scholarly journals Variational Control Approach to Energy Extraction from a Fluid Flow

Energies ◽  
2020 ◽  
Vol 13 (18) ◽  
pp. 4913
Author(s):  
Gianluca Pepe ◽  
Federica Mezzani ◽  
Antonio Carcaterra ◽  
Luca Cedola ◽  
Franco Rispoli
Keyword(s):  
Optimal Control ◽  
Fluid Flow ◽  
Energy Harvesting ◽  
Control Theory ◽  
Wind Turbine ◽  
Optimal Control Theory ◽  
Maximum Efficiency ◽  
Time Interval ◽  
Electrical Machine ◽  
Control Approach

Energy harvesting from the environment is an important aspect of many technologies. The scale of energy capturing and storage can involve the power range from mWatt up to MWatt, depending on the used devices and the considered environments (from ambient acoustic and vibration to ocean wave motion, or wind). In this paper, the wind turbine energy harvesting problem is approached as an optimal control problem, where the objective function is the absorption of an amount of energy in a given time interval by a fluid-flow environment, that should be maximized. The interest relies on outlining general control models of fluid-flow-based extraction plants and identifying an optimum strategy for the regulation of an electrical machine to obtain a maximum-efficiency process for the related energy storage. The mathematical tools are found in the light of optimal control theory, where solutions to the fundamental equations are in the frame of Variational Control (the basis of the Pontryagin optimal control theory). A special problem, named Optimally Controlled Betz’s Machine OCBM-optimal control steady wind turbine, is solved in closed form, and it is shown that, in the simpler steady case, it reproduces the maximum efficiency machine developed in Betz’s theory.

Optimal Control of a Wind Turbine for Tradeoff Analysis Between Energy Harvesting and Noise Emission

2013 ◽  
Author(s):  
Mohamed L. Shaltout ◽  
Dongmei Chen
Keyword(s):  
Optimal Control ◽  
Energy Harvesting ◽  
Wind Turbine ◽  
Load Condition ◽  
Noise Emission ◽  
Continuous Growth ◽  
Control Approach ◽  
The Public ◽  
Partial Load ◽  
Blade Pitch Angle

An optimal control approach for a wind turbine drivetrain with the objective of maximizing energy harvesting and minimizing noise emission is presented. One of the major challenges facing the public acceptance for continuous growth of wind turbine installation is its noise emission. However, reducing the noise emission could lead to decreased wind energy harvesting. As a result, a tradeoff arises between power generation and noise emission, especially when a wind turbine operates under the partial-load condition. This paper will show that through controlling the generator electromagnetic torque and/or the blade pitch angle, an optimal tradeoff between wind turbine energy harvesting and noise emission can be obtained. The dynamic model of a wind turbine drivetrain and a noise emission prediction model are also presented. Simulation results of using the proposed control design for different wind speed ranges are analyzed and compared.

scholarly journals A minimum trapping time problem in optimal control theory

1990 ◽  
Vol 32 (1) ◽  
pp. 100-114 ◽  
Author(s):  
M. E. Fisher ◽  
J. L. Noakes ◽  
K. L. Teo
Keyword(s):  
Optimal Control ◽  
Control Theory ◽  
Optimal Control Theory ◽  
Natural Extension ◽  
Computational Procedure ◽  
Fixed Time ◽  
Minimum Time ◽  
Time Interval ◽  
Trapping Time ◽  
Time Problem

AbstractIn this paper we consider a natural extension of the minimum time problem in optimal control theory which we refer to as the minimum trapping time problem. The minimum trapping time problem requires a fixed time interval [0, T], where T is finite. The aim is to determine a control for which the system trajectory not only reaches a specified target in minimum time but also remains trapped within the target until time T. Our aim is to devise a computational procedure for solving the minimum trapping time problem. The computational procedure we adopt uses control parametrisation in which the class of controls is approximated by a class of piecewise constant functions. The problem we are solving is therefore an approximation to the original minimum trapping time problem. Some properties for the approximate problem are then established. These lead to an extremely efficient iterative procedure for calculating the minimum trapping time.

Dispersion of nanoparticles with optimal control theory based on destabilization

2014 ◽  
Vol 2 ◽  
pp. 86-86
Author(s):  
Miki U. Kobayashi ◽  
Nobuaki Aoki ◽  
Noriyoshi Manabe ◽  
Tadafumi Adschiri
Keyword(s):  
Optimal Control ◽  
Control Theory ◽  
Optimal Control Theory ◽  
Dispersion Of Nanoparticles

scholarly journals Recoil control of deepwater drilling riser system based on optimal control theory

2020 ◽  
pp. 108473
Author(s):  
Xiuquan Liu ◽  
Zhaowei Liu ◽  
Xianglei Wang ◽  
Nan Zhang ◽  
Na Qiu ◽  
...  
Keyword(s):  
Optimal Control ◽  
Control Theory ◽  
Optimal Control Theory ◽  
Deepwater Drilling

scholarly journals Optimal Control for a COVID-19 Model Accounting for Symptomatic and Asymptomatic

2020 ◽  
Vol 8 (1) ◽  
pp. 168-179
Author(s):  
Jead M. Macalisang ◽  
Mark L. Caay ◽  
Jayrold P. Arcede ◽  
Randy L. Caga-anan
Keyword(s):  
Optimal Control ◽  
Control Theory ◽  
Medical Care ◽  
Optimal Control Theory ◽  
Comparable Result ◽  
Type Model ◽  
Hospital Beds ◽  
Transmission Reduction ◽  
Bed Capacity ◽  
The Government

AbstractBuilding on an SEIR-type model of COVID-19 where the infecteds are further divided into symptomatic and asymptomatic, a system incorporating the various possible interventions is formulated. Interventions, also referred to as controls, include transmission reduction (e.g., lockdown, social distancing, barrier gestures); testing/isolation on the exposed, symptomatic and asymptomatic compartments; and medical controls such as enhancing patients’ medical care and increasing bed capacity. By considering the government’s capacity, the best strategies for implementing the controls were obtained using optimal control theory. Results show that, if all the controls are to be used, the more able the government is, the more it should implement transmission reduction, testing, and enhancing patients’ medical care without increasing hospital beds. However, if the government finds it very difficult to implement the controls for economic reasons, the best approach is to increase the hospital beds. Moreover, among the testing/isolation controls, testing/isolation in the exposed compartment is the least needed when there is significant transmission reduction control. Surprisingly, when there is no transmission reduction control, testing/isolation in the exposed should be optimal. Testing/isolation in the exposed could seemingly replace the transmission reduction control to yield a comparable result to that when the transmission reduction control is being implemented.

Low-power homonuclear dipolar recoupling in solid-state NMR developed using optimal control theory

2005 ◽  
Vol 414 (1-3) ◽  
pp. 204-209 ◽  
Author(s):  
Cindie Kehlet ◽  
Thomas Vosegaard ◽  
Navin Khaneja ◽  
Steffen J. Glaser ◽  
Niels Chr. Nielsen
Keyword(s):  
Optimal Control ◽  
Solid State ◽  
Control Theory ◽  
Low Power ◽  
Optimal Control Theory ◽  
Solid State Nmr ◽  
Dipolar Recoupling
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