臺灣博碩士論文加值系統

本論文對於無線網路連結的多異質三輪或四輪麥卡輪型機器人系統，提出分散式智慧型協同編隊控制之方法學與其實作技術。經由簡單地描述多機器人編隊系統、兩種異質輪型機器人的運動學與動力學模型與Wi-Fi結構拓樸後，兩種分散式領導跟隨架構之智慧型協同編隊控制方法被提出，以達成多機器人隊形保持與協同追蹤。第一種控制方法為結合遞迴二型模糊類神經網路(recurrent interval type-2 fuzzy neural networks)、協同追蹤、適應倒逆步(adaptive backstepping)與順滑模式控制之智慧型協同分散式編隊控制法則。第二種控制方法為整合輸出遞迴二型模糊類神經網路(output recurrent interval type-2 fuzzy neural networks)、Lyapunov穩定度分析與協同追蹤控制之智慧型指數穩定分散協同編隊控制律。上述兩種編隊控制法則之可行性及有效性可利用電腦模擬與實際實驗來加以驗證。本文所提及之方法對於從事多機器人編隊控制的研究者與工程人員而言，可提供實而有用的參考價值。

This thesis proposes methodologies and techniques for distributed consensus formation control of uncertain networked heterogeneous multiple three-wheeled or four-wheeled Mecanum omnidirectional robots (MWORs). After brief descriptions of formation control system, kinematic and dynamic models of MWORs and Wi-Fi communication topology, two distributed leader-follower consensus formation control methods are proposed to achieve formation keeping and consensus tracking. One is that an intelligent consensus cooperative formation control law is derived by combining recurrent interval type-2 fuzzy neural networks (RIT2FNNs), adaptive backstepping, sliding-mode control and consensus tracking. The other is that an intelligent exponential consensus distributed formation control law with collision and obstacle avoidance is established by integrating online learning of output recurrent interval type-2 fuzzy neural networks (ORIT2FNNs), consensus tracking, and Lyapunov analytical techniques. The effectiveness and merits of the two proposed control laws are examined and verified through several computer simulations and experimental results on the built formation control system. The aforementioned methods and system techniques may provide solid and useful references for researchers and engineers working for multi-robot or multi-agent systems.

摘 要 i
Abstract ii
Contents iii
List of Figures vi
List of Tables x
Nomenclature xi
List of Abbreviations xii
Chapter 1 Introduction 1
1.1 Introduction 1
1.2 Literature Review 3
1.2.1 Related Work on Cooperative Formation Control 3
1.2.2 Related Work on Heterogeneous Omnidirectional Wheel Robots 4
1.2.3 Related Work on RIT2FNN 4
1.2.4 Related Work on ORIT2FNN 5
1.2.5 Related Work on Backstepping and Sliding-Mode Approach 5
1.3 Motivation and Objectives 6
1.4 Main Contributions 7
1.5 Thesis Organization 8
Chapter 2 Formation System Design and Implementation 9
2.1 Introduction 9
2.2 Formation System Structure 10
2.2.1 Graph of multi-HOWR Formation System 10
2.2.2 Graph of HOWR in Formation 10
2.3 Description of the HOWR in formation 12
2.3.1 Mechatronic Structure of HOWR 12
2.3.2 ARM-based Controller 15
2.3.3 Single-Board Computer 16
2.3.4 Dynamixel MX-64AR Servomotors 18
2.3.5 Encoders and Odometry 19
2.3.6 Omnidirectional Wheels 20
2.3.7 TTL-to-RS485 Signal Board 21
2.3.8 Power supply for single HOWR 23
2.4 Modeling a Multi-HOWR System 25
2.5 Problem Formulations 26
2.6 Kinematic Formation Control 28
2.7 Experimental Results and Discussion 31
2.7.1 Experimental Results of Odometry 32
2.7.2 Experimental Results of the Kinematic Formation Control 41
2.7.3 Experimental Results of the Obstacle Detection 43
2.8 Concluding Remarks 45
Chapter 3 Intelligent Adaptive Backstepping Cooperative Formation Control Using RIT2FNN 46
3.1 Introduction 46
3.2 Dynamic Model of the Unified HOWR 46
3.2.1 Modeling a Car-Like Four-Wheeled MWOR 47
3.2.2 Modeling a Three-wheeled SWOR 49
3.23 Modeling a HOWR in a Unified Framework 51
3.3 RIT2FNN Function Approximation 52
3.4 Intelligent Adaptive Backstepping Cooperative Formation Control Using RIT2FNN 56
3.5 Simulation Results and Discussion 62
3.6 Experimental Results and Discussion 65
3.7 Concluding Remarks 68

Chapter 4 Intelligent Distributed Exponential Consensus Formation Control Using ORIT2NN 69
4.1 Introduction 69
4.2 Dynamic Model of the Unified HOWR 69
4.3 ORIT2FNN Function Approximation 70
4.4 Intelligent Distributed Exponential Consensus Formation Control Using ORIT2NN 72
4.5 Unified Collision and Obstacle Avoidance 76
4.5.1 Unified Collision and Obstacle Avoidance 76
4.5.2 Stability Analysis of the Formation Control Law with Collision and Obstacle Avoidance 78
4.6 Simulation Results and Discussion 80
4.7 Experimental Results and Discussion 84
4.8 Concluding Remarks 86
Chapter 5 Conclusions and Recommendations 88
5.1 Conclusions 88
5.2 Recommendations 90
References 91

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