6 papers
On robustness, input-to-state stability and backstepping for stochastic differential equations
Robert H. Moldenhauer, Dragan NeÅ¡iÄ, 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…
Value iteration with stopping criterion: finite iterations, stability, and near-optimality guarantees
Mathieu Granzotto, Romain Postoyan, Dragan NeÅ¡iÄ +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…
Discounted MPC and infinite-horizon optimal control under plant-model mismatch: Stability and suboptimality
Robert H. Moldenhauer, Karl Worthmann, Romain Postoyan +2
We study closed-loop stability and suboptimality for MPC and infinite-horizon optimal control solved using a surrogate model that differs from the real plant. We employ a unified f…
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 NeÅ¡iÄ +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…
Robust Recurrence of Discrete-Time Infinite-Horizon Stochastic Optimal Control with Discounted Cost
Robert H. Moldenhauer, Dragan NeÅ¡iÄ, 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…