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Paper Information

Journal:   JOURNAL OF ARTIFICIAL INTELLIGENCE IN ELECTRICAL ENGINEERING   SEPTEMBER 2014 , Volume 3 , Number 10; Page(s) 8 To 15.
 
Paper: 

REINFORCEMENT LEARNING BASED PID CONTROL OF WIND ENERGY CONVERSION SYSTEMS

 
 
Author(s):  AKBARI MOHAMMAD ESMAEIL, GHADIMI NORADDIN*
 
* YOUNG RESEARCHERS AND ELITE CLUBARDABIL BRANCH, ISLAMIC AZAD UNIVERSITY, ARDABIL, IRAN
 
Abstract: 

In this paper an adaptive PID controller for Wind Energy Conversion Systems (WECS) has been developed. The adaptation technique applied to this controller is based on Reinforcement Learning (RL) theory. Nonlinear characteristics of wind variations as plant input, wind turbine structure and generator operational behavior demand for high quality adaptive controller to ensure both robust stability and safe performance. Thus, a reinforcement learning algorithm is used for online tuning of PID coefficients in order to enhance closed loop system performance. In this study, at start the proposed controller is applied to two pure mathematical plants, and then the closed loop WECS behavior is discussed in the presence of a major disturbance.

 
Keyword(s): ADAPTIVE CONTROL, WECS, REINFORCEMENT LEARNING
 
References: 
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