50 citations · 79 across the 19 of their papers we have counts for
20 papers
Anderson Acceleration for Linearly Converging SQP-Type Methods
Jonathan Frey, David Kiessling, Katrin Baumgärtner +1
Although Anderson acceleration (AA) is known to speed up fixed-point iterations, it is rarely applied in constrained optimization, in particular sequential quadratic programming (S…
Riccati-ZORO: An efficient algorithm for heuristic online optimization of internal feedback laws in robust and stochastic model predictive control
Florian Messerer, Yunfan Gao, Jonathan Frey +1
We present Riccati-ZORO, an algorithm for tube-based optimal control problems (OCP). Tube OCPs predict a tube of trajectories to capture predictive uncertainty. The tube induces a…
Differentiable Nonlinear Model Predictive Control
Jonathan Frey, Katrin Baumgärtner, Gianluca Frison +5
The efficient computation of parametric solution sensitivities is a key challenge in the integration of learning-enhanced methods with nonlinear model predictive control (MPC), as…
MPC4RL -- A Software Package for Reinforcement Learning based on Model Predictive Control
Dirk Reinhardt, Katrin Baumgärnter, Jonathan Frey +2
In this paper, we present an early software integrating Reinforcement Learning (RL) with Model Predictive Control (MPC). Our aim is to make recent theoretical contributions from th…
L4acados: Learning-based models for acados, applied to Gaussian process-based predictive control
Amon Lahr, Joshua Näf, Kim P. Wabersich +5
Incorporating learning-based models, such as artificial neural networks or Gaussian processes, into model predictive control (MPC) strategies can significantly improve control perf…
Multi-Phase Optimal Control Problems for Efficient Nonlinear Model Predictive Control with acados
Jonathan Frey, Katrin Baumgärtner, Gianluca Frison +1
Computationally efficient nonlinear model predictive control relies on elaborate discrete-time optimal control problem (OCP) formulations trading off accuracy with respect to the c…
Fast Generation of Feasible Trajectories in Direct Optimal Control
David Kiessling, Katrin Baumgärtner, Jonathan Frey +3
This paper examines the question of finding feasible points to discrete-time optimal control problems. The optimization problem of finding a feasible trajectory is transcribed to a…
Advanced-Step Real-time Iterations with Four Levels -- New Error Bounds and Fast Implementation in acados
Jonathan Frey, Armin Nurkanovic, Moritz Diehl
The Real-Time Iteration (RTI) is an online nonlinear model predictive control algorithm that performs a single Sequential Quadratic Programming (SQP) per sampling time. The algorit…
Efficient Zero-Order Robust Optimization for Real-Time Model Predictive Control with acados
Jonathan Frey, Yunfan Gao, Florian Messerer +3
Robust and stochastic optimal control problem (OCP) formulations allow a systematic treatment of uncertainty, but are typically associated with a high computational cost. The recen…
Gauss-Newton Runge-Kutta Integration for Efficient Discretization of Optimal Control Problems with Long Horizons and Least-Squares Costs
Jonathan Frey, Katrin Baumgärtner, Moritz Diehl
This work proposes an efficient treatment of continuous-time optimal control problem (OCP) with long horizons and nonlinear least-squares costs. The Gauss-Newton Runge-Kutta (GNRK)…
Finite Elements with Switch Detection for Numerical Optimal Control of Nonsmooth Dynamical Systems with Set-Valued Heaviside Step Functions
Armin Nurkanović, Anton Pozharskiy, Jonathan Frey +1
This paper develops high-accuracy methods for numerically solving optimal control problems subject to nonsmooth differential equations with set-valued step functions. A notable sub…
Collision-free Motion Planning for Mobile Robots by Zero-order Robust Optimization-based MPC
Yunfan Gao, Florian Messerer, Jonathan Frey +2
This paper presents an implementation of robust model predictive control (MPC) for collision-free reference trajectory tracking for mobile robots. The presented approach considers…
FESD-J: Finite Elements with Switch Detection for Numerical Optimal Control of Rigid Bodies with Impacts and Coulomb Friction
Armin Nurkanović, Jonathan Frey, Anton Pozharskiy +1
The Finite Elements with Switch Detection (FESD) is a high-accuracy method for the numerical simulation and solution of optimal control problems subject to discontinuous ODEs. In t…
Imitation Learning from Nonlinear MPC via the Exact Q-Loss and its Gauss-Newton Approximation
Andrea Ghezzi, Jasper Hoffman, Jonathan Frey +2
This work presents a novel loss function for learning nonlinear Model Predictive Control policies via Imitation Learning. Standard approaches to Imitation Learning neglect informat…
Finite Elements with Switch Detection for Direct Optimal Control of Nonsmooth Systems with Set-Valued Step Functions
Armin Nurkanović, Jonathan Frey, Anton Pozharskiy +1
This paper extends the Finite Elements with Switch Detection (FESD) method [Nurkanović et al., 2022] to optimal control problems with nonsmooth systems involving set-valued step fu…
Frenet-Cartesian Model Representations for Automotive Obstacle Avoidance within Nonlinear MPC
Rudolf Reiter, Armin Nurkanović, Jonathan Frey +1
In recent years, nonlinear model predictive control (NMPC) has been extensively used for solving automotive motion control and planning tasks. In order to formulate the NMPC proble…
Fast integrators with sensitivity propagation for use in CasADi
Jonathan Frey, Jochem De Schutter, Moritz Diehl
Efficient integrators with sensitivity propagation are an essential ingredient for the numerical solution of optimal control problems. This paper gives an overview on the acados in…
Active Learning of Discrete-Time Dynamics for Uncertainty-Aware Model Predictive Control
Alessandro Saviolo, Jonathan Frey, Abhishek Rathod +2
Model-based control requires an accurate model of the system dynamics for precisely and safely controlling the robot in complex and dynamic environments. Moreover, in the presence…
Introducing the quadratically-constrained quadratic programming framework in HPIPM
Gianluca Frison, Jonathan Frey, Florian Messerer +2
This paper introduces the quadratically-constrained quadratic programming (QCQP) framework recently added in HPIPM alongside the original quadratic-programming (QP) framework. The…
acados: a modular open-source framework for fast embedded optimal control
Robin Verschueren, Gianluca Frison, Dimitris Kouzoupis +7
This paper presents the acados software package, a collection of solvers for fast embedded optimization intended for fast embedded applications. Its interfaces to higher-level lang…