In this paper, we consider the problem of motion planning for mobile robots with nonlinear hybrid dynamics, and high-level temporal goals. We use a multi-layered synergistic framew...
Complex networks capture interactions among entities in various application areas in a graph representation. Analyzing large scale complex networks often answers important question...
mentation of the Abstraction Method In Coq Eelis van der Weegen Institute for Computing and Information Sciences Raboud University Nijmegen This technical report documents our deve...
Herman Geuvers, Adam Koprowski, Dan Synek, Eelis v...
In this paper, timed Petri nets are used to model and control hybrid systems. Petri nets are used instead of finite automata primarily because of the advantages they offer in de...
Xenofon D. Koutsoukos, Kevin X. He, Michael D. Lem...
Applying Vector Autoregression (VAR) and genetic algorithm (GA) in hybrid systems with neural network can improve the NN's prediction capability. Two case studies have been ca...
Abstract In this article, we describe some recent results on the hybridization methods for the analysis of nonlinear systems. The main idea of our hybridization approach is to appl...
Hybrid system modeling refers to the construction of system models combining both continuous and discrete dynamics. These models can greatly reduce the complexity of a phystem mod...
This paper presents an efficient online mode estimation algorithm for a class of sensor-rich, distributed embedded systems, the so-called hybrid systems. A central problem in dist...
Feng Zhao, Xenofon D. Koutsoukos, Horst W. Haussec...
Modeling and simulation of biochemical systems are important tasks because they can provide insights into complicated systems where traditional experimentation is expensive or imp...
A 3D biped with knees and a hip is naturally modeled as a nontrivial hybrid system; impacts occur when the knee strikes and when the foot impacts the ground causing a switch in the...