We generalise the optimisation technique of dynamic programming for discretetime systems with an uncertain gain function. We assume that uncertainty about the gain function is des...
This paper presents novel analysis results for input-to-state stability (ISS) that utilise dynamic programming techniques to characterise minimal ISS gains and transient bounds. Th...
Shoudong Huang, Matthew R. James, Dragan Nesic, Pe...
In this work, probabilistic reachability over a finite horizon is investigated for a class of discrete time stochastic hybrid systems with control inputs. A suitable embedding of ...
Alessandro Abate, Maria Prandini, John Lygeros, Sh...
Abstract— We relax the monotonicity requirement of Lyapunov’s theorem to enlarge the class of functions that can provide certificates of stability. To this end, we propose two...
The usual methods of applying Bayesian networks to the modeling of temporal processes, such as Dean and Kanazawa's dynamic Bayesian networks (DBNs), consist in discretizing t...