Zobrazeno 1 - 10
of 195 025
pro vyhledávání: '"Nonlinear Model"'
Autor:
Schäfke, Hendrik, Habich, Tim-Lukas, Muhmann, Christian, Ehlers, Simon F. G., Seel, Thomas, Schappler, Moritz
Soft robots pose difficulties in terms of control, requiring novel strategies to effectively manipulate their compliant structures. Model-based approaches face challenges due to the high dimensionality and nonlinearities such as hysteresis effects. I
Externí odkaz:
http://arxiv.org/abs/2411.05616
Nonlinear Model Predictive Control (NMPC) is a general and flexible control approach, used in many industrial contexts, and is based on the online solution of a nonlinear optimization problem. This operation requires in general a high computational c
Externí odkaz:
http://arxiv.org/abs/2410.19467
Autor:
Pandey, Pushpa, Khodaparast, Hamed Haddad, Friswell, Michael Ian, Chatterjee, Tanmoy, Madinei, Hadi, Deighan, Tom
The study presents a novel approach for stochastic nonlinear model updating in structural dynamics, employing a Bayesian framework integrated with Markov Chain Monte Carlo (MCMC) sampling for parameter estimation by using an approximated likelihood f
Externí odkaz:
http://arxiv.org/abs/2410.11902
Multi-quadrotor systems face significant challenges in decentralized control, particularly with safety and coordination under sensing and communication limitations. State-of-the-art methods leverage Control Barrier Functions (CBFs) to provide safety
Externí odkaz:
http://arxiv.org/abs/2409.17379
This article presents a Visual Servoing Nonlinear Model Predictive Control (NMPC) scheme for autonomously tracking a moving target using multirotor Unmanned Aerial Vehicles (UAVs). The scheme is developed for surveillance and tracking of contour-base
Externí odkaz:
http://arxiv.org/abs/2409.16665
Variational Autoencoders (VAEs) are a powerful framework for learning compact latent representations, while NeuralODEs excel in learning transient system dynamics. This work combines the strengths of both to create fast surrogate models with adjustab
Externí odkaz:
http://arxiv.org/abs/2410.10174