Reconfigurable sensor networks with a real time optimization method

2012 ◽  
Author(s):  
Oscar Quevedo-Teruel ◽  
Eva Rajo-Iglesias
Keyword(s):  
Sensor Networks ◽  
Real Time ◽  
Optimization Method ◽  
Time Optimization ◽  
Real Time Optimization

scholarly journals ADAPTIVE DISTRIBUTION OF A SWARM OF HETEROGENEOUS ROBOTS

2016 ◽  
Vol 56 (1) ◽  
pp. 67 ◽  
Author(s):  
Amanda Prorok ◽  
M. Ani Hsieh ◽  
Vijay Kumar
Keyword(s):  
Real Time ◽  
Large Scale ◽  
Optimization Problem ◽  
Optimization Method ◽  
Transition Rates ◽  
Trait Distribution ◽  
Time Optimization ◽  
Heterogeneous Robots ◽  
Real Time Optimization ◽  
Optimal Set

We present a method that distributes a swarm of heterogeneous robots among a set of tasks that require specialized capabilities in order to be completed. We model the system of heterogeneous robots as a community of species, where each species (robot type) is defined by the traits (capabilities) that it owns. Our method is based on a continuous abstraction of the swarm at a macroscopic level as we model robots switching between tasks. We formulate an optimization problem that produces an optimal set of transition rates for each species, so that the desired trait distribution is reached as quickly as possible. Since our method is based on the derivation of an analytical gradient, it is very efficient with respect to state-of-the-art methods. Building on this result, we propose a real-time optimization method that enables an online adaptation of transition rates. Our approach is well-suited for real-time applications that rely on online redistribution of large-scale robotic systems.

On-Board Real-Time Optimization Control for Turbo-Fan Engine Life Extending

2016 ◽  
Vol 0 (0) ◽  
Author(s):  
Qiangang Zheng ◽  
Haibo Zhang ◽  
Lizhen Miao ◽  
Fengyong Sun
Keyword(s):  
Real Time ◽  
Optimization Method ◽  
Support Vector ◽  
Thermal Mechanical Fatigue ◽  
Mechanical Fatigue ◽  
Time Optimization ◽  
Optimization Control ◽  
Conventional Optimization ◽  
Real Time Optimization ◽  
Engine Life

AbstractA real-time optimization control method is proposed to extend turbo-fan engine service life. This real-time optimization control is based on an on-board engine mode, which is devised by a MRR-LSSVR (multi-input multi-output recursive reduced least squares support vector regression method). To solve the optimization problem, a FSQP (feasible sequential quadratic programming) algorithm is utilized. The thermal mechanical fatigue is taken into account during the optimization process. Furthermore, to describe the engine life decaying, a thermal mechanical fatigue model of engine acceleration process is established. The optimization objective function not only contains the sub-item which can get fast response of the engine, but also concludes the sub-item of the total mechanical strain range which has positive relationship to engine fatigue life. Finally, the simulations of the conventional optimization control which just consider engine acceleration performance or the proposed optimization method have been conducted. The simulations demonstrate that the time of the two control methods from idle to 99.5 % of the maximum power are equal. However, the engine life using the proposed optimization method could be surprisingly increased by 36.17 % compared with that using conventional optimization control.

Real-time Optimization Method for Optical Parameters of Ion Implanters

2006 ◽  
Author(s):  
Seiji Ogata ◽  
Tsutomu Nishihashi ◽  
Kazuhiko Tonari ◽  
Hidekazu Yokoo ◽  
Hideo Suzuki ◽  
...  
Keyword(s):  
Real Time ◽  
Optimization Method ◽  
Optical Parameters ◽  
Time Optimization ◽  
Real Time Optimization

scholarly journals A real-time optimization method for economic and effective operation of electrostatic precipitators

2020 ◽  
Vol 70 (7) ◽  
pp. 708-720
Author(s):  
Chenghang Zheng ◽  
Zhongyang Zhao ◽  
Yishan Guo ◽  
Haitao Zhao ◽  
Weiguo Weng ◽  
...  
Keyword(s):  
Real Time ◽  
Optimization Method ◽  
Time Optimization ◽  
Effective Operation ◽  
Electrostatic Precipitators ◽  
Real Time Optimization
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