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研究生：	林琮暘 Lin, Tsung-Yang
論文名稱：	調適性類神經H∞ 模糊滑動控制器設計 Design of H∞ ANFIS-Based Fuzzy Sliding Mode Controller
指導教授：	黃正能 Hwang, Cheng-Neng
學位類別：	碩士 Master
系所名稱：	工學院 - 系統及船舶機電工程學系 Department of Systems and Naval Mechatronic Engineering
論文出版年：	2015
畢業學年度：	103
語文別：	英文
論文頁數：	136
中文關鍵詞：	ANFIS 、H∞控制理論、滑動控制、模糊控制
外文關鍵詞：	ANFIS, Fuzzy, H∞ control theory, Sliding mode control
相關次數：	點閱：129 下載：9
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在現實生活，大多數具物理意義的系統屬於非線性系統，利用回授線性化控制時，系統不確定性及干擾會影響到控制器的可行性，並使閉迴路系統難以達到預期性能，為了解決此類不確定性的問題，本文提出以Adaptive-Network-Based Fuzzy Inference System (ANFIS)為基礎的H_∞模糊滑動控制器來達到此預設性能。
在本文中，綜合控制器是由兩個部分組成，第一部分是以回授線性化為基礎的滑動控制器，其控制增益及觀測增益是由H_∞ 標準控制理論所求出，另一部分是以模糊控制為基礎的控制器，其歸屬函數係由ANFIS最佳化學習得到。在綜合控制器作用下，系統誤差會隨著第一部分控制器逼近滑動面，為確保追蹤性能以及預設性能，第二部分控制器可消除系統不確定性誤差。為確保本文之綜合控制器的有效性，本研究以里阿普諾夫穩定理論來證明閉迴路系統之穩定性，並以不等式來探討不確定性的最大容許範圍。
最後，本文以機械手臂來進行電腦模擬，追蹤預設路徑。從模擬結果可以看出，即使含有干擾及不確定項，系統仍保有良好的追蹤性能，依此可驗證控制器的可行性及強健性。

In practical, most of physical systems are nonlinear, and the feedback linearization method may be utilized to control the system. However, the system uncertainties and disturbances will affect the feasibility of the controller and make the closed-loop system hard to match the desired performance. To solve this problem, in this thesis, the ANFIS-based H_∞ Fuzzy Sliding Mode Controller is derived to form the proposed robust controller and to meet the pre-specified specifications.
The proposed controller is composed of two control components. One component is the feedback-linearization based sliding mode controller, in which the control gains and the observer gains are optimally chosen from the standard H_∞ control problem. The other component is the fuzzy-based controller, whose membership functions are optimally tuned by the Adaptive-Network Based Fuzzy Inference System (ANFIS). With the proposed controller, the system tracking errors will be forced to the sliding surface by the first component. To ensure the achievement of tracking performance and desired specifications, the errors resulted from system uncertainties will be eliminated by the second component. The closed-loop system stability of the proposed controller is proved by the Lyapunov’s stability criterion. The largest allowable scale of uncertainties is then explored by an inequality proposed in this research.
Finally, a robot manipulator with uncertainties is simulated to prove the feasibilities of the proposed composite controller.

Table of Contents
摘要	I
Abstract	II
致謝	III
List of tables	V
List of figures	VI
Chapter 1: Introduction	1
1 Motivation	1
2 Literature reviews	2
3 Thesis outline	4
Chapter 2: Sliding mode control theory	5
1 Introduction	5
2 Applied SMC theory	5
3 System description	7
4 SMC controller	10
5 The robustness of the SMC controller	11
Chapter3: Adaptive-Network-Based Fuzzy Inference System	15
1 Introduction	15
2Fuzzy control and neural network	15
2.1 Fuzzy control	15
2.1.1 Fuzzification interface	16
2.1.2 Fuzzy knowledge base	16
2.1.3 Decision-making logic	17
2.1.4 Defuzzification interface	17
2.2Neural network	17
2.2.1 Classification of neural networks	18
2.2.2 Operation and characteristic of neural networks	19
2.2.3 Back propagation neural networks	21
3 ANFIS	22
3.1 ANFIS structure	24
3.2 ANFIS toolbox	26
Chapter 4: H_∞ control theory	31
1 Preface	31
2 Concepts of H_∞ control theory	31
3 The variation approach	32
3.1 Augmented system	33
3.2 State feedback controller	35
3.3 State observer S_o (s)	36
4 Procedure of solving H_∞control problem	39
Chapter 5: H_∞ ANFIS-Based Fuzzy Sliding Mode Controller	40
1 System description	40
2 Sliding mode controller	41
3 Adaptive-Network-based Fuzzy Inference	44
3.1 Introdction of ANFIS structure	44
3.2 Generate fuzzy inference system	46
3.2.1 Loading data	47
3.2.2 Generating FIS structure	47
3.2.3 Train the FIS	47
3.2.4 Validating the trained FIS	48
4 Design of H_∞ ANFIS-based fuzzy sliding mode controller	50
5 Controller design step and procedure	66
Chapter 6: Simulation	68
1Design a fuzzy controller u_A	68
1.1Plant	68
1.2Fuzzy logic control	68
1.3 ANFIS-based fuzzy controller	75
2 System description	77
2.1 Reference trajectory	79
2.2 Design procedure	83
2.3 Conclusion of manipulator	104
3 System description	105
3.1 Submarine system description	105
3.2 Design procedure	110
Chapter 7: Conclusion	133
References	134

                                    

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校內：2018-08-05公開
校外：2019-08-05公開

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