A deterministic-control-based approach motion by curvature

2005 ◽  
Vol 59 (3) ◽  
pp. 344-407 ◽  
Author(s):  
Robert Kohn ◽  
Sylvia Serfaty
Keyword(s):  
Motion By Curvature ◽  
Deterministic Control

Simultaneous Deterministic Control of Distant Qubits in Two Semiconductor Quantum Dots

Nano Letters ◽  
2013 ◽  
Vol 13 (10) ◽  
pp. 4666-4670 ◽  
Author(s):  
A. Gamouras ◽  
R. Mathew ◽  
S. Freisem ◽  
D. G. Deppe ◽  
K. C. Hall
Keyword(s):  
Quantum Dots ◽  
Semiconductor Quantum Dots ◽  
Deterministic Control

The Optimization of Adaptive PID Control Algorithm Based on RBF Neural Network

2014 ◽  
Vol 998-999 ◽  
pp. 943-946
Author(s):  
Jing Liu ◽  
Guo Xin Wang
Keyword(s):  
Neural Network ◽  
Pid Controller ◽  
Rbf Neural Network ◽  
High Reliability ◽  
Simple Algorithm ◽  
Poor Performance ◽  
Learning Ability ◽  
The Neural Network ◽  
Pid Controller Tuning ◽  
Deterministic Control

As the earliest practical controller, PID controller has more than 50 years of history, and it is still the most widely used and most common industrial controllers. PID controller is simple to understand and use, without a prerequisite for an accurate model of the physical system, thus become the most popular, the most common controller. The reason why PID controller is the first developed one is that its simple algorithm, robustness and high reliability. It is widely used in process control and motion control, especially for accurate mathematical model that can be established deterministic control system. But the conventional PID controller tuning parameters are often poor performance, poor adaptability to the operating environment. The neural network has a strong nonlinear mapping ability, competence, self-learning ability of associative memory, and has a viable quantities of information processing methods and good fault tolerance.

Motion by curvature in generalized Cahn-Allen models

1994 ◽  
Vol 77 (1-2) ◽  
pp. 173-181 ◽  
Author(s):  
Paul C. Fife ◽  
Andrew A. Lacey
Keyword(s):  
Motion By Curvature

scholarly journals Approximate Controllability of Sobolev Type Nonlocal Fractional Stochastic Dynamic Systems in Hilbert Spaces

2013 ◽  
Vol 2013 ◽  
pp. 1-10 ◽  
Author(s):  
Mourad Kerboua ◽  
Amar Debbouche ◽  
Dumitru Baleanu
Keyword(s):  
Control Systems ◽  
Hilbert Spaces ◽  
Dynamic Systems ◽  
Approximate Controllability ◽  
Dynamic Control ◽  
Sufficient Conditions ◽  
Sobolev Type ◽  
Stochastic Dynamic ◽  
Deterministic Control ◽  
Stochastic Dynamic Systems

We study a class of fractional stochastic dynamic control systems of Sobolev type in Hilbert spaces. We use fixed point technique, fractional calculus, stochastic analysis, and methods adopted directly from deterministic control problems for the main results. A new set of sufficient conditions for approximate controllability is formulated and proved. An example is also given to provide the obtained theory.

scholarly journals Motion by curvature of planar networks

2009 ◽  
pp. 235-324
Author(s):  
Carlo Mantegazza ◽  
Matteo Novaga ◽  
Vincenzo Maria Tortorelli
Keyword(s):  
Motion By Curvature ◽  
Planar Networks

scholarly journals Determinants of haemosporidian single and co-infections risks in western paleartic birds

2021 ◽  
Author(s):  
Romain Pigeault ◽  
Mathieu Chevalier ◽  
Camille-sophie Cozzarolo ◽  
Molly Baur ◽  
Mathilde Arlettaz ◽  
...  
Keyword(s):  
Life History Strategy ◽  
Infection Risk ◽  
Single Infection ◽  
Modelling Framework ◽  
Infection Pattern ◽  
Haemosporidian Parasites ◽  
In The Wild ◽  
Deterministic Control ◽  
Parasite Evolution ◽  
Multiple Pathogens

Co-infections with multiple pathogens are common in the wild and may act as a strong selective pressure on both host and parasite evolution. Yet, contrary to single infection, the factors that shape co-infection risk are largely under-investigated. Here, we explored the extent to which bird ecology and phylogeny impact single and co-infection probabilities by haemosporidian parasites using large datasets from museum collections and a Bayesian phylogenetic modelling framework. While both phylogeny and species attributes (e.g. size of the geographic range, life-history strategy, migration) were relevant predictors of co-infection risk, these factors were less pertinent in predicting the probability of being single infected. Our study suggests that co-infection risk is under a stronger deterministic control than single-infection risk. These results underscore the combined influence of host evolutionary history and species attributes in determining single and co-infection pattern providing new avenues regarding our ability to predict infection risk in the wild.

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