CodeCPS: Correct-by-Design Estimation and Control of Cyber-Physical Systems

网络物理系统（CPS）可以在所有应用领域中找到，包括智能电网、机器人系统、自动汽车和医疗监控系统。CPS是一种在物理组件和计算元件（网络部件）之间具有紧密交互的系统。由于计算、通信和存储器的快速发展，CPS变得无处不在。CPS的设计和实现已经见证了源于嵌入在系统中的控制软件与物理元件交互的关键问题。这种不期望的行为的示例包括电力网络的频率偏离其标称值太多，导致停电，由于软件错误导致飞机坠毁，或自动驾驶汽车撞上行人。例如，剑桥郡的停电在2019年影响了英国的100多万客户，波音737 Max客机在2019年全球停飞，此前有346人死于两起坠机事故，造成航空业损失141亿英镑，丰田召回了65架，在系统中运行的核心控制软件的开发仍然是临时的和容易出错的，今天的大部分工程成本都用于确保控制软件正确工作。可靠CPS的设计需要结合多个学科的方法，包括计算机科学，工程和控制理论，研究分析和系统设计使用其数学模型。CPS开发的一个主要挑战是所涉及的学科之间的设计实践存在很大差异。应对这样的挑战需要研究人员从整体上理解系统的复杂性，分析网络和物理部分之间的相互作用，并确保CPS在设计阶段不会表现出不期望的行为。设计正确综合是一种新颖的新兴方法，它使用“数学描述”或“模型”并设计控制软件，保证在受控CPS在真实的世界中实现之前，在受控CPS中没有不期望的行为。然而，由于分析模型需要极大的计算能力，设计正确的方法目前仅限于小而简单的（线性）数学模型。它们还依赖于系统的精确数学模型，而这些模型往往是不可用的，也很难构建。这些局限性阻止了在不确定的环境中工作的大型复杂CPS的正确的设计方法的应用。CodeCPS项目将提供一套技术和工具，以克服这些限制，并推动CPS的边界处理的正确的设计方法。我的新研究者项目的目的是推进理论基础的正确的设计合成CPS。特别是，我将解决这类系统的三个具体挑战：复杂的动态，大规模和存在的不确定性（在模型，环境和状态信息）。我将提供，第一次，正确的设计技术，是强大的模型的不确定性，可以处理系统的非线性行为，并组成，因此适用于CPS与大量的组件。我将专门将这些技术应用于智能能源系统，以设计控制软件，通过集成响应负载（例如，CodeCPS将强烈影响CPS的可靠性，例如通过提供新的方法作为设计智能能源系统的垫脚石，这些智能能源系统是无停电或可靠的无人驾驶汽车。该项目的成功完成将为控制软件的自动化设计提供一种方法，最终可以开发复杂但可靠的CPS应用程序，同时大大降低工程成本。

Cyber-physical systems (CPS) can be found in all application domains, including smart power grids, robotics systems, autonomous cars and medical monitoring systems. A CPS is a system that has a tight interaction between physical components and computing elements (cyber parts). CPS are becoming ubiquitous due to rapid advances in computation, communication, and memory. Design and implementation of CPS have witnessed critical issues originated from the control software embedded in the system interacting with the physical elements. Examples of such undesired behaviours include the frequency of the power network deviating too much from its nominal value causing an electricity blackout, crash of an airplane due to software bugs, or an autonomous car hitting a pedestrian. For instance, Cambridgeshire's power cut affected over one million customers in the UK in 2019, the Boeing 737 Max airliner was grounded in 2019 worldwide after 346 people died in two crashes causing a loss of £14.1 billion to the aviation industry, and Toyota recalled 65,000 cars in 2015 over a software bug.The development of core control software running in the system is still ad hoc and error-prone and much of the engineering costs today go into ensuring that control software works correctly. Design of reliable CPS requires combining approaches from multiple disciplines including computer science, engineering and control theory that studies analysis and design of systems using their mathematical models. A major challenge in the development of CPS is the large differences in the design practices between the involved disciplines. Addressing such a challenge requires researchers who understand the system complexity as a whole, analyse the interaction between the cyber and the physical parts, and ensure that the CPS does not show undesired behaviours at the design stage.Correct-by-design synthesis is a novel and emerging approach that uses a "mathematical description" or "model" of the CPS and designs control software with guarantees on the lack of undesired behaviours in the controlled CPS before it is implemented in the real world. Correct-by-design approaches, however, are currently limited to small and simple (linear) mathematical models due to the need for extremely large computational power for analysing the model. They also rely on exact mathematical models of the system, which is often not available and hard to construct. These limitations prevent the application of correct-by-design approaches to large complex CPS working in an uncertain environment. The CodeCPS project will provide a set of techniques and tools to overcome such limitations and push the boundaries of the CPS handled by correct-by-design approaches.My New Investigator project aims to advance the theoretical foundations of correct-by-design synthesis for CPS. In particular, I will address three specific challenges of such systems: complex dynamics, being large-scale, and presence of uncertainty (in the model, environment, and state information). I will provide, for the first time, correct-by-design techniques that are robust with respect to model uncertainties, can handle systems with non-linear behaviours, and are compositional, thus applicable to CPS with large number of components. I will apply these techniques specifically to smart energy systems for designing control software that ensures safe operation of the frequency of the energy system by integrating responsive loads (e.g., Smart Buildings and Electric Vehicles).CodeCPS will strongly impact the reliability of CPS, such as by providing new methodologies as stepping stones for designing smart energy systems that are blackout free or trustworthy autonomous cars with no fatalities. Successful completion of this project will give a method for automated design of control software that makes it finally possible to develop complex, yet reliable CPS applications while considerably reducing the engineering cost.