Automatic Control Engineering (ACE) Network

自动控制工程(ACE)网络

基本信息

  • 批准号:
    EP/X031470/1
  • 负责人:
  • 金额:
    $ 72.38万
  • 依托单位:
  • 依托单位国家:
    英国
  • 项目类别:
    Research Grant
  • 财政年份:
    2024
  • 资助国家:
    英国
  • 起止时间:
    2024 至 无数据
  • 项目状态:
    未结题

项目摘要

We are increasingly dependent on complex "smart" systems: cities, houses, vehicles, electricity grids and a myriad of connected 'things' gathering information and performing automated decision-making with or without a human in the loop. This is in part possible because of technological advances in sensing, actuation, computer hardware, networking and communication, which enable the harnessing, processing and analysis of vast volumes of data. Major advances in Automatic Control Engineering have provided the underpinning theory, methodology and practice needed to design and implement highly complex control and decision-making systems. Automatic control engineering continues to play a vital role in realising the government's long-term industrial strategy of raising productivity and earning power within the UK. Specifically, automatic control is a key enabling technology for all four major societal challenge themes identified in the 2017 UK Industrial Strategy: AI and Data, Clean Growth, Future Mobility and Aging Society and the specific challenge areas within each theme.Automatic control not only dramatically improves the productivity, efficiency, reliability and safety of a wide range of processes across all sectors, but also provides fundamental theory, methodologies and tools to further the understanding and enable discovery in other disciplines such as biology, medicine and social sciences. Whilst the UK led the First Industrial Revolution through the adoption of new technologies, including automation and control, today it lags behind its international competitors. This is evidenced in part by the slow productivity growth over the past decade, which is in sharp contrast to other economic indicators. It is argued that if the UK does not make a concerted effort to transition towards automation, it will miss a pivotal opportunity for growth, estimated to be worth more than £200 billion to the UK economy by 2030.For the UK to become a global leader in intelligent automation and leapfrog international competitors, it is vital that it consolidates its research leadership in automatic control engineering. The UK has a strong control engineering community of well over 1000 active researchers, and engineering practitioners spanning all career stages, which are represented at an international level by the UK Automatic Control Council (UKACC), the United Kingdom's National Member Organisation (NMO) of the International Federation of Automatic Control (IFAC), acting as an effective link between the UK and the international control communities. At the time of dramatic advances in automation, AI, sensing and computation technologies, in order to engage effectively with the UK Grand Challenge research agenda, avoid fragmentation of effort and to ensure control engineers are engaged from the outset with end-users or initiatives, there is a need for the UK control community to connect effectively with other academic and industry stakeholders, to develop a common research vision and strategy and to start addressing these challenges through ambitious pilot studies, paving the way for full-scale, high-impact grant proposals, novel groundbreaking research and knowledge transfer projects. The Automatic Control Engineering Network aims to drive forward the UK's research and international leadership in next-generation automation and control, by bringing together and connecting the country's expertise in automation, the internet-of-things, cybersecurity, machine learning and robotics, with industry stakeholders and the wider research communities working towards addressing the same pressing societal challenges. Through the creation of a Virtual Centre of Excellence in Automation and Control, the Network will ensure that the coordination of research efforts, industry engagement, training activities and resource sharing needed to address Grand Challenges, will continue beyond the end of the funding period.
我们越来越依赖复杂的“智能”系统:城市、房屋、车辆、电网和无数相互连接的“事物”收集信息,并在有或没有人类参与的情况下执行自动决策。这在一定程度上是可能的,因为传感、驱动、计算机硬件、网络和通信方面的技术进步,使利用、处理和分析大量数据成为可能。自动控制工程的主要进展为设计和实施高度复杂的控制和决策系统提供了基础理论、方法和实践。自动控制工程在实现政府提高英国生产力和盈利能力的长期工业战略方面继续发挥着至关重要的作用。具体来说,自动控制是2017年英国工业战略中确定的所有四个主要社会挑战主题的关键使能技术:人工智能和数据,清洁增长,未来流动性和老龄化社会以及每个主题中的具体挑战领域。自动控制不仅极大地提高了所有部门广泛过程的生产力、效率、可靠性和安全性,而且还提供了基础理论、方法和工具,以进一步理解和发现其他学科,如生物学、医学和社会科学。虽然英国通过采用包括自动化和控制在内的新技术引领了第一次工业革命,但今天它落后于国际竞争对手。过去十年生产率增长缓慢,与其他经济指标形成鲜明对比,在一定程度上证明了这一点。有人认为,如果英国不齐心协力向自动化过渡,它将错过一个关键的增长机会,据估计,到2030年,这个机会对英国经济的价值将超过2000亿英镑。英国要成为智能自动化领域的全球领导者,超越国际竞争对手,巩固其在自动控制工程领域的研究领导地位至关重要。英国拥有一个强大的控制工程界,拥有超过1000名活跃的研究人员和跨越所有职业阶段的工程从业人员,由英国自动控制委员会(UKACC)、国际自动控制联合会(IFAC)的英国国家成员组织(NMO)在国际层面代表,作为英国与国际控制界之间的有效联系。在自动化、人工智能、传感和计算技术取得巨大进步的时候,为了有效地参与英国大挑战的研究议程,避免分散的努力,并确保控制工程师从一开始就与最终用户或计划进行接触,英国控制社区需要与其他学术和行业利益相关者进行有效的联系。制定共同的研究愿景和战略,并通过雄心勃勃的试点研究开始应对这些挑战,为全面的、高影响力的资助提案、新颖的开创性研究和知识转移项目铺平道路。自动控制工程网络旨在通过汇集和连接英国在自动化、物联网、网络安全、机器学习和机器人方面的专业知识,与行业利益相关者和更广泛的研究团体一起努力解决同样紧迫的社会挑战,推动英国在下一代自动化和控制方面的研究和国际领导地位。通过创建自动化和控制领域的虚拟卓越中心,该网络将确保在资助期结束后继续协调研究工作、行业参与、培训活动和资源共享,以应对重大挑战。

