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What is common to these systems? They have a computational core that interacts with the physical world. These cyber-physical systems require tight conjoining and coordination between the computational discrete and the physical continuous worlds. Cyber-physical systems are penetrating every aspect of our lives, with profound impact on sectors including aerospace, agriculture, automotive, chemical production, civil infrastructure, energy, entertainment, finance, healthcare, manufacturing, materials, retail, and transportation.
In the future, cyber-physical systems will rely less and less on human control and more and more on the intelligence embodied in the computational core.
Applied Cyber-Physical Systems
In some cases, such as an automated brake system in a car, this computational core may be able to detect and respond faster than a human; in some cases, such as robotic surgery, this computational core can be more precise than a human and not prone to fatigue; and in some cases, such as a minefield, an icefield, or a volcano, we would rather risk the expense of a machine over the life of a human. In all cases, it will be the software that provides much of the intelligence of the computational core.
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Our daily lives will depend more and more on these systems. Our lives, our money, our welfare. How can we design cyber-physical systems that we can bet our lives on?
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To ensure cyber-physical systems are safe, we need to address two fundamental scientific challenges. First, we need to reason about the discrete and continuous at the same time. Fortunately, much progress in formal verification has been made in the past 20 years on this front.
Model checking technology can be applied to hybrid automata, making it feasible to prove properties about and find bugs in models of cyber-physical systems. Another approach is to write logical formulae describing the behavior of a hybrid system and then use theorem proving technology to prove properties from the formulae.
An example of an appropriate logic in which to write such formulae is differential dynamic logic, developed within the last decade along with rich tool support. Active research addresses the scalability of these techniques, since currently they support only tens of state variables, whereas an operational cyber-physical system typically has orders of magnitude more. Second, cyber-physical systems operate under the presence of uncertainty. My Wishlist Sign In Join. Suh Editor , U.
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Add to Wishlist. Ships in 15 business days. Link Either by signing into your account or linking your membership details before your order is placed. Description Table of Contents Product Details Click on the cover image above to read some pages of this book! Industry Reviews From the reviews: "This book is an edited volume with contributions from the leading experts on the topic of CPS and presents diverse application examples and challenges in CPS.
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Advanced-level undergraduate and graduate students and researchers in the fields of computer science and engineering will find this book very useful as a reference. Virtual prototyping for maritime crane design and operations Yingguang Chu , Lars I. A hierarchical domain model for safety-critical cyber-physical systems in process automation Dirk Kuschnerus , Attila Bilgic , Felix Bruns , Thomas Musch.
McKelvin , Alejandro Jimenez.
References Publications referenced by this paper. Gladigau , A. Gerstlauer , M.
Haubelt , J.