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— The complexity of present day embedded systems (continuous processes controlled by digital processors), and the increased demands on their reliability motivate the need for monitoring and fault isolation capabilities in the embedded processors. This paper develops monitoring, prediction, and fault isolation methods for abrupt faults in complex dynamic… (More)

Modeling and simulation are quickly becoming the primary enablers for complex system design. They allow the representation of intricate knowledge at various levels of abstraction and allow automated analysis as well as synthesis. The heterogeneity of the design process, as much as of the system itself, however, requires a manifold of formalisms tailored to… (More)

The design of embedded systems is often based on the development of a detailed formal system specification. Considerable effort is spent to ensure the correctness of this specification. However, the actual implementation of the specification and later maintenance is usually done using traditional programming and tends to diverge from the specification. To… (More)

Modeling abstractions in physical systems result in hybrid models which encompass continuous behaviors with discrete changes, causing discontinuities in system behavior generation which violate the physical laws of conservation of energy and continuity of power. This paper develops a formal speciication for handling discrete model connguration changes at… (More)

—This paper discusses a method for fault detection and isolation (FDI) in continuous dynamic systems. A key aspect of this approach is the coupling of a qualitative diagnosis engine and a monitoring system that computes symbolic feature values through a signal-to-symbol transformation on the continuously sampled measurement data. Signal analysis techniques… (More)

Physical systems are by nature continuous, but often exhibit nonlinearities that make b e h a vior generation complex and hard to analyze. Complexity is often reduced by linearizing model constraints and by a b-stracting the time scale for behavior generation. In either case, the physical components are modeled to operate in multiple modes, with abrupt… (More)

Physical systems often exhibit complex nonlinear behaviors in continuous time at multiple temporal and spatial scales. Abstractions simplify behavioral analysis and help focus on dominant system behaviors by defining sets of equivalent behavior types called modes. System behavior evolves in continuous modes with discrete transitions between modes. Subtle… (More)

Physical system modeling benefits from the use of implicit equations because it is often an intuitive way to describe physical constraints and behaviors. To achieve efficient models, model abstraction may lead to idealized component behavior that switches between modes of operation (e.g., an electrical diode may be on or off) based on inequalities (e.g.,… (More)

Continuous system dynamics can be described by, possibly large, systems of diierential equations. These can be either ordinary diierential equations (ODEs) or contain algebraic constraints as well to form diierential and algebraic equations (DAEs). Complex systems, such as aircraft, often operate in diierent modes of continuous operation and when mode… (More)