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101 0 _aeng
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181 0 _ai
182 0 _ab
200 1 _aFractional Order PID Controller Design for an AVR System Using Chaotic Yellow Saddle Goatfish Algorithm
_fM. Micev, M. Calasan, D. A. Oliva Navarro
203 _aText
_celectronic
300 _aTitle screen
320 _a[References: 33 tit.]
330 _aThis paper presents a novel method for optimal tunning of a Fractional Order Proportional-Integral-Derivative (FOPID) controller for an Automatic Voltage Regulator (AVR) system. The presented method is based on the Yellow Saddle Goatfish Algorithm (YSGA), which is improved with Chaotic Logistic Maps. Additionally, a novel objective function for the optimization of the FOPID parameters is proposed. The performance of the obtained FOPID controller is verified by comparison with various FOPID controllers tuned by other metaheuristic algorithms. A comparative analysis is performed in terms of step response, frequency response, root locus, robustness test, and disturbance rejection ability. Results of the simulations undoubtedly show that the FOPID controller tuned with the proposed Chaotic Yellow Saddle Goatfish Algorithm (C-YSGA) outperforms FOPID controllers tuned by other algorithms, in all of the previously mentioned performance tests.
461 _tMathematics
463 _tVol. 8, iss. 7
_v[1182, 21 p.]
_d2020
610 1 _aэлектронный ресурс
610 1 _aтруды учёных ТПУ
610 1 _aautomatic voltage regulation system
610 1 _achaotic optimization
610 1 _afractional order proportional-integral-derivative controller
610 1 _ayellow saddle goatfish algorithm
610 1 _aсистема автоматического регулирования
610 1 _aоптимизация
700 1 _aMicev
_bM.
701 1 _aCalasan
_bM.
701 1 _aOliva Navarro
_bD. A.
_cspecialist in the field of informatics and computer technology
_cProfessor of Tomsk Polytechnic University
_f1983-
_gDiego Alberto
_2stltpush
_3(RuTPU)RU\TPU\pers\37366
712 0 2 _aНациональный исследовательский Томский политехнический университет
_bИнженерная школа информационных технологий и робототехники
_bОтделение информационных технологий
_h7951
_2stltpush
_3(RuTPU)RU\TPU\col\23515
801 2 _aRU
_b63413507
_c20210219
_gRCR
856 4 _uhttps://doi.org/10.3390/math8071182
942 _cCF