Monitoring and control of cyber-physical systems.
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Abstract:
Cyber-Physical Systems (CPS) encompass a large variety of systems including example future energy systems (e.g. smart grid), homeland security and emergency response, smart medical technologies, smart cars and air transportation. One of the most important challenges in the design and deployment of Cyber-Physical Systems is how to formally guarantee that they are amenable to effective human control.
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The goal of this project is to integrate digital microfluidics systems with thin-film photodetectors in the top plate to realize biochemical target sensing using fluorescence. System control, adaptation, and reconfiguration through software will lead to a general-purpose lab-on-chip computing platform, in the same way as programmable computing devices allow multifunctional capabilities via software on a hardware platform.
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With the increasing popularity of mobile computing, cyber physical systems are merging into major mobile systems of our society, such as public transportation, supply chain systems, and taxi networks. Researchers have accumulated abundant knowledge for designing cyber physical systems, such as military surveillance, infrastructure protection, scientific exploration, and smart environments, mostly in relatively stationary settings, i.e., where spatial diversity is limited.
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Medical devices are typically developed as stand-alone units. Current industrial Verification and Validation (V&V) tech- niques primarily target stand-alone systems. Moreover, the US Food and Drug Administration's (FDA) regulatory clearance processes are designed to approve such devices that are integrated by a single manufacturer with complete control over all components.
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Effective engineering of complex devices often depends on the ability to encapsulate responsibility for tasks into modular components with specific responsibilities and clearly defined lines of communication. Under such conditions, one can determine what components or lines of communication are at fault for poor system performance because the system can be checked against modularized model specifications.
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Despite their importance within the energy sector, buildings have not kept pace with technological improvements and particularly the evolution of intelligent features. A primary obstacle in enabling intelligent buildings is their highly distributed and diverse nature.
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A hybrid system is a dynamical model that describes the coupled evolution of both continuous- valued variables and discrete patterns. A prime example of such a system is a power electronic circuit, where the semiconductor transistors behave as ideal switches whose switching actions effectively change the circuit topology (i.e., the discrete pattern) that in turn defines the dynamics of currents and voltages (i.e., the continuous variables) and hence the switching actions.
