文關鍵詞:多層類神經網路適應控制奇異擾動系統李亞普諾夫理論
外文關鍵詞:Multilayered neural networkAdaptive controlSingularly
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本篇論文, 在探討某類未知參數非線性動態系統, 利用類神經網路處理系
統穩定度和輸出追蹤的問題. 對於輸出追蹤, 提出兩組控制器設計方式,
其中一組為切換控制加多層類神經網路, 另一組為切換控制加CMAC, 使得
閉回路系統的輸出逐漸逼近期望輸出軌跡. 對於系統穩定度, 則利用多層
類神經網路構建一非線性適應控制器, 處理某類非線性非時變奇異擾動系
統, 使得該系統的軌跡, 從有界的初始狀態, 皆能沿著設計的 manifold
到達穩定原點. 對於所提的控制方式都由電腦模擬加以印證.
In this dissertation, the stabilization and tracking problems
for several classes of unknown nonlinear dynamic systems using
neural networks are investigated. For tracking problems,
without a priori knowledge of the system parameter values, the
proposed controllers, one of which consisting of the sliding
control and the multilayered neural network and the other
consisting of the sliding control and the Cerebeller Model
Arithmetic Computer (CMAC) network, are proposed such that the
outputs of the closed- loop systems asymptotically track the
desired output trajectories. For the stabilization problems,
multilayered neural networks are used to construct a nonlinear
adaptive feedback controller for a class of nonlinear time-
invariant singularly perturbed systems with fast actuators such
that the trajectories of the feedback-controlled system,
starting from the bounded initial states, are steered along the
integral manifold to a bounded set centered at the origin. The
Lyapunov approach is employed throughout the dissertation. Some
computer simulation results are provided to show the
effectiveness of the proposed control schemes.
COVER
CONTENTS
ACKNOWLEDGMENT
ABSTRACT
CHAPTER I INTRODUCTION
1.1 Motivation
1.2 History Review
1.3 Brief Sketch of the Contents
CHAPTER II NONLINEAR CONTROLLER DESIGN THCHNIQUES
2.1 Adaptive Control
2.2 Input-Output Linearization
2.3 Sliding Control
CHAPTER III NEURAL NETWORKS
3.1 Fundamentals of Neural Networks
3.2 Backpropagation Approach
3.3 CMAC Neural Networks
CHAPTER IV ADAPTIVE OUTPUT TRACKING OF A CLASS OF UNKNOWN NONLINEAR SYSTEMS USING NEURAL NETWORKS
4.1 Problem Statement
4.2 Adaptive Tracking Controller Design
4.3 Illustrative Examples
CHAPTER V ADAPTIVE TRACKING CONTROL OF A CLASS OF NONLINEAR SYSTEMS USING CMAC NETWORK
5.1 Problem Statement
5.2 Nonadaptive Tracking Control
5.3 Adaptive Tracking Control via a CMAC Network
5.4 Illustrative Example
CHAPTER VI STABILIZATION OF NONLINEAR SINGULARLY PERTURBED SYSTEMS USING MULTILAYERED NEURAL NETWORKS
6.1 Problem Formulation
6.2 Controller Design
6.3 Illustrative Example
CHAPTER VII CONCLUSIONS AND DISCUSSIONS
REFERENCES
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