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Robust Control of Biomedical and Environmentally Sustainable Engineered Systems

Robust Control of Biomedical and Environmentally Sustainable Engineered Systems
生物医学和环境可持续工程系统的鲁棒控制
批准号:
RGPIN-2015-05574
负责人:
Boulet, Benoit
金额:
$2.7万
依托单位:
依托单位国家:
加拿大
项目类别:
Discovery Grants Program - Individual
财政年份:
2018
资助国家:
加拿大
项目状态:
已结题
起止时间:
2018-01-01 至 2019-12-31

项目摘要

项目成果

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中文摘要
翻译
工程系统的环境可持续性和改进疗法的生物医学系统的开发将是确保加拿大人更好的生活质量和为子孙后代保护环境的关键。因此,拟议的工程研究计划的主要目标是为以下方面开发创新的稳健和可持续的控制系统:(A)环境可持续的工程系统:电动汽车(EV)、插电式混合动力汽车(PHEV)、能源管理系统、使用可再生能源的建筑供暖、通风和空调(HVAC)系统,以及(B)主要专注于人工胰腺的医疗应用。电动汽车(EV)和插电式混合动力汽车(PHEV)产生零排放或极少排放,现在被广泛视为可持续交通的未来。本文首先提出从动态能量优化的角度研究电动汽车和混合动力汽车的设计、控制和充电问题。研究的重点将是通过先进的反馈控制设计将化石燃料和电能的消耗降至最低。在PHEV和可再生能源系统中,一个基本问题是如何根据系统和负载的动态特性使用电能蓄能器,以最大限度地减少燃料或能源消耗。其次,我们建议研究大型建筑物的供暖、通风和空调系统的管制,以最大限度地利用蓄能器,如冰库和光伏电池板。*糖尿病患者血糖控制系统研究的目标是设计和实现一种闭环设备,用于调节1型糖尿病患者的血糖水平。这种闭环设备(所谓的人工胰腺)测量血糖水平,并通过控制算法使用这些测量结果,通过皮下胰岛素和胰升糖素泵适当地给胰岛素和胰高血糖素剂量。我们最近合作开发了一种用于双激素人工胰腺的控制算法,该算法在15名1型糖尿病患者的临床试验中被证明是成功的。我们希望继续这项研究,开发一种先进的可穿戴人工胰腺。该方法的创新之处在于开发了自适应和健壮的预测控制算法,该算法适应胰岛素敏感性的变化,同时对不确定的动态和长扩散延迟具有健壮性。我们还建议使用迭代学习来观察周期到周期的控制,因为胰岛素敏感性模式遵循昼夜节律。*该研究计划将为三名博士生和三名硕士生提供多学科培训,他们将作为有效的变革推动者吸引加拿大的组织和机构。
英文摘要
The environmental sustainability of engineered systems and the development of biomedical systems for improved therapies will be critical to ensure a better quality of life for Canadians and to preserve the environment for future generations. The main goal of the proposed engineering research program is thus to develop innovative robust and sustainable control systems for: (a) environmentally sustainable engineered systems: electric vehicles (EV), plug-in hybrid electric vehicles (PHEV), energy management systems, building heating, ventilation and air conditioning (HVAC) systems using renewable energy, and (b) medical applications, mostly focusing on the artificial pancreas.******Electric (EV) and plug-in hybrid electric vehicles (PHEV) produce no or little emissions and are now widely seen as the future of sustainable transportation. We first propose to study the design, control and charging of EV and PHEV from the point of view of dynamic energy optimization. The research will focus on minimizing consumption of fossil fuel and electrical energy through advanced feedback control design. One of the fundamental issues in PHEV and renewable energy systems is how to use the electrical energy accumulator with respect to the dynamics of the system and the load in order to minimize fuel or energy consumption. Secondly, we propose to investigate the control of heating, ventilation and air conditioning systems of large buildings to maximize the use of energy accumulators, such as ice banks, and photovoltaic panels. ******The objective of the blood glucose control system research for diabetic patients is to design and implement a closed-loop device that regulates glucose levels for people with Type 1 diabetes. The closed-loop device (so-called artificial pancreas) measures blood glucose levels and uses these measurements via a control algorithm to properly dose insulin and glucagon using the subcutaneous insulin and glucagon pumps. Our recent collaborative work has developed a control algorithm for a dual-hormone artificial pancreas which proved to be successful in a clinical trial on 15 patients with type 1 diabetes. We wish to continue this research in the development of an advanced wearable artificial pancreas. Novelty of the proposed approach lies in the development of adaptive and robust MPC algorithms that adapt to changes in insulin sensitivity while being robust to uncertain dynamics and long diffusion delays. We also propose to look at cycle-to-cycle control using iterative learning as insulin sensitivity patterns follow circadian rhythms. ******This research program will provide multidisciplinary training to three Ph.D. students and three Master's students who will be attractive to Canadian organizations and institutions as effective agents of change.
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会议论文
Data-Driven Robust Control Systems for Sustainability
  • 批准号:
    RGPIN-2020-05914
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $2.4万
  • 财政年份:
    2022
  • 负责人:
    Boulet, Benoit
  • 依托单位:
Modeling and machine learning-based control of a continuously-variable transmission system
  • 批准号:
    570764-2021
  • 项目类别:
    Alliance Grants
  • 资助金额:
    $14.57万
  • 财政年份:
    2021
  • 负责人:
    Boulet, Benoit
  • 依托单位:
Data-Driven Robust Control Systems for Sustainability
  • 批准号:
    RGPIN-2020-05914
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $2.4万
  • 财政年份:
    2021
  • 负责人:
    Boulet, Benoit
  • 依托单位:
Data-Driven Robust Control Systems for Sustainability
  • 批准号:
    RGPIN-2020-05914
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $2.4万
  • 财政年份:
    2020
  • 负责人:
    Boulet, Benoit
  • 依托单位:
国内基金
海外基金
Cortical control of internal state in the insular cortex-claustrum region