Design of Robust, Adaptive and Privacy-Preserving Control Networks

控制网络将嵌入我们环境中的传感器、执行器和计算设备连接起来，大大提高了我们监控和调节物理世界的能力。随着这些网络变得更加普遍，其规模和复杂性增加，有必要进一步发展其原则性设计、部署和验证的科学基础。实际上，尽管最近在网络化控制系统领域取得了进展，但是用于合成控制系统的模型与在其上实现控制系统的嵌入式平台的复杂性之间的差距正在增长。这种差距导致过于保守的设计和快速增加的成本和延迟与系统开发，测试和维护。这些无处不在的嵌入式网络的部署的第二个障碍是阻力，由于合理的隐私问题，个人用户谁可以从他们最受益，例如通过安装智能电表的电力控制网络。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，使其无缝集成，同时保证整体控制性能。此外，严格的隐私保护机制的大型控制网络首次引入，以保护用户谁是越来越多地负责提供必要的输入数据和测量。推动这项研究的应用包括航空电子系统、智能交通系统、节能建筑和智能电网的基于模型的设计。预期的成果将是一套理论成果，设计方法和软件工具，简化了建立可靠的，具有成本效益和高性能的控制网络的任务，并适用于现实复杂的系统。通过整合所提出的隐私保护机制，新兴的大规模控制网络也将增加用户参与，从而加速其部署并提高其效率。

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.