Design of Robust, Adaptive and Privacy-Preserving Control Networks

鲁棒、自适应和隐私保护控制网络的设计

• 批准号: 435905-2013
• 负责人: LeNy, Jerome
• 金额: $ 1.82万
• 依托单位: École Polytechnique de Montréal
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2015
• 资助国家: 加拿大
• 起止时间: 2015-01-01 至 2016-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=574220
• 关键词: Design; Robust; Adaptive; Privacy; Preserving

Control networks connect sensors, actuators and computing devices embedded in our environment to vastly improve our abilities to monitor and regulate the physical world. As these networks become more pervasive and their size and complexity increase, there is a need to further develop the scientific foundations for their principled design, deployment and validation. Indeed, despite recent advances in the field of networked control systems, the gap between the models used to synthesize control systems and the complexity of the embedded platforms on which they are implemented is growing. This gap leads to overly conservative designs and fast increasing costs and delays associated to system development, testing, and maintenance. A second obstacle to the deployment of these ubiquitous embedded networks is the resistance, due to justified privacy concerns, of the individual users who could most benefit from them, as illustrated for example by the installation of smart meters for power control networks. To answer these challenges, this research program proposes new interfaces between control, computing and communication systems enabling their seamless integration while guaranteeing the overall control performance. Moreover, rigorous privacy-preserving mechanisms for large-scale control networks are introduced for the first time, to protect the users who are increasingly responsible for providing the necessary input data and measurements. Applications that will drive this research include the model-based design of avionics systems, intelligent transportation systems, energy-efficient buildings and smart grids. The expected outcome will be a set of theoretical results, design methodologies and software tools that simplify the task of building reliable, cost-effective and high-performance control networks, and applicable to systems of realistic complexity. By integrating the proposed privacy-preserving mechanisms, emerging large-scale control networks will also see increased user participation, thereby accelerating their deployment and improving their efficiency.

控制网络连接嵌入在我们环境中的传感器，执行器和计算设备，以极大地提高我们监视和调节物理世界的能力。随着这些网络变得更加普遍，其规模和复杂性的增加，有必要进一步开发其原则性设计，部署和验证的科学基础。确实，尽管网络控制系统领域的最新进展，但用于综合控制系统的模型与实施的嵌入式平台的复杂性的差距正在增长。这一差距导致过度保守的设计，并快速增加与系统开发，测试和维护相关的成本和延误。这些无处不在的嵌入式网络部署这些网络的第二个障碍是，由于有道理的隐私问题，可以从中受益最大的个人用户，例如通过为电力控制网络安装智能电表所示。 为了应对这些挑战，该研究计划提出了控制，计算和通信系统之间的新接口，从而实现了无缝集成，同时保证了整体控制性能。此外，首次引入了针对大规模控制网络的严格保护隐私机制，以保护越来越多地提供必要输入数据和测量的用户。 将推动这项研究的应用程序包括基于模型的航空电子系统，智能运输系统，节能建筑物和智能电网的设计。预期的结果将是一组理论结果，设计方法和软件工具，可简化构建可靠，具有成本效益和高性能控制网络的任务，并适用于现实的复杂性系统。通过整合拟议的隐私保护机制，新兴的大规模控制网络还将看到用户参与度的增加，从而加快其部署并提高其效率。