collaborators

8 papers

eess.SY2026

On robustness, input-to-state stability and backstepping for stochastic differential equations

Robert H. Moldenhauer, Dragan Nešić, Mathieu Granzotto +2

We study conditions under which stability of the origin of stochastic differential equations is robust to small perturbations. We express robustness in two ways, firstly in the sen…

math.OC2026

Value iteration with stopping criterion: finite iterations, stability, and near-optimality guarantees

Mathieu Granzotto, Romain Postoyan, Dragan Nešić +2

Value iteration (VI) is a cornerstone of dynamic programming that allows computing near-optimal feedback laws for general plant dynamics and cost functions. In practice, however, i…

math.OC2025

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…

math.OC2025

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…

eess.SY2025

Low-dimensional observer design for stable linear systems by model reduction

M. F. Shakib, M. Khalil, R. Postoyan

This paper presents a low-dimensional observer design for stable, single-input single-output, continuous-time linear time-invariant (LTI) systems. Leveraging the model reduction by…

math.OC2025

Robust Recurrence of Discrete-Time Infinite-Horizon Stochastic Optimal Control with Discounted Cost

Robert H. Moldenhauer, Dragan Nešić, Mathieu Granzotto +2

We analyze the stability of general nonlinear discrete-time stochastic systems controlled by optimal inputs that minimize an infinite-horizon discounted cost. Under a novel stochas…