開始日期: 2023-12-16

　　課時安排: 7周在線小組科研學習+5周不限時論文指導學習

　　適合人群

　　適合年級 (Grade): 大學生及以上

　　適合專業 (Major): 機械工程、自動化與控制理論、機器人學、人工智能、智能制造等專業或者希望修讀相關專業的學生

　　學生需要具備微積分、信號與系統基礎，并會使用MATLAB編程語言

　　導師介紹

　　Harrison

　　牛津大學 University of Oxford終身教授

　　導師Harrison現任牛津大學工程科學系教授，兼由14名博士生和博士后組成的研究小組組長、哈里斯曼徹斯特學院講師;曾任麻省理工學院機械工程系客座研究員。擔任Science, Nature Communications, PLoS journals, ACS journals, Royal Society Interface, IEEE Transactions等十多種知名學術期刊審稿人，UKRI, NSF, Swiss National Science Foundation等機構獎金評審人。開源Chi.Bio實驗自動化平臺的創始人和發明人，約100個學術和工業實驗室使用(https://chi.bio/)。OxVent(由來自牛津大學和倫敦國王學院的工程師和醫生組成的多學科團隊)首席技術官兼電子團隊負責人。曾在德國知名研究機構DESY擔任工程師，致力于下一代粒子加速技術。曾在美國航天局艾姆斯研究中心擔任研究科學家，從事南極環境項目以及火星和木衛二的行星任務。曾獲得Philip Leverhulme獎(英國國家獎每三年頒發給五名工程師，表彰那些工作已經獲得國際認可的早期職業研究人員)、EPSRC新視野獎(開發控制細胞進化的機器人顯微鏡新技術)等多個獎項。Pro.Harrison is currently a professor of the College of Engineering Sciences, Oxford University, and the leader of the research team composed of 14 doctoral students and postdoctoral students, as well as a lecturer of Harris Manchester College; Previously served as a visiting researcher in the Department of Mechanical Engineering at Massachusetts Institute of Technology. Served as a reviewer for over ten well-known academic journals such as Science, Nature Communications, PLoS journals, ACS journals, Royal Society Interface, IEEE Transactions, and as a prize reviewer for institutions such as UKRI, NSF, and Swiss National Science Foundation. Founder and inventor of the open-source Chi Bio experimental automation platform, used by approximately 100 academic and industrial laboratories( https://chi.bio/ )。 Chief Technical Officer and Electronic Team Leader of OxVent, a multidisciplinary team of engineers and doctors from Oxford University and King's College London. Formerly worked as an engineer at the renowned German research institution DESY, dedicated to the next generation of particle acceleration technology. He once worked as a research scientist in the Ames Research Center of NASA, engaged in the Antarctic environment project and the planetary missions of Mars and Europa. He has won multiple awards, including the Philip Leverhulme Award (which is awarded every three years to five engineers by the British National Award to recognize early career researchers whose work has been internationally recognized), the EPSRC New Horizons Award (which develops new technologies for robotic microscopes that control cell evolution), and more.

　　任職學校

　　牛津大學(University of Oxford)，是一所位于英國牛津的世界頂尖公立研究型大學。其與劍橋大學并稱為牛劍，是羅素大學集團成員，被譽為“金三角名?！焙汀癎5超級精英大學”。牛津大學是英語世界中最古老的大學，也是世界上現存第二古老的高等教育機構。該校涌現了一批引領時代的科學巨匠，培養了大量開創紀元的藝術大師、國家元首，其中包括28位英國首相及數十位世界各國元首、政商界領袖。牛津大學在數學、物理、醫學、法學、商學等多個領域擁有崇高的學術地位及廣泛的影響力，被公認為是當今世界最頂尖的高等教育機構之一。截止至2019年3月，牛津大學的校友、教授及研究人員中，共有72位諾貝爾獎得主(世界第九)、3位菲爾茲獎得主(世界第二十)、6位圖靈獎得主(世界第九)。牛津大學名列2023QS英國最佳大學排名第2名、2023QS世界大學排名第4名、2022QS英國最佳大學排名第1名、2022QS世界大學排名第2名、2022軟科世界大學學術排名第7位。

