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              基于事件觸發機制的多自主水下航行器協同路徑跟蹤控制

              王浩亮 柴亞星 王丹 劉陸 王安青 彭周華

              王浩亮, 柴亞星, 王丹, 劉陸, 王安青, 彭周華. 基于事件觸發機制的多自主水下航行器協同路徑跟蹤控制. 自動化學報, 2024, 50(5): 1024?1034 doi: 10.16383/j.aas.c211163
              引用本文: 王浩亮, 柴亞星, 王丹, 劉陸, 王安青, 彭周華. 基于事件觸發機制的多自主水下航行器協同路徑跟蹤控制. 自動化學報, 2024, 50(5): 1024?1034 doi: 10.16383/j.aas.c211163
              Wang Hao-Liang, Chai Ya-Xing, Wang Dan, Liu Lu, Wang An-Qing, Peng Zhou-Hua. Event-triggered cooperative path following of multiple autonomous underwater vehicles. Acta Automatica Sinica, 2024, 50(5): 1024?1034 doi: 10.16383/j.aas.c211163
              Citation: Wang Hao-Liang, Chai Ya-Xing, Wang Dan, Liu Lu, Wang An-Qing, Peng Zhou-Hua. Event-triggered cooperative path following of multiple autonomous underwater vehicles. Acta Automatica Sinica, 2024, 50(5): 1024?1034 doi: 10.16383/j.aas.c211163

              基于事件觸發機制的多自主水下航行器協同路徑跟蹤控制

              doi: 10.16383/j.aas.c211163
              基金項目: 國家自然科學基金(51979020, 51909021, 51939001, 52071044), 國家青年拔尖人才計劃(36261402), 遼寧省博士科研啟動計劃(2023-BS-077), 遼寧省教育廳高等學?;究蒲许椖?LJKZ0044, LJKQZ2021007), 大連海事大學博聯科研基金(3132023616), 水路交通控制全國重點實驗室開放課題(SKLMTA-DMU2024Y3), 大連市科技局高層次人才創新項目(2020RQ013)資助
              詳細信息
                作者簡介:

                王浩亮:大連海事大學輪機工程學院副教授. 2021年獲得大連海事大學博士學位. 主要研究方向為多自主水下航行器路徑規劃和協同路徑跟蹤. E-mail: haoliang.wang12@dlmu.edu.cn

                柴亞星:大連海事大學輪機工程學院碩士研究生. 2018年獲得南陽理工學院學士學位. 主要研究方向為多自主水下航行器協同路徑跟蹤. E-mail: yaxingchai@dlmu.edu.cn

                王丹:大連海事大學船舶電氣工程學院教授. 2001年獲得香港中文大學博士學位. 主要研究方向為控制理論及其在海洋航行器中的應用. 本文通信作者. E-mail: dwang@dlmu.edu.cn

                劉陸:大連海事大學船舶電氣工程學院副教授. 2018年獲得大連海事大學博士學位. 主要研究方向為多水面船制導與控制. E-mail: luliu@dlmu.edu.cn

                王安青:大連海事大學船舶電氣工程學院副教授. 2020年獲得香港城市大學和哈爾濱工業大學博士學位. 主要研究方向為不確定非線性系統, 事件觸發機制與協同控制. E-mail: anqingwang@dlmu.edu.cn

                彭周華:大連海事大學船舶電氣工程學院教授. 2011年獲得大連海事大學博士學位. 主要研究方向為多水面無人船協同控制. E-mail: zhpeng@dlmu.edu.cn

              Event-triggered Cooperative Path Following of Multiple Autonomous Underwater Vehicles

              Funds: Supported by National Natural Science Foundation of China (51979020, 51909021, 51939001, 52071044), Top-notch Young Talents Program of China (36261402), Doctoral Scientific Research Program of Liaoning Province (2023-BS-077), Basic Scientific Research Project of Higher Education Department of Liaoning Province (LJKZ0044, LJKQZ2021007), Bolian Research Funds of Dalian Maritime University (3132023616), Open Project of State Key Laboratory of Maritime Technology and Safety (SKLMTA-DMU2024Y3), and Dalian Science and Technology Bureau High-level Talent Innovation Project (2020RQ013)
              More Information
                Author Bio:

                WANG Hao-Liang Associate professor at the College of Marine Engineering, Dalian Maritime University. He received his Ph.D. degree from Dalian Maritime University in 2021. His research interest covers path planning and cooperative path following of multiple autonomous underwater vehicles

