Zobrazeno 1 - 10
of 1 882
pro vyhledávání: '"De Schutter, P."'
PieceWise Affine (PWA) approximations for nonlinear functions have been extensively used for tractable, computationally efficient control of nonlinear systems. However, reaching a desired approximation accuracy without prior information about the beh
Externí odkaz:
http://arxiv.org/abs/2410.16960
Greenhouse climate control is concerned with maximizing performance in terms of crop yield and resource efficiency. One promising approach is model predictive control (MPC), which leverages a model of the system to optimize the control inputs, while
Externí odkaz:
http://arxiv.org/abs/2409.12789
This work proposes an approach that integrates reinforcement learning and model predictive control (MPC) to efficiently solve finite-horizon optimal control problems in mixed-logical dynamical systems. Optimization-based control of such systems with
Externí odkaz:
http://arxiv.org/abs/2409.11267
Nonlinear Programs (NLPs) are prevalent in optimization-based control of nonlinear systems. Solving general NLPs is computationally expensive, necessitating the development of fast hardware or tractable suboptimal approximations. This paper investiga
Externí odkaz:
http://arxiv.org/abs/2405.20387
Model mismatch often poses challenges in model-based controller design. This paper investigates model predictive control (MPC) of uncertain linear systems with input constraints, focusing on stability and closed-loop infinite-horizon performance. The
Externí odkaz:
http://arxiv.org/abs/2405.15552
Measuring the similarity between motions and established motion models is crucial for motion analysis, recognition, generation, and adaptation. To enhance similarity measurement across diverse contexts, invariant motion descriptors have been proposed
Externí odkaz:
http://arxiv.org/abs/2405.04392
This paper presents a novel approach for distributed model predictive control (MPC) for piecewise affine (PWA) systems. Existing approaches rely on solving mixed-integer optimization problems, requiring significant computation power or time. We propo
Externí odkaz:
http://arxiv.org/abs/2404.16712
Autor:
Cordiano, Francesco, De Schutter, Bart
Scenario reduction algorithms can be an effective means to provide a tractable description of the uncertainty in optimal control problems. However, they might significantly compromise the performance of the controlled system. In this paper, we propos
Externí odkaz:
http://arxiv.org/abs/2404.07746
In previous work on learning and controlling contact-rich tasks, the procedure for choosing a proper reference frame to express learned signals for the motion and the interaction wrench is often implicit, requires expert insight, or starts from propo
Externí odkaz:
http://arxiv.org/abs/2404.01900
The European Economic Area Electricity Network Benchmark (EEA-ENB) is a multi-area power system representing the European network of transmission systems for electricity to facilitate the application of distributed control techniques. In the EEA-ENB
Externí odkaz:
http://arxiv.org/abs/2403.14372