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Adaptive Fractional Order PI Controller Design for a Flexible Swing arm System Via Enhanced Virtual Reference Feedback Tuning
Author(s) -
Xie Yuanlong,
Tang Xiaoqi,
Zheng Shiqi,
Qiao Wenjun,
Song Bao
Publication year - 2018
Publication title -
asian journal of control
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.769
H-Index - 53
eISSN - 1934-6093
pISSN - 1561-8625
DOI - 10.1002/asjc.1633
Subject(s) - control theory (sociology) , computer science , controller (irrigation) , trajectory , swing , computation , process (computing) , stability (learning theory) , control engineering , control (management) , engineering , algorithm , mechanical engineering , physics , astronomy , artificial intelligence , machine learning , agronomy , biology , operating system
Abstract Flexible swing arm system (FSAS) is one of the most important components in the LED packaging industry. The trajectory tracking performance of the FSAS will directly affect the efficiency and accuracy of the LED packaging equipment. In order to meet the high precision and high speed requirements, this paper proposes an adaptive fractional order proportional integral (AFOPI) control method based on enhanced virtual reference feedback tuning (EVRFT). In this method, the AFOPI controller is applied to handle the fractional order characteristics of the FSAS. EVRFT is used to tune the AFOPI controller in a real‐time way to accommodate the time‐varying operating conditions. The proposed method is facilitated with two advantages: 1) only input/output measured data are fully utilized during the recursive tuning process without using model information of the controlled FSAS; 2) an improved adaptive law is incorporated in EVRFT to reduce the computation burden and provide an unbiased estimate for the ideal controller simultaneously. Thus, the conventional VRFT is enhanced both in efficiency and accuracy. The stability of the proposed method is guaranteed by rigorous theoretical analysis. Finally, experimental results are presented to verify the effectiveness of the EVRFT‐based AFOPI controller.