臺灣博碩士論文加值系統

本論文研究兩大類的導引方式，第一類是比例型的導引律，其中又分為比例、擴增比例、特殊比例及真比例導引律四種傳統的比例型的導引律；第二類則是視線指引導引律。
比例型導引律在本論文是應用在魚雷導引上而且都有一個共通點：當魚雷追擊目標時，這些導引律的導引常數在追擊的過程中都是固定不變的。從導引系統的觀點來看，固定不變的導引常數並不是非常適用於多變的追擊閃避運動。由於模糊邏輯推理技術具備適應性推論能力，因此四種以模糊邏輯為基礎的導引律被提出，分別是模糊邏輯比例、模糊邏輯擴增比例、模糊邏輯特殊比例及模糊邏輯真比例導引律。這些以模糊邏輯為基礎的導引律本質上是一種適應性導引律。藉由模糊邏輯推理技術，我們發現不論在二度空間或三度空間中，以模糊邏輯為基礎的導引律，其終端均方根誤失距離都比傳統的導引律小。
視線指引導引律是應用在飛彈導引上，且提出模糊邏輯視線指引飛彈導引律的設計方法。先將模糊邏輯記憶以適應性網路模糊推論系統來訓練與學習；並配合以線上微調的方法隨時修正模糊邏輯記憶，以獲得更小的誤差距離。模擬結果顯示，這種方法能夠應付來自不同方向的目標，且能夠獲致較小的誤差距離。

In this thesis, two kinds of principal guidance laws are introduced. The first kind is the PN-type guidance laws, where four kinds of traditional PN-type guidance laws are introduced, which are proportional navigation (PN), augmented PN (APN), special PN (SPN) and true PN (TPN) guidance laws. The second kind is the command to line-of-sight (CLOS) guidance law.
We apply the PN-type guidance laws to the torpedo guidance in this thesis and these guidance laws have mutual character : when a torpedo pursues a target, the navigation constants of these guidance laws are invariable in the process of pursuit. For the concept of guidance system, invariable navigation constant is not so suitable for various pursuit-evasion motion. Since fuzzy logic inference technique possesses the adaptive inference scheme, four kinds of fuzzy-logic-based guidance laws are proposed. They are fuzzy-logic-based PN (named FPN), fuzzy-logic-based APN (named FAPN), fuzzy-logic-based SPN (named FSPN) and fuzzy-logic-based TPN (named FTPN) guidance laws. These fuzzy-logic-based guidance laws are essentially the kind of adaptive guidance laws. By fuzzy logic inference technique, it is observed that, the terminal RMS miss distances of fuzzy-logic-based guidance laws are smaller than those of traditional guidance laws in 2D and 3D space.
The fuzzy-logic-based command to line-of-sight (CLOS) guidance law is proposed. The fuzzy associated memory (FAM) are trained and learned by adaptive-network-based fuzzy inference system (ANFIS). An on-line tuning algorithm is also proposed to update the FAM so as to get smaller miss distance. The simulation results demonstrate that it can cope with the target coming from different directions and achieve small miss distance.

1 Introduction
1.1General Remark and Overview of Previous Work 1
1.2Motivation and Contributions of the Thesis 2
1.3Scope and Organization of the Thesis 3
2 Guidance Law Formulations and Fuzzy Control Theory
2.1Overview 4
2.2Formulations Derivation of SPN and TPN Guidance Laws 7
2.2.1TPN Guidance Law Formulations 8
2.2.2SPN Guidance Law Formulations 10
2.3Fuzzy Logic Control System 12
2.3.1Fuzzification Interface 13
2.3.2Decision-Making Logic 13
2.3.3Defuzzification 15
2.3.4Knowledge Base 17
3 Fuzzy-Logic-Based 2D Torpedo Guidance Laws Design
3.1Overview 18
3.2Torpedo Guidance Systems 19
3.3Fuzzy-Logic-Based Guidance Laws 20
3.3.1FPN Guidance Law 22
3.3.2FAPN Guidance Law 24
3.3.3Defuzzification 24
3.4Simulation Results 24
3.4.1Example 1 : the torpedo pursues the submarine 25
3.4.1.1FPN and PN 25
3.4.1.2FAPN and APN 26
3.5Summary 27
4 Fuzzy-Logic-Based 3D Torpedo Guidance Laws Design
4.1Overview 28
4.2Torpedo Guidance Systems 28
4.3Fuzzy-Logic-Based Guidance Laws 30
4.3.1FSPN Guidance Law 32
4.3.2FTPN Guidance Law 35
4.3.3Defuzzification 35
4.4Simulation Results 36
4.4.1Example 1 : The torpedo pursues the submarine with
longitudinally escaping 36
4.4.1.1FSPN and SPN 39
4.4.1.2FTPN and TPN 40
4.4.2Example 2 : The torpedo pursues the submarine with
laterally escaping 41
4.4.2.1FSPN and SPN 43
4.4.2.2FTPN and TPN 44
4.4.3 Example 3：The torpedo intercepts the submarine with
x-axis moving to toward 45
4.4.3.1FSPN and SPN 47
4.4.3.2FTPN and TPN 48
4.5Summary 49
5 Fuzzy-Logic-Based CLOS Guidance Law Design
5.1Overview 50
5.2Problem Formulation 52
5.3Fuzzy Logic Controller Design 54
5.4Simulation Result 59
5.5Summary 62
6 Conclusions and Suggestions for Future Research
6.1Conclusions 67
6.2Suggestions for Future Research 67
References 69

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