2 citations · 3 across the 7 of their papers we have counts for
8 papers · 1 filter
Discounted LQR: stabilizing (near-)optimal state-feedback laws
Jonathan de Brusse, Jamal Daafouz, Mathieu Granzotto +2
We study deterministic, discrete linear time-invariant systems with infinite-horizon discounted quadratic cost. It is well-known that standard stabilizability and detectability pro…
An optimistic planning algorithm for switched discrete-time LQR
Mathieu Granzotto, Romain Postoyan, Dragan Nešić +2
We introduce TROOP, a tree-based Riccati optimistic online planner, that is designed to generate near-optimal control laws for discrete-time switched linear systems with switched q…
Stability criteria for singularly perturbed impulsive linear switched systems
Ihab Haidar, Yacine Chitour, Jamal Daafouz +2
We study a class of singularly perturbed impulsive linear switched systems exhibiting switching between slow and fast dynamics. To analyze their behavior, we construct auxiliary sw…
A Berger-Wang formula for impulsive switched systems
Yacine Chitour, Jamal Daafouz, Ihab Haidar +2
This paper addresses a class of impulsive systems defined by a mix of continuous-time and discrete-time switched linear dynamics. We first analyze a related class of weighted discr…
Exploiting homogeneity for the optimal control of discrete-time systems: application to value iteration
Mathieu Granzotto, Romain Postoyan, Lucian Buşoniu +2
To investigate solutions of (near-)optimal control problems, we extend and exploit a notion of homogeneity recently proposed in the literature for discrete-time systems. Assuming t…
When to stop value iteration: stability and near-optimality versus computation
Mathieu Granzotto, Romain Postoyan, Dragan Nešić +2
Value iteration (VI) is a ubiquitous algorithm for optimal control, planning, and reinforcement learning schemes. Under the right assumptions, VI is a vital tool to generate inputs…