Searched for: subject:"parametric%5C+uncertainties"
(1 - 5 of 5)
document
Koryakovskiy, I. (author)
Reinforcement learning is an active research area in the fields of artificial intelligence and machine learning, with applications in control. The most important feature of reinforcement learning is its ability to learn without prior knowledge about the system. However, in the real world, reinforcement learning actions may lead to serious damage...
doctoral thesis 2018
document
Yuan, S. (author)
As a special class of hybrid systems, switched systems have attracted a lot of attention in the last decade due to theoretical and practical interests. When controlling switched systems, a ubiquitous problem is the presence of large parametric uncertainties and external disturbances. However, the state of the art on adaptive and robust control...
doctoral thesis 2018
document
Koryakovskiy, I. (author), Kudruss, M. (author), Babuska, R. (author), Caarls, W. (author), Kirches, Christian (author), Mombaur, Katja (author), Schlöder, Johannes P. (author), Vallery, H. (author)
Model-free reinforcement learning and nonlinear model predictive control are two different approaches for controlling a dynamic system in an optimal way according to a prescribed cost function. Reinforcement learning acquires a control policy through exploratory interaction with the system, while nonlinear model predictive control exploits an...
journal article 2017
document
ur Rehman, S. (author), Langelaar, M. (author)
A novel technique for efficient global robust optimization of problems affected by parametric uncertainties is proposed. The method is especially relevant to problems that are based on expensive computer simulations. The globally robust optimal design is obtained by searching for the best worst-case cost, which involves a nested min-max...
journal article 2015
document
Loeven, G.J.A. (author)
When modeling physical systems, several sources of uncertainty are present. For example, variability in boundary conditions like free stream velocity or ambient pressure are always present. Furthermore, uncertainties in geometry arise from production tolerances, wear or unknown deformations under loading. Uncertainties in computational fluid...
doctoral thesis 2010
Searched for: subject:"parametric%5C+uncertainties"
(1 - 5 of 5)