@phdthesis{Geiselhart2015,
  author    = {Geiselhart, Roman},
  title     = {Advances in the stability analysis of large-scale discrete-time systems},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-112963},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2015},
  abstract  = {Several aspects of the stability analysis of large-scale discrete-time systems are considered. An important feature is that the right-hand side does not have have to be continuous. In particular, constructive approaches to compute Lyapunov functions are derived and applied to several system classes. For large-scale systems, which are considered as an interconnection of smaller subsystems, we derive a new class of small-gain results, which do not require the subsystems to be robust in some sense. Moreover, we do not only study sufficiency of the conditions, but rather state an assumption under which these conditions are also necessary. Moreover, gain construction methods are derived for several types of aggregation, quantifying how large a prescribed set of interconnection gains can be in order that a small-gain condition holds.},
  subject      = {Ljapunov-Funktion},
  language  = {en}
}
@misc{Proell2013,
  type      = {Master Thesis},
  author    = {Pr{\"o}ll, Sebastian},
  title     = {Stability of Switched Epidemiological Models},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-108573},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2013},
  abstract  = {In this thesis it is shown how the spread of infectious diseases can be described via mathematical models that show the dynamic behavior of epidemics. Ordinary differential equations are used for the modeling process. SIR and SIRS models are distinguished, depending on whether a disease confers immunity to individuals after recovery or not. There are characteristic parameters for each disease like the infection rate or the recovery rate. These parameters indicate how aggressive a disease acts and how long it takes for an individual to recover, respectively. In general the parameters are time-varying and depend on population groups. For this reason, models with multiple subgroups are introduced, and switched systems are used to carry out time-variant parameters. When investigating such models, the so called disease-free equilibrium is of interest, where no infectives appear within the population. The question is whether there are conditions, under which this equilibrium is stable. Necessary mathematical tools for the stability analysis are presented. The theory of ordinary differential equations, including Lyapunov stability theory, is fundamental. Moreover, convex and nonsmooth analysis, positive systems and differential inclusions are introduced. With these tools, sufficient conditions are given for the disease-free equilibrium of SIS, SIR and SIRS systems to be asymptotically stable.},
  subject      = {Gew{\"o}hnliche Differentialgleichung},
  language  = {en}
}
@phdthesis{Sailer2014,
  author    = {Sailer, Rudolf},
  title     = {Stability and Stabilization of Large-Scale Digital Networks},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-101509},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2014},
  abstract  = {Several aspects of the control of large-scale systems communicating over digital channels are considered. In particular, the issue of delay, quantization, and packet loss is addressed with the help of dynamic quantization. New small-gain results suitable for networked control systems are introduced and it is shown that many of the known small-gain conditions are equivalent. The issue of bandwidth limitations is addressed with the help of event-triggered control. A novel approach termed parsimonious triggering is introduced, which helps to rule out the occurrence of an infinite number of triggering events within finite time. Moreover, the feasibility of the presented approaches is demonstrated by numerical examples.},
  subject      = {Rechnernetz},
  language  = {en}
}