Automated Modular Synthesis for Reliable Cyber Physical System Design

Technological progress is currently revolutionizing our society through machines taking over truly complex actions - the first self-driving cars are being deployed, smart grids are being integrated into the global power network and production plants are starting to realize individual product designs in the spirit of the new "Industry 4.0" paradigm.Such automated complex behavior is realized by a large software stack orchestrating the interaction of physical and digital components resulting in a Cyber Physical System (CPS). While such systems operate fully automatically, they are typically built in an ad-hoc manner. This manual design approach is currently reaching its limit, as the resulting code base is becoming so complex that it cannot be correctly handled by humans anymore. Additionally, exhaustive testing of CPS is too costly and time consuming to reach suitable confidence margins for their safe and reliable operation. At the same time, CPS need to be affordable and performant if they are to replace existing technology in industry and our daily life, and thereby unfold their full potential.To change today's design methodology, a promising research direction is the use of formal methods: automated methodologies that ensure system requirements during design-time. The main challenge in their application to CPS is the large amount of interacting heterogeneous components for which synthesis tools must automatically and locally generate code implementing a desired joint behavior. When considering for example a two-joint robot arm mounted on a mobile cart, its physical components are coupled (e.g., the arms' joint angle influences the wheels' friction and the cart moves the arms' mounting point). When actuating these components, synthesized feedback controllers must handle such couplings properly.In addition, synthesized coordinating software must ensure that different tasks performed by different components are scheduled and executed correctly, both sequentially and concurrently, despite component interactions. E.g., when the cart-and-arm assembly is fetching a distant object, the cart must move to the objects location first, before the arm can reach for it. Further, the mass of the arm differs before and after object pick-up. This changes the cart's dynamics due to the changed center of mass of the assembly. Hence, the cart's motion controller implementing the task 'move' depends on its position within the schedule w.r.t.\ the arm's 'pick-up' task.It is the overarching goal of this project to tackle the outlined challenges in automatic CPS design by significantly expanding the scope of formal automated synthesis techniques for CPS.In particular, we will provide a framework that automatically synthesizes and negotiates contracts to resolve component interactions. This allows for automated modular synthesis of controllers, abstractions and coordinating software throughout the layers of a CPS resulting in its reliable behavior.

技术进步目前正在通过接管真正复杂行动的机器彻底改变我们的社会 - 部署了第一辆自动驾驶汽车，智能电网已集成到全球电力网络中，生产工厂开始以新的“工业4.0” Paradigm的精神实现单个产品设计，并通过大型软件的物理组合和数字组成的互动来实现，从而实现了互动的互动，从而实现了互动的互动。尽管此类系统会自动运行，但它们通常以临时方式构建。这种手动设计方法目前已达到极限，因为所得代码基础变得如此复杂，以至于不再由人类正确处理。此外，CPS的详尽测试过于昂贵且耗时，无法达到安全可靠的运营。同时，如果CPS要代替工业和我们的日常生活中的现有技术，则需要负担得起和表现，从而发挥了全部潜力。要改变当今的设计方法，有希望的研究方向是使用正式方法：自动化方法，以确保在设计时间期间系统要求的自动化方法。他们应用于CPS的主要挑战是合成工具必须自动并在本地生成实现所需联合行为的代码的大量相互作用的异质组件。例如，当考虑一个安装在移动推车上的两关节机器人臂时，其物理组件是耦合的（例如，手臂的关节角度会影响车轮的摩擦，手推车移动了手臂的安装点）。在驱动这些组件时，合成的反馈控制器必须正确处理此类耦合。此外，合成的协调软件必须确保按照组件交互，依次和同意地安排和同时执行了不同组件执行的不同任务。例如，当手推车和武器组件拿起一个遥远的物体时，手推车必须先移动到对象位置，然后才能到达手臂。此外，手臂的质量在物体拾取前后都不同。由于装配的质量中心变化，这改变了购物车的动态。因此，手推车的运动控制器实施任务“移动”取决于其在时间表中的位置W.R.T. \ ARM的“拾取”任务。该项目是该项目的总体目标，即在自动CPS设计中应对cps的范围进行显着扩大cpss的范围，以解决CPS的范围，我们将为cpss提供了范围，我们将自动构成CPSS。互动。这允许在CPS的整个层中对控制器，抽象和协调软件的自动模块化综合，从而实现其可靠的行为。