Fuzzy PID controller design using Q-learning algorithm with a manipulated reward function

Vahid Tavakol Aghaei, Ahmet Onat, Ibrahim Eksin, Mujde Guzelkaya

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12 Atıf (Scopus)

Özet

In this paper we propose a manipulated reward function for the Q-learning algorithm which is a reinforcement learning technique and utilize the proposed algorithm to tune the parameters of the input-output membership functions of fuzzy logic controllers. The use of a reward signal to formalize the idea of a goal is one of the most distinctive features of reinforcement learning. To improve both the performance and convergence criteria of the mentioned algorithm we propose a fuzzy structure for the reward function. In order to demonstrate the effectiveness of the algorithm we apply it to two second order linear systems with and without time delay and finally a nonlinear system will be examined.

Orijinal dilİngilizce
Ana bilgisayar yayını başlığı2015 European Control Conference, ECC 2015
YayınlayanInstitute of Electrical and Electronics Engineers Inc.
Sayfalar2502-2507
Sayfa sayısı6
ISBN (Elektronik)9783952426937
DOI'lar
Yayın durumuYayınlandı - 16 Kas 2015
EtkinlikEuropean Control Conference, ECC 2015 - Linz, Austria
Süre: 15 Tem 201517 Tem 2015

Yayın serisi

Adı2015 European Control Conference, ECC 2015

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???event.eventtypes.event.conference???European Control Conference, ECC 2015
Ülke/BölgeAustria
ŞehirLinz
Periyot15/07/1517/07/15

Bibliyografik not

Publisher Copyright:
© 2015 EUCA.

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