　　項目背景

　　當前，云計算、物聯網和大數據等新興信息通信技術快速發展，為機器人的高端制造應用提供了新的思路和發展契機。數字化、網絡化、智能化融合創新引領未來工業發展已取得廣泛共識。我國在《十四五規劃和2035年遠景目標綱要》也明確提出要“加快推進制造強國、質量強國建設。深入實施智能制造和綠色制造工程。發展服務型制造新模式。推動制造業高端化智能化綠色化”。而傳統的人工以及專機加工。加工質量一致性差、效率低且只能實現小批量生產，已無法滿足智能制造需求。區別于傳統工業機器人簡單、重復性勞動，高端制造機器人是更信息化、網絡化、智能化、柔性化的機器人。在智能工廠中，機器人的作業環境日益非結構化。生產的動態性對機器人的環境感知與控制技術提出了越來越高的要求。在未來的智能工廠中，機器人也將得到更加廣泛的應用，其控制性能不僅影響到最終的加工效果，還影響到加工過程的安全。高精、高效、高柔性、高穩定性的控制策略能為工件的安全制造提供堅實的保障。Currently, emerging information and communication technologies such as cloud computing, the Internet of Things, and big data are rapidly developing, providing new ideas and development opportunities for high-end manufacturing applications of robots. The integration and innovation of digitization, networking, and intelligence have achieved broad consensus in leading future industrial development. In the 14th Five Year Plan and the 2035 Long Range Goals Outline, China also explicitly proposes to "accelerate the construction of a strong manufacturing and quality country, deepen the implementation of intelligent manufacturing and green manufacturing projects, develop new service-oriented manufacturing models, and promote the high-end, intelligent, and green manufacturing industry. And traditional manual and specialized machine processing. The consistency of processing quality is poor, the efficiency is low, and only small batch production can be achieved, which can no longer meet the needs of intelligent manufacturing. Unlike traditional industrial robots with simple and repetitive labor, high-end manufacturing robots are more information-based, networked, intelligent, and flexible robots. In intelligent factories, the working environment of robots is becoming increasingly unstructured. The dynamic nature of production places increasing demands on the environmental perception and control technology of robots. In future intelligent factories, robots will also be more widely used, and their control performance not only affects the final processing effect, but also affects the safety of the processing process. The control strategy of high precision, efficiency, flexibility, and stability can provide a solid guarantee for the safe manufacturing of workpieces.

　　項目介紹

　　本項目主要研究自動化控制和數字技術的原理。通過學習，學生將能夠了解離散控制系統相關知識，掌握機器人系統等數字技術中自動控制器的設計和分析方法。具體內容涵蓋控制方法論、控制系統的數學分析、控制設計方法、離散控制系統及其前沿應用。為以后學生能夠在機電一體化、機器人等智能制造領域深入研究打下堅實的基礎。This project mainly studies the principles of automation control and digital technology. Through learning, students will be able to understand knowledge related to discrete control systems and master the design and analysis methods of automatic controllers in digital technologies such as robot systems. The specific contents include control methodology, mathematical analysis of control system, control design method, discrete control system and its cutting-edge applications. To lay a solid foundation for future students to conduct in-depth research in intelligent manufacturing fields such as mechatronics and robotics.

　　項目大綱

　　機器人和控制導論：使用拉普拉斯變換對時域和頻域中的反饋控制器進行建模，以及控制性能和穩定性分析 Introduction to robotics and control

　　離散控制系統簡介：用于分析和設計機器人和實驗系統離散控制器的財產和z變換的使用 Introduction to discrete control systems

　　離散控制系統的系統規范和性能：用于機器人動力學分析的狀態空間形式的離散控制 System specification and performance of discrete control systems

　　控制系統的應用：在機器人和其他數字技術中的應用示例 pplication of Control Systems

　　學術研討1：教授與各組學生探討并評估個性化研究課題可行性，幫助學生明晰后續科研思路 Final Project Preparation Session I

　　學術研討2：教授將根據各組進度進行個性化指導，確保學生優質的終期課題產出 Final Project Preparation Session II

　　項目成果展示 Final Presentation

　　論文指導 Project Deliverables Tutoring

　　項目收獲

　　7周在線小組科研學習+5周不限時論文指導學習 共125課時

　　項目報告

　　優秀學員獲主導師Reference Letter

　　EI/CPCI/Scopus/ProQuest/Crossref/EBSCO或同等級別索引國際會議全文投遞與發表指導(可用于申請)

　　結業證書

　　成績單

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