Zobrazeno 1 - 10
of 362 386
pro vyhledávání: '"MPC."'
Accurate and comprehensive 3D sensing using LiDAR systems is crucial for various applications in photogrammetry and robotics, including facility inspection, Building Information Modeling (BIM), and robot navigation. Motorized LiDAR systems can expand
Externí odkaz:
http://arxiv.org/abs/2412.13873
In this paper, a learning based Model Predictive Control (MPC) using a low dimensional residual model is proposed for autonomous driving. One of the critical challenge in autonomous driving is the complexity of vehicle dynamics, which impedes the for
Externí odkaz:
http://arxiv.org/abs/2412.03874
Model predictive control (MPC) has become increasingly popular for the control of robot manipulators due to its improved performance compared to instantaneous control approaches. However, tuning these controllers remains a considerable hurdle. To add
Externí odkaz:
http://arxiv.org/abs/2412.01597
Publikováno v:
Europhysics Letters 148, (2024) 49002
Weak lensing exhibits that rotation curves of isolated galaxies remain flat up to Mpc scale (Mistele et al, 2024). Recently we proposed that dark matter is a combination of electrostatic and vacuum energy in standard physics. In this theory, isolated
Externí odkaz:
http://arxiv.org/abs/2411.18221
Autor:
Kuntz, Steven J., Rawlings, James B.
We consider the asymptotic stability of MPC under plant-model mismatch, considering primarily models where the origin remains a steady state despite mismatch. Our results differ from prior results on the inherent robustness of MPC, which guarantee on
Externí odkaz:
http://arxiv.org/abs/2411.15452
Autor:
Lee, Hotae, Borrelli, Francesco
We propose a novel Stochastic Model Predictive Control (MPC) for uncertain linear systems subject to probabilistic constraints. The proposed approach leverages offline learning to extract key features of affine disturbance feedback policies, signific
Externí odkaz:
http://arxiv.org/abs/2411.13935
Autor:
van Leeuwen, Steven, Kolmanovsky, Ilya
The paper considers a computational governor strategy to facilitate the implementation of Model Predictive Control (MPC) based on inexact optimization when the time available to compute the solution may be insufficient. In the setting of linear-quadr
Externí odkaz:
http://arxiv.org/abs/2411.07919
This paper presents a stochastic model predictive control (SMPC) algorithm for linear systems subject to additive Gaussian mixture disturbances, with the goal of satisfying chance constraints. To synthesize a control strategy, the stochastic control
Externí odkaz:
http://arxiv.org/abs/2411.07887
This paper presents a data-driven min-max model predictive control (MPC) scheme for linear parameter-varying (LPV) systems. Contrary to existing data-driven LPV control approaches, we assume that the scheduling signal is unknown during offline data c
Externí odkaz:
http://arxiv.org/abs/2411.05624