Zobrazeno 1 - 10
of 225
pro vyhledávání: '"A Rupenyan"'
Singularities, manifesting as special configuration states, deteriorate robot performance and may even lead to a loss of control over the system. This paper addresses the kinematic singularity concerns in robotic systems with model mismatch and actua
Externí odkaz:
http://arxiv.org/abs/2411.07830
Unwanted vibrations stemming from the energy-optimized design of Delta robots pose a challenge in their operation, especially with respect to precise reference tracking. To improve tracking accuracy, this paper proposes an adaptive mismatch-compensat
Externí odkaz:
http://arxiv.org/abs/2411.07862
Ensuring safety is a key aspect in sequential decision making problems, such as robotics or process control. The complexity of the underlying systems often makes finding the optimal decision challenging, especially when the safety-critical system is
Externí odkaz:
http://arxiv.org/abs/2409.18000
Autor:
Kavas, Baris, Balta, Efe C., Tucker, Michael R., Krishnadas, Raamadaas, Rupenyan, Alisa, Lygeros, John, Bambach, Markus
Open-loop control of laser powder bed fusion (LPBF) additive manufacturing (AM) has enabled the production of complex, high-criticality parts for various industries. This method relies on static parameter sets from extensive experimentation and simul
Externí odkaz:
http://arxiv.org/abs/2406.19096
Controller tuning and parameter optimization are crucial in system design to improve closed-loop system performance. Bayesian optimization has been established as an efficient model-free controller tuning and adaptation method. However, Bayesian opti
Externí odkaz:
http://arxiv.org/abs/2404.14602
In this paper, we consider the problem of reference tracking in uncertain nonlinear systems. A neural State-Space Model (NSSM) is used to approximate the nonlinear system, where a deep encoder network learns the nonlinearity from data, and a state-sp
Externí odkaz:
http://arxiv.org/abs/2404.12097
This article presents the guided Bayesian optimization algorithm as an efficient data-driven method for iteratively tuning closed-loop controller parameters using an event-triggered digital twin of the system based on available closed-loop data. We d
Externí odkaz:
http://arxiv.org/abs/2403.16619
Autor:
Guidetti, Xavier, Mingard, Nathan, Cruz-Oliver, Raul, Nagel, Yannick, Rueppel, Marvin, Rupenyan, Alisa, Balta, Efe C., Lygeros, John
In material extrusion additive manufacturing, the extrusion process is commonly controlled in a feed-forward fashion. The amount of material to be extruded at each printing location is pre-computed by a planning software. This approach is inherently
Externí odkaz:
http://arxiv.org/abs/2403.16042
Online Feedback Optimization (OFO) controllers steer a system to its optimal operating point by treating optimization algorithms as auxiliary dynamic systems. Implementation of OFO controllers requires setting the parameters of the optimization algor
Externí odkaz:
http://arxiv.org/abs/2312.01996
Autor:
Liao-McPherson, Dominic, Balta, Efe C., Afrasiabi, Mohamadreza, Rupenyan, Alisa, Bambach, Markus, Lygeros, John
Additive manufacturing processes are flexible and efficient technologies for producing complex geometries. However, ensuring reliability and repeatability is challenging due to the complex physics and various sources of uncertainty in the process. In
Externí odkaz:
http://arxiv.org/abs/2311.10218