6 papers
Towards turnpike-based performance analysis of risk-averse stochastic predictive control
Jonas SchieÃl, Ruchuan Ou, Michael H. Baumann +2
In this paper, we present performance estimates for stochastic economic MPC schemes with risk-averse cost formulations. For MPC algorithms with costs given by expectations, it was…
Stability and performance of stochastic economic MPC -- Stochastic characterization of the closed-loop asymptotics
Jonas SchieÃl, Hannah Selder, Ruchuan Ou +3
Model Predictive Control (MPC) is well understood in the deterministic setting, yet rigorous stability and performance guarantees for stochastic MPC remain limited to the considera…
PolyOCP.jl -- A Julia Package for Stochastic OCPs and MPC
Ruchuan Ou, Learta Januzi, Jonas SchieÃl +3
The consideration of stochastic uncertainty in optimal and predictive control is a well-explored topic. Recently Polynomial Chaos Expansions (PCE) have received considerable attent…
Closed-loop analysis of linear stochastic MPC with risk-averse constraints
Jonas SchieÃl, Ruchuan Ou, Michael H. Baumann +2
Chance constraints are widely used in stochastic model predictive control (MPC) to enforce probabilistic state and input constraints in the presence of unbounded disturbances. Howe…
Turnpike and dissipativity in generalized discrete-time stochastic linear-quadratic optimal control
Jonas SchieÃl, Ruchuan Ou, Timm Faulwasser +2
We investigate different turnpike phenomena of generalized discrete-time stochastic linear-quadratic optimal control problems. Our analysis is based on a novel strict dissipativity…
A Polynomial Chaos Approach to Stochastic LQ Optimal Control: Error Bounds and Infinite-Horizon Results
Ruchuan Ou, Jonas SchieÃl, Michael Heinrich Baumann +2
The stochastic linear--quadratic regulator problem subject to Gaussian disturbances is well known and usually addressed via a moment-based reformulation. Here, we leverage polynomi…