2 citations · 2 across the 11 of their papers we have counts for
12 papers
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…
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…
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 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…
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…
Policy iteration for discrete-time systems with discounted costs: stability and near-optimality guarantees
Jonathan de Brusse, Mathieu Granzotto, Romain Postoyan +1
Given a discounted cost, we study deterministic discrete-time systems whose inputs are generated by policy iteration (PI). We provide novel near-optimality and stability properties…
Policy iteration: for want of recursive feasibility, all is not lost
Mathieu Granzotto, Olivier Lindamulage De Silva, Romain Postoyan +2
This paper investigates recursive feasibility, recursive robust stability and near-optimality properties of policy iteration (PI). For this purpose, we consider deterministic nonli…
Stability analysis of optimal control problems with time-dependent costs
Sifeddine Benahmed, Romain Postoyan, Mathieu Granzotto +3
We present stability conditions for deterministic time-varying nonlinear discrete-time systems whose inputs aim to minimize an infinite-horizon time-dependent cost. Global asymptot…
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…
Optimistic planning for the near-optimal control of nonlinear switched discrete-time systems with stability guarantees
Mathieu Granzotto, Romain Postoyan, Lucian Buşoniu +2
Originating in the artificial intelligence literature, optimistic planning (OP) is an algorithm that generates near-optimal control inputs for generic nonlinear discrete-time syste…