104 citations · 134 across the 33 of their papers we have counts for
21 papers · 1 filter
Feedback Synthesis for Nonlinear Systems Via Convex Control Lyapunov Functions
Mario Eduardo Villanueva, Juraj Oravec, Radoslav Paulen +1
This paper introduces computationally efficient methods for synthesizing explicit piecewise affine (PWA) feedback laws for nonlinear discrete-time systems, ensuring robustness and…
Control Lyapunov Function Design via Configuration-Constrained Polyhedral Computing
Boris Houska, Matthias A. Müller, Mario E. Villanueva
This paper proposes novel approaches for designing control Lyapunov functions (CLFs) for constrained linear systems. We leverage recent configuration-constrained polyhedral computi…
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…
Intrinsic Separation Principles
Boris Houska
This paper is about output-feedback control problems for general linear systems in the presence of given state-, control-, disturbance-, and measurement error constraints. Because…
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…
Ambiguity Tube MPC
Fan Wu, Mario E. Villanueva, Boris Houska
This paper is about a class of distributionally robust model predictive controllers (MPC) for nonlinear stochastic processes that evaluate risk and control performance measures by…
Distributed MPC with ALADIN -- A Tutorial
Boris Houska, Jiahe Shi
This paper consists of a tutorial on the Augmented Lagrangian based Alternating Direction Inexact Newton method (ALADIN) and its application to distributed model predictive control…
Distributed Multi-Building Coordination for Demand Response
Junyan Su, Yuning Jiang, Altug Bitlislioglu +2
This paper presents a distributed optimization algorithm tailored for solving optimal control problems arising in multi-building coordination. The buildings coordinated by a grid o…
A set-theoretic generalization of dissipativity with applications in Tube MPC
Mario Eduardo Villanueva, Elena De Lazzari, Matthias Müller +1
This paper introduces a framework for analyzing a general class of uncertain nonlinear discrete-time systems with given state-, control-, and disturbance constraints. In particular…
Towards Global Optimal Control via Koopman Lifts
Mario E. Villanueva, Colin Jones, Boris Houska
This paper introduces a framework for solving time-autonomous nonlinear infinite horizon optimal control problems, under the assumption that all minimizers satisfy Pontryagin's nec…
Partially Distributed Outer Approximation
Alexander Murray, Timm Faulwasser, Veit Hagenmeyer +2
This paper presents a novel partially distributed outer approximation algorithm, named PaDOA, for solving a class of structured mixed integer convex programming (MICP) problems to…
Parallel Explicit Tube Model Predictive Control
Kai Wang, Yuning Jiang, Juraj Oravec +2
This paper is about a parallel algorithm for tube-based model predictive control. The proposed control algorithm solves robust model predictive control problems suboptimally, while…
Decentralized Optimization over Tree Graphs
Yuning Jiang, Dimitris Kouzoupis, Haoyu Yin +2
This paper presents a decentralized algorithm for non-convex optimization over tree-structured networks. We assume that each node of this network can solve small-scale optimization…
Backward-Forward Reachable Set Splitting for State-Constrained Differential Games
Xuhui Feng, Mario E. Villanueva, Boris Houska
This paper is about a set-based computing method for solving a general class of two-player zero-sum Stackelberg differential games. We assume that the game is modeled by a set of c…
Decomposition of non-convex optimization via bi-level distributed ALADIN
Alexander Engelmann, Yuning Jiang, Boris Houska +1
Decentralized optimization algorithms are important in different contexts, such as distributed optimal power flow or distributed model predictive control, as they avoid central coo…
Parallel Explicit Model Predictive Control
Yuning Jiang, Juraj Oravec, Boris Houska +1
This paper is about a real-time model predictive control (MPC) algorithm for large-scale, structured linear systems with polytopic state and control constraints. The proposed contr…
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…
Self-reflective model predictive control
Boris Houska, Dries Telen, Filip Logist +1
This paper proposes a novel control scheme, named self-reflective model predictive control, which takes its own limitations in the presence of process noise and measurement errors…