Robust Wake Steering Control Design in a Wind Farm for Power Optimization Using Adaptive Learning Game Theory (ALGT) Method

2021 ◽  
pp. 1-0
Author(s):  
Vahid Fazlollahi ◽  
Farzad A. Shirazi ◽  
Mostafa Taghizadeh ◽  
Shahin Siahpour
Keyword(s):  
Game Theory ◽  
Adaptive Learning ◽  
Wind Farm ◽  
Power Optimization ◽  
Control Design ◽  
Steering Control ◽  
Learning Game

An E/H Control Design for a Hydraulic Variable Displacement Axial Piston Motor

2011 ◽  
Author(s):  
Hongliu Du
Keyword(s):  
Adaptive Learning ◽  
Lower Cost ◽  
Learning Algorithm ◽  
Control Design ◽  
Test Results ◽  
Satisfactory Performance ◽  
Control Scheme ◽  
Variable Displacement ◽  
System Uncertainties ◽  
Axial Piston

A simple and novel speed control scheme for variable displacement motors has been developed under the consideration of some system uncertainties. Theoretical analysis and experimental test results have shown that the proposed control strategy is capable of driving the swashplate to track its desired trajectory with robust stability and satisfactory performance. An adaptive learning algorithm enables the controls to automatically adjust for uncertainties in the control bias current. Compared with its hydro-mechanical counterpart, the provided E/H control results in a hydraulic variable displacement motor with lower cost and better performance.

Learning Game Theory from John Harsanyi

2001 ◽  
Vol 36 (1) ◽  
pp. 20-25 ◽  
Author(s):  
Roger Myerson
Keyword(s):  
Game Theory ◽  
Learning Game ◽  
John Harsanyi

scholarly journals Consensus based on learning game theory with a UAV rendezvous application

2015 ◽  
Vol 28 (1) ◽  
pp. 191-199 ◽  
Author(s):  
Zhongjie Lin ◽  
Hugh hong-tao Liu
Keyword(s):  
Game Theory ◽  
Learning Game
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