In this project, we plan to investigate and develop new analysis and verification techniques (e.g., based on abstractions) that are directly applicable to general SHS models, while being computationally scalable.Courses: Computer-Aided Formal Verification, Probabilistic Model Checking, Probability and Computing, Automata Logic and Games Prerequisites: Familiarity with stochastic processes and formal verification Smart microgrids are small-scale versions of centralized electricity systems, which locally generate, distribute, and regulate the flow of electricity to consumers.html head meta http equiv content type text charset ISO 8859 1 title Google style body td a p h font family arial sans serif size 20px color 3366cc q 00c script function sf document f focus bgcolor ffffff 000000 link 0000cc vlink 551a8b alink ff0000 onload if images new Image src nav logo2 png topmargin 3 marginheight center div align right nowrap padding bottom 4px width 100 href url sa pref ig pval www de 3Fhl 3Dde usg Z0CJb WM4Hl Sg Uf Avcq REfrp5hx E Diese Seite personalisieren nbsp https com accounts Login continue hl Anmelden img alt height 110 intl logo gif 301 br form action search name defer table border 0 cellspacing cellpadding 4 tr b Web class imghp ie oe tab wi Bilder groups grphp wg news nwshp wn froogle frghp wf options Mehr raquo valign top 25 input hidden value maxlength 2048 55 Suche btn G submit btn I Auf gut Gl??2 advanced Erweiterte preferences Einstellungen language tools Sprachtools colspan id all radio checked label for Das lgr lr lang Seiten Deutsch cty cr country DE aus Deutschland ads Werbung services Unternehmensangebote about ?
For example, enter "giraffe" and you'll get back words like "gazellephant" and "gorilldebeest".
Formal analysis, verification, and optimal control of SHS models represent relevant goals because of their theoretical generality and for their applicability to a wealth of studies in the Sciences and in Engineering.
In a number of practical instances the presence of a discrete number of continuously operating modes (e.g., in fault-tolerant industrial systems), the effect of uncertainty (e.g., in safety-critical air-traffic systems), or both occurrences (e.g., in models of biological entities) advocate the use of a mathematical framework, such as that of SHS, which is structurally predisposed to model such heterogeneous systems.
However, the computational cost for the inverse hessian matrix is expensive especially when the objective function takes a large number of variables.
The L-BFGS method iteratively finds a minimizer by approximating the inverse hessian matrix by information from last m iterations.