Checking Safe Trajectories of Aircraft Using Hybrid Automata

Oliveira, Ítalo Romani de; Cugnasca, Paulo Sérgio

doi:10.1007/3-540-45732-1_22

Cited by 3 publications

(2 citation statements)

References 6 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The use of hybrid automata to model and analyze spatial networks is a relatively new subject area, and includes application to Delta-Notch signaling networks [9], coordinated control of autonomous underwater vehicles [14], and aircraft trajectories and landing protocols [7,16]. In contrast, our focus is on emergent behavior (in the form of spiral waves) in networks of cardiac myocytes, and the use of spatial superposition as an abstraction mechanism.…”

Section: Related Workmentioning

confidence: 99%

Learning and detecting emergent behavior in networks of cardiac myocytes

et al. 2009

View full text Add to dashboard Cite

Abstract. We address the problem of specifying and detecting emergent behavior in networks of cardiac myocytes, spiral electric waves in particular, a precursor to atrial and ventricular fibrillation. To solve this problem we: (1) Apply discrete mode-abstraction to the cycle-linear hybrid automata (CLHA) we have recently developed for modeling the behavior of myocyte networks; (2) Introduce the new concept of spatialsuperposition of CLHA modes; (3) Develop a new spatial logic, based on spatial-superposition, for specifying emergent behavior; (4) Devise a new method for learning the formulae of this logic from the spatial patterns under investigation; and (5) Apply bounded model checking to detect (within milliseconds) the onset of spiral waves. We have implemented our methodology as the Emerald tool-suite, a component of our EHA framework for specification, simulation, analysis and control of excitable hybrid automata. We illustrate the effectiveness of our approach by applying Emerald to the scalar electrical fields produced by our CellExcite simulator.

show abstract

Section: Related Workmentioning

confidence: 99%

Learning and detecting emergent behavior in networks of cardiac myocytes

et al. 2009

View full text Add to dashboard Cite

show abstract

“…1 The example concerns conflict detection in aircraft routing and is massively simplified, since its purpose is simply to illustrate the methods.…”

Section: A Simple Examplementioning

confidence: 99%

Formal Verification and Automated Testing for Diagnostic and Monitoring Systems

Dutertre

Rushby

Tiwari

et al. 2008

AIAA Guidance, Navigation and Control Conference and Exhibit

View full text Add to dashboard Cite

Formal methods offer the unique benefit that it is possible to examine all possible circumstances within a given scope, rather than merely sample them as with testing and simulation. This is possible even when huge numbers of discrete possibilities must be considered, such as in fault scenarios, and in the presence of real-time and continuous behavior, and when both these sources of difficulty are combined. Formal methods achieve this by using symbolic methods of analysis, and it is the computational complexity of these symbolic methods that limits and complicates their application.Recently, new methods and tools for symbolic analysis have been developed that are far more efficient and effective in practice than earlier methods. These include solvers for "satisfiability modulo theories" (SMT solvers) and methods for using these to analyze discrete and hybrid (i.e., mixed discrete and continuous) systems. In addition, new ways to apply these capabilities have been developed, such as their use for test generation, and controller synthesis, in addition to analysis.In this paper, we outline these new methods, and describe a project to extend and apply them in combination to issues in verification and testing of diagnostic and monitoring systems.

show abstract