2 citations · 2 across the 2 of their papers we have counts for
6 papers · 1 filter
Polyhedral Control Design: Theory and Methods
Boris Houska, Matthias A. Müller, Mario E. Villanueva
In this article, we survey the primary research on polyhedral computing methods for constrained linear control systems. Our focus is on the modeling power of convex optimization, f…
Convex operator-theoretic methods in stochastic control
Boris Houska
This paper is about operator-theoretic methods for solving nonlinear stochastic optimal control problems to global optimality. These methods leverage on the convex duality between…
Configuration-Constrained Tube MPC
Mario E. Villanueva, Matthias A. Müller, Boris Houska
This paper is about robust Model Predictive Control (MPC) for linear systems with additive and multiplicative uncertainty. A novel class of configuration-constrained polytopic robu…
Parallel MPC for Linear Systems with State and Input Constraints
Jiahe Shi, Yuning Jiang, Juraj Oravec +1
This paper proposes a parallelizable algorithm for linear-quadratic model predictive control (MPC) problems with state and input constraints. The algorithm itself is based on a par…
Robust MPC via Min-Max Differential Inequalities
Mario E. Villanueva, Rien Quirynen, Moritz Diehl +2
This paper is concerned with tube-based model predictive control (MPC) for both linear and nonlinear, input-affine continuous-time dynamic systems that are affected by time-varying…
Real-time Algorithm for Self-Reflective Model Predictive Control
Xuhui Feng, Boris Houska
This paper is about a real-time model predictive control (MPC) algorithm for a particular class of model based controllers, whose objective consists of a nominal tracking objective…