TY - GEN
T1 - On the application of self -adaptation and mutation domain fuzzy algorithm in the optimization of the dynamic characteristics of micro -aircraft
AU - Wu, Jinhao
AU - Li, Xinyi
AU - Fan, Yukun
AU - Liu, Weiguo
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - Adjust the gesture of small aircraft, adjust the use of permanent magnet synchronous motor (PMSM) servo control system aircraft size, different system rotation of the rudder ring installation position, etc., and the transition of the aircraft in the air encountered in the air. At the time, the traditional PI control method and fuzzy control method cannot solve the problem of slower system response and the problem of turning the system caused by it. This article proposes a fuzzy control algorithm based on model reference self -adaptation. First of all, the system's rotation inertia parameters are recognized online through the MRAS algorithm, and then the identified results are fed back to the vague algorithm of the transformation domain to obtain a real -time PI parameter change volume to achieve precise control of the servo control system. Through the simulation verification, the results indicate that the model refer to the self -adaptation domain blur control algorithm has high accuracy of the online recognition of system rotation inertia. Compared with the traditional blur control method, the dynamic characteristics of the system have been improved.
AB - Adjust the gesture of small aircraft, adjust the use of permanent magnet synchronous motor (PMSM) servo control system aircraft size, different system rotation of the rudder ring installation position, etc., and the transition of the aircraft in the air encountered in the air. At the time, the traditional PI control method and fuzzy control method cannot solve the problem of slower system response and the problem of turning the system caused by it. This article proposes a fuzzy control algorithm based on model reference self -adaptation. First of all, the system's rotation inertia parameters are recognized online through the MRAS algorithm, and then the identified results are fed back to the vague algorithm of the transformation domain to obtain a real -time PI parameter change volume to achieve precise control of the servo control system. Through the simulation verification, the results indicate that the model refer to the self -adaptation domain blur control algorithm has high accuracy of the online recognition of system rotation inertia. Compared with the traditional blur control method, the dynamic characteristics of the system have been improved.
KW - Fire attitude adjustment
KW - model reference adaptive
KW - parameter recognition
KW - permanent magnet synchronous motor
KW - servo control system
KW - vague control of variant domains
UR - http://www.scopus.com/inward/record.url?scp=85186507463&partnerID=8YFLogxK
U2 - 10.1109/ICCEIC60201.2023.10426739
DO - 10.1109/ICCEIC60201.2023.10426739
M3 - 会议稿件
AN - SCOPUS:85186507463
T3 - 2023 4th International Conference on Computer Engineering and Intelligent Control, ICCEIC 2023
SP - 317
EP - 323
BT - 2023 4th International Conference on Computer Engineering and Intelligent Control, ICCEIC 2023
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2023 4th International Conference on Computer Engineering and Intelligent Control, ICCEIC 2023
Y2 - 20 October 2023 through 22 October 2023
ER -