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| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 黃漢邦(Han-Pang Huang) | |
| dc.contributor.author | Po-Jen Cheng | en |
| dc.contributor.author | 鄭博任 | zh_TW |
| dc.date.accessioned | 2021-06-15T13:32:16Z | - |
| dc.date.available | 2021-03-08 | |
| dc.date.copyright | 2016-03-08 | |
| dc.date.issued | 2016 | |
| dc.date.submitted | 2016-02-02 | |
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| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/51380 | - |
| dc.description.abstract | 此論文將利用鍵結圖發展人機安全互動系統，並且應用在主動-被動變剛性彈性驅動器上。鍵結圖主要用來建立系統模型、設計模型匹配控制器與強健式錯誤偵測與隔離系統。為了將人機安全互動系統導入人因元素，我們利用Kinect偵測人類的骨架點，再利用使用者在空間中的位置與速度參數，來調控驅動器的剛性值，藉此達到人機安全互動的目的。
模型匹配控制器，能夠使受控系統的輸出響應追蹤至欲匹配的模型輸出響應。本論文提出完整鍵結圖模型匹配控制器的設計流程，並且應用在主動-被動變剛性彈性驅動器上。在論文中，模型匹配控制器用來控制受控系統的剛性值，以達到人類即使在與機器人碰撞時，也能夠保護人類不受傷害。若系統中的關鍵元件發生損壞或錯誤，將可能導致整體系統不穩定或發散。為了能夠使系統具有主動自我錯誤偵測，本論文發展強健式錯誤偵測與隔離系統，能夠有效偵測損壞的關鍵元件。並當偵測到元件發生錯誤被偵測後，能夠立即切換至合適的控制策略，以確保人類在安全環境下工作。 本論文提出的人與機器人安全互動系統，已在實際機器人系統上實現，所得結果符合預期。 | zh_TW |
| dc.description.abstract | This dissertation aims to develop an intelligent safe human–robot interaction (sHRI) system and apply it to an active–passive variable stiffness elastic actuator (APVSEA). A Bond graph is used to construct the system model, model matching controller (MMC), and robust fault detection and isolation system. To import the human factor into the sHRI system, Kinect was adopted to detect points on the human skeleton. Human joint positions and their velocities in space are used to dynamically adjust the actuator stiffness for sHRI.
MMC can force the output response of a plant to that of a reference. In this study, a complete MMC design flowchart is proposed. Moreover, an MMC was implemented in the APVSEA system. The MMC is used to change a plant stiffness so that if a human collides with a robot, the human will not sustain injuries. If any key system components break or fail, the entire system may destabilize or become divergent. Thus, this study develops a robust fault detection and isolation (RFDI) system for effectively detecting key component faults. When a fault in the system is detected, the RFDI system is switched to a suitable control system to guarantee human safety. In summary, this study proposes an intelligent sHRI system that can vary the stiffness of a plant and detect fault components. Furthermore, by importing the human factor, the sHRI system becomes even more smart. | en |
| dc.description.provenance | Made available in DSpace on 2021-06-15T13:32:16Z (GMT). No. of bitstreams: 1 ntu-105-D97522033-1.pdf: 5021822 bytes, checksum: aa0fd4dc819c81badb86df3e44cf6c9b (MD5) Previous issue date: 2016 | en |
| dc.description.tableofcontents | 致謝 i
摘要 ii Abstract iii List of Tables xi List of Figures xii Nomenclature xvi Chapter 1. Introduction 1 1.1. Motivation 1 1.2. Overview of the Dissertation 5 1.3. Contributions of the Dissertation 8 Chapter 2. Backgroud of Bond Graph 13 2.1. Introduction 13 2.2. Generalized Variables in Bond Graph Models 16 2.2.1. Power variables 16 2.2.2. Energy variables 17 2.3. Bonds and Ports 19 2.3.1. Power bond 19 2.3.2. Information bond 22 2.4. Bond Graph Elements 23 2.4.1. Storage elements 24 2.4.2. Resistors 25 2.4.3. Sources 25 2.4.4. Transformers and gyrators 26 2.4.5. Junctions 28 2.5. Positive Orientation 30 2.6. Causal Analysis 31 2.6.1. Causal constraints – fixed causality 32 2.6.2. Causal constraints – constrained causality 32 2.6.3. Causal constraints – preferred causality 33 2.6.4. Causal constraints – indifferent causality 33 2.6.5. Causal constraints – overview 34 2.6.6. Causal analysis procedure 34 2.7. Power Line 35 2.8. Causal Path Concept 36 2.9. Bi-Causal Bond Graph 38 2.9.1. The concept of bi-causal Bond graph 38 2.9.2. Bi-causal Bond graph 40 2.10. Bond Graph Modeling in LFT Form 42 2.10.1. LFT representation 42 2.10.2. LFT modeling of Bond graph elements 43 Chapter 3. Working Principle and Modeling of APVSEA 45 3.1. Introduction 45 3.2. Working Principle of Active-Passive Variable Stiffness Elastic Actuator 46 3.3. Model APVSEA by Bond graph 49 Chapter 4. Model Matching Control Design 53 4.1. Introduction 53 4.2. MMC Controller Design Flow 53 4.3. Design MMC Controller for APVSEA 56 4.3.1. Solvability checking 56 4.3.2. Inverse system 57 4.3.3. Reference model 58 4.3.4. Disturbance decouple problem (DDP) 60 4.3.5. Error dynamics 61 4.3.6. Asymptotic stability 62 4.4. Simulations 64 4.5. Experiments 66 4.6. Summary 71 Chapter 5. Robust Fault Detection and Isolation 73 5.1. Introduction 73 5.2. APVSEA Modeling with Key Mechanism Components 76 5.3. Robust Fault Detection and Isolation Strategy 77 5.3.1. Doubt index 79 5.3.2. Zero gravity control 82 5.4. Robust FDI Design for APVSEA 84 5.4.1. The effect of APVSEA element broken 84 5.4.2. Inverse model with uncertainty part 85 5.4.3. ARR equations and fault signature matrix 87 5.4.4. Doubt index design 90 5.4.5. Fault tolerance control 90 5.4.6. Zero gravity controller design 92 5.5. Experiments 94 5.5.1. Combination of adaptive FDI and doubt index 94 5.5.2. The experiment of zero gravity control 96 5.5.3. Robust fault detection and isolation 97 5.6. Summary 105 Chapter 6. Safe Human Robot Interaction using Kinect 107 6.1. Introduction 107 6.2. Safe Human Robot Interaction using Kinect and MMC 112 6.3. Calculating the Shortest Distance S 116 6.4. Generating Required Stiffness 119 6.5. Fuse Model using Bond Graph 121 6.6. Combining Fuse into APVSEA 124 6.7. RFDI Design 126 6.7.1. Inverse model with uncertainty part 126 6.7.2. ARR equations and fault signature matrix 128 6.8. The Fuse Switch Criterion 130 6.9. Experiments 132 6.9.1. Scenario 1: operator moving speed normally 133 6.9.2. Scenario 2: operator has fast moving 136 6.10. Summary 141 Chapter 7. Conclusions and Future Works 143 7.1. Conclusions 143 7.2. Future Works 145 7.2.1. Improving doubt index algorithm 145 7.2.2. Applying the sHRI function to a complete robot system 145 7.2.3. Considering mechatronics problem in RFDI 145 7.2.4. Implement zero gravity control to multi-DoF robot arm system 146 7.2.5. Integrate force control/position control into MMC 146 References 147 | |
| dc.language.iso | en | |
| dc.title | 利用鍵結圖發展人與機器人安全互動系統 | zh_TW |
| dc.title | Development of Safe Human Robot Interaction System using Bond Graph | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 104-1 | |
| dc.description.degree | 博士 | |
| dc.contributor.oralexamcommittee | 蔡清池(Ching-Chih Tsai),郭振華(Jen-Hwa Guo),葉廷仁(Ting-Jen Yeh),林顯易(Hsien-I Lin) | |
| dc.subject.keyword | 人機安全互動,主動-被動變剛性彈性驅動器,鍵結圖,模型匹配控制器,強健式錯誤偵測與隔離系統, | zh_TW |
| dc.subject.keyword | Safe Human-Robot Interaction,Active-Passive Variable Stiffness Elastic Actuator,Bond graph,Model Matching Control,Robust Fault Detection and Isolation, | en |
| dc.relation.page | 155 | |
| dc.rights.note | 有償授權 | |
| dc.date.accepted | 2016-02-02 | |
| dc.contributor.author-college | 工學院 | zh_TW |
| dc.contributor.author-dept | 機械工程學研究所 | zh_TW |
| 顯示於系所單位： | 機械工程學系 | |
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