项目成果

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Daniel Coca其他文献

Does calcium diffusional global feedback leads to slow light adaptation in Drosophila photoreceptors? - A 3D biophysical modelling approach
  • DOI:
    10.1186/1471-2202-12-s1-p56
  • 发表时间:
    2011-07-18
  • 期刊:
  • 影响因子:
    2.300
  • 作者:
    Zhuoyi Song;Marten Postma;Weiliang Chen;Daniel Coca;SA Billings;Roger C Hardie;Mikko Juusola;Erik De Schutter
  • 通讯作者:
    Erik De Schutter
A Novel Architecture - Switching Echo State Networks
一种新颖的架构 - 切换回声状态网络
A novel recovery algorithm of time encoded signals
  • DOI:
    10.1186/1471-2202-14-s1-p130
  • 发表时间:
    2013-07-08
  • 期刊:
  • 影响因子:
    2.300
  • 作者:
    Dorian Florescu;Daniel Coca
  • 通讯作者:
    Daniel Coca
We now know what fly photoreceptors compute
  • DOI:
    10.1186/1471-2202-14-s1-o5
  • 发表时间:
    2013-07-08
  • 期刊:
  • 影响因子:
    2.300
  • 作者:
    Uwe Friederich;Stephen A Billings;Mikko Juusola;Daniel Coca
  • 通讯作者:
    Daniel Coca
Stem cell fate decisions: Substates and attractors
干细胞命运抉择:亚状态与吸引子
  • DOI:
    10.1016/j.stemcr.2025.102532
  • 发表时间:
    2025-06-10
  • 期刊:
  • 影响因子:
    5.100
  • 作者:
    James E. Mason;Xiaokai Nie;Daniel Coca;Peter W. Andrews
  • 通讯作者:
    Peter W. Andrews

Daniel Coca的其他文献

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{{ truncateString('Daniel Coca', 18)}}的其他基金

The Digital Fruit Fly Brain
数字果蝇大脑
  • 批准号:
    BB/M025527/1
  • 财政年份:
    2015
  • 资助金额:
    $ 72.38万
  • 项目类别:
    Research Grant
Reverse-engineering Drosophila's retinal networks
对果蝇视网膜网络进行逆向工程
  • 批准号:
    BB/H013849/1
  • 财政年份:
    2010
  • 资助金额:
    $ 72.38万
  • 项目类别:
    Research Grant
Stem Cell Dynamics: Exploration of the Stem Cell attractor Landscape
干细胞动力学:干细胞吸引子景观的探索
  • 批准号:
    G0802627/1
  • 财政年份:
    2009
  • 资助金额:
    $ 72.38万
  • 项目类别:
    Research Grant
FPGA supercomputing technology for high-throughput identification and quantitation in proteomics
用于蛋白质组学高通量识别和定量的 FPGA 超级计算技术
  • 批准号:
    BB/F004893/1
  • 财政年份:
    2008
  • 资助金额:
    $ 72.38万
  • 项目类别:
    Research Grant
Hardware accelerated data processing pipeline for proteomics
用于蛋白质组学的硬件加速数据处理流程
  • 批准号:
    BB/F52809X/1
  • 财政年份:
    2007
  • 资助金额:
    $ 72.38万
  • 项目类别:
    Research Grant

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Cortical control of internal state in the insular cortex-claustrum region
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    2020
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    25 万元
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Nonlinear Quantum Control Engineering
非线性量子控制工程
  • 批准号:
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    2024
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  • 项目类别:
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Engineering the bone marrow niche to control stem cell regulation, metastatic evolution and cancer dormancy
改造骨髓生态位来控制干细胞调节、转移进化和癌症休眠
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    2024
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Travel: Improving the Utility of Haptic Feedback in Upper-Limb Prosthesis Control: Establishing user-centric guidelines for engineering innovation
旅行:提高上肢假肢控制中触觉反馈的效用:建立以用户为中心的工程创新指南
  • 批准号:
    2331318
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    2023
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    $ 72.38万
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    Standard Grant
Engineering Receptors to Control Platelet Activation and Therapeutic Release
工程受体来控制血小板激活和治疗释放
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Development of experimental materials and curriculum for practical learning of control engineering
控制工程实践学习实验教材和课程开发
  • 批准号:
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  • 财政年份:
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21ENGBIO Engineering bacterial 'sense and respond' systems to control microbial communities
21ENGBIO 工程细菌“感知和响应”系统来控制微生物群落
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  • 财政年份:
    2023
  • 资助金额:
    $ 72.38万
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Self-excitation, Limit Cycle Oscillations, and Control of Large Deflection Plate Models in Engineering Applications
工程应用中大偏转板模型的自激、极限循环振荡和控制
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Conference: Stochastic Control for Financial Engineering: Methods and Numerics
会议:金融工程的随机控制:方法和数值
  • 批准号:
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    $ 72.38万
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    Standard Grant
CAREER: Engineering Extracellular Matrix Ligands for Macrophage Control
职业:工程细胞外基质配体用于巨噬细胞控制
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