                CHAI Ya-Xing Master student at the College of Marine Engineering, Dalian Maritime University. She received her bachelor degree from Nanyang Institute of Technology in 2018. Her main research interest is cooperative path following of multiple autonomous underwater vehicles

                WANG Dan  Professor at the College of Marine Electrical Engineering, Dalian Maritime University. He received his Ph.D. degree from Chinese University of Hong Kong in 2001. His research interest covers control theory and its applications in marine vehicles. Corresponding author of this paper

                LIU Lu  Associate professor at the College of Marine Electrical Engineering, Dalian Maritime University. She received her Ph.D. degree from Dalian Maritime University in 2018. Her main research interest is guidance and control of multiple marine surface vehicles

                WANG An-Qing Associate professor at the College of Marine Electrical Engineering, Dalian Maritime University. She received her Ph.D. degree from City University of Hong Kong and Harbin Institute of Technology in 2020. Her research interest covers uncertain nonlinear systems, event-triggered mechanism and cooperative control

                PENG Zhou-Hua Professor at the College of Marine Electrical Engineering, Dalian Maritime University. He received his Ph.D. degree from Dalian Maritime University in 2011. His main research interest is cooperative control of multiple unmanned surface vehicles

              • 摘要: 針對考慮外部海洋環境擾動和內部模型不確定性的多自主水下航行器(Autonomous underwater vehicle, AUV), 研究其在通信資源受限和機載能量受限下的協同路徑跟蹤控制問題. 首先, 針對水聲通信信道窄造成的通信資源受限問題, 設計一種基于事件觸發機制(Event-triggered mechanism, ETM)的協同通信策略; 然后, 針對模型不確定性和海洋環境擾動問題, 設計一種基于事件觸發機制的線性擴張狀態觀測器(Extended state observer, ESO)來逼近水下航行器的未知動力學, 并降低了系統采樣次數; 最后, 針對機載能量受限問題, 設計一種基于事件觸發機制的動力學控制律, 在保證控制精度的前提下, 降低了執行機構的動作頻次, 從而節省了能量消耗. 應用級聯系統穩定性分析方法, 分別驗證了閉環系統是輸入狀態穩定的且系統不存在Zeno行為. 仿真結果驗證了所提基于事件觸發機制的多自主水下航行器協同路徑跟蹤控制方法的有效性.
              • 圖  1  垂直面參考坐標系

                Fig.  1  Vertical plane reference coordinate system

                圖  2  基于事件觸發的協同路徑跟蹤控制器結構圖

                Fig.  2  Architecture of event-triggered cooperative path following controller

                圖  3  協同路徑跟蹤性能效果

                Fig.  3  Cooperative path following performance effect

                圖  4  路徑參數$\chi_{i}$

                Fig.  4  Path variables $\chi_{i}$

                圖  5  垂直面內協同路徑跟蹤誤差

                Fig.  5  Cooperative path following errors in vertical plane

                圖  6  速度估計效果

                Fig.  6  Velocity estimation effect

                圖  7  擾動估計

                Fig.  7  Disturbance estimation

                圖  8  通信觸發事件

                Fig.  8  Communication triggering events

                圖  9  AUV1的速度觸發事件

                Fig.  9  Velocity triggering events of AUV1

                圖  10  AUV1的控制輸入觸發事件

                Fig.  10  Control input triggering events of AUV1

                表  1  觸發次數

                Table  1  Triggering times

                觸發內容 事件觸發 時間觸發 采樣
                周期
                (s)
                百分比
                最大值
                (%)
                AUV1 AUV2 AUV3 AUV$i$
                ($i$=1, 2, 3)
                協同次數($\chi_{i}$) 91 102 124 10 000 0.04 1.24
                采樣次數($u_{i}$) 324 352 420 10 000 0.04 4.20
                采樣次數($q_{i}$) 286 363 297 10 000 0.04 3.63
                執行次數($\tau_{iu}$) 585 592 451 10 000 0.04 5.92
                執行次數($\tau_{iq}$) 487 523 553 10 000 0.04 5.53
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                        • 收稿日期:  2021-12-07
                        • 錄用日期:  2022-06-23
                        • 網絡出版日期:  2022-09-26
                        • 刊出日期:  2024-05-20

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