PECASE: Hierarchical Abstractions of Hybrid Systems

题目：PECASE：混合系统的层次抽象机构：宾夕法尼亚大学近年来，我们见证了功能极其强大且价格低廉的计算机的出现，通信网络的爆炸式发展，以及传感器和执行器技术的革命。这些加速的进步已经在许多物理系统中找到了自己的方式，如汽车、飞机、化学过程、电网、微机械系统和制造系统，从而产生了所谓的嵌入式控制系统或嵌入式软件系统，它们将物理过程与信息系统相结合。这些应用领域不仅从工程角度来看很重要，而且因为它们在日常生活和经济福祉中普遍存在。设计高效、健壮的大规模嵌入式系统是一个重大的系统挑战。发展研究基础和教育计划，使下一代工程师能够最佳地利用信息技术提供的机会，这是非常重要的。嵌入式系统的难点在于软件设计和控制设计是高度解耦的。因此，在软件设计过程中没有明确地考虑物理约束，例如微分方程。因此，从根本上说，嵌入式系统的设计需要新颖的方法，也需要开发模型和工具，以解决集成系统的许多不同的物理、功能和逻辑方面的分析和设计。混合系统的研究为嵌入式系统的建模、分析和设计提供了理论基础。混合系统以一种可以在统一的建模框架中捕获软件逻辑、物理动态和通信协议的方式，自然地将离散事件和连续时间系统组合在一起。混合系统已被用作自动高速公路系统、空中交通管理系统、嵌入式汽车控制器、制造系统、化学过程以及最近的生物分子网络的数学模型。混合系统的广泛适用性激发了控制理论和理论计算机科学的大量研究。尽管混合系统作为一个模型取得了巨大的成功，但由于复杂性，最先进的混合系统分析和设计技术的适用性仅限于小尺寸的例子。降低复杂性的基本方法之一涉及使用分层分解。分层系统的主要挑战之一是在不同抽象层次上提取与每一层的功能和目标兼容的模型层次。层次结构在分别管理控制和软件设计的复杂性方面发挥了重要作用。然而，对于重新集成软件和控制的混合系统，正确的层次概念是一个巨大的挑战，并且是将我们的模型，理论，算法和工具扩展到大规模嵌入式系统的关键障碍。下一代大规模嵌入式系统激发了新的控制和软件范例。因此，从理论和应用的角度来看，有许多根本性和重大贡献的机会。在这个令人兴奋的知识领域，研究和教育议程的建议研究的重点是发展混合系统在不同抽象层次的分层分解的理论基础。研究议程的长期目标将解决给定一类混合模型和一类必须保留的属性的基本问题，提取保留感兴趣属性的建模抽象。要实现这一目标，首先要发展纯连续系统双仿真的鲁棒概念，然后以与混合系统动力学一致的方式统一连续和离散概念。合并离散和连续系统产生了严重的教育问题，以便将传统上分离的离散和连续数学线程结合起来。这些问题必须在各级教育中加以解决。在研究生阶段，需要开设关于混合系统的新课程，但重点是控制理论和计算机科学中的复杂性降低方法。然而，考虑到大多数本科生的片面背景，本科阶段需要的是一门跨部门的嵌入式系统课程，该课程将突出嵌入式系统在各种应用领域中的离散性和连续性。这将允许更早地统一教育背景，使学生接触到其他部门的相关应用领域，并展示模型、方法和工具的跨学科能力。该项目最初是作为职业奖资助的，并于2004年5月转换为工程师和科学家的总统早期职业奖（PECASE）奖。

Proposal Title: PECASE: Hierarchical Abstractions of Hybrid Systems Institution: University of PennsylvaniaRecent years have witnessed the availability of extremely powerful and inexpensive computers, the explosion of communication networks, and revolutions in sensor and actuator technology. These accelerating advances have found their way inside many physical systems such as cars, aircraft, chemical processes, power networks, micro-mechanical systems, and manufacturing systems, resulting in the so-called embedded control systems or embedded software systems which merge physical processes with information systems. These application domains are important not only from an engineering perspective but also because of their prevalence in everyday life and the well-being of the economy.Designing efficient, yet robust, large-scale embedded systems is a significant systems challenge. It is of immediate importance to develop the research foundations and educational programs to enable next-generation engineers to optimally utilize the opportunities offered by information technology. The difficulty with embedded systems arises from the fact that the software design and the control design is highly decoupled. As a result, physical constraints, such as differential equations, are not taken explicitly into account in the software design process. Consequently, fundamentally novel approaches to the design of embedded systems are needed as well as the development of models and tools that address the analysis and design of the integrated system with its many different physical, functional and logical aspects.The research discipline of hybrid systems provides a theoretical foundation for the modeling, analysis, and design of embedded systems. Hybrid systems naturally combine discrete-event and continuous-time systems in a manner that can capture software logic, physical dynamics, and communication protocols, in a unified modeling framework. Hybrid systems have been used as mathematical models for automated highway systems, air traffic management systems, embedded automotive controllers, manufacturing systems, chemical processes, and, more recently, biomolecular networks. The wide applicability of hybrid systems has inspired a great deal of research from both control theory and theoretical computer science.Despite the great success of hybrid systems as a model, the applicability of state-of-the-art analysis and design techniques for hybrid systems has been limited to examples of small size due to complexity. One of the fundamental approaches for reducing complexity involves the use of hierarchical decomposition. One of the main challenges in hierarchical systems is the extraction of a hierarchy of models at various levels of abstraction which are compatible with the functionality and objectives of each layer. Hierarchies have been instrumental in separately managing the complexity of both control and software designs. However, for hybrid systems which re-integrate software and control, the right notion of hierarchy is a great challenge, and is the critical obstacle for scaling our models, theories, algorithms, and tools to large scale, embedded systems.Next-generation, large-scale embedded systems have motivated new control as well as software paradigms. As a result, there are numerous opportunities for fundamental and significant contributions from both a theoretical and an applied perspective. In this exciting intellectual landscape, the research and educational agenda of the proposed research focuses on developing the theoretical foundations for the hierarchical decomposition of hybrid systems at various levels of abstraction. The long term goal of the research agenda will address the fundamental problem of given a class of hybrid models, and a class of properties that must be preserved, extract modeling abstractions that preserve the properties of interest. Achieving this goal will consist of first developing robust notions of bi-simulation for purely continuous systems, and then unifying the continuous and discrete notions in a manner that is consistent with the dynamics of hybrid systems.Merging discrete and continuous systems creates serious educational issues in order to combine the traditionally separate threads of discrete and continuous mathematics. These issues must be addressed at all educational levels. At the graduate level, creating new courses on hybrid systems are needed, but with focus on complexity reduction methods in both control theory and computer science. However, given the one-sided backgrounds of most undergraduate students, what is needed at the undergraduate level, is a cross-departmental, embedded systems course that will highlight both the discrete and continuous nature of embedded systems in various application domains. This will allow the earlier uniformization of educational backgrounds, expose students to related application domains in other departments, as well as demonstrate the cross-disciplinary power of the models, methods, and tools.This project was originally funded as a CAREER award, and was converted to a Presidential Early Career Award for Engineers and Scientists (PECASE) award in May 2004.