TY - GEN
T1 - Robust-Tube Model Predictive Control for Piezoelectrically Actuated Fast Mechanical Switches for Hybrid Circuit Breakers
AU - Chai, Yu
AU - Yang, Chen
AU - Dong, Huijuan
AU - Zhao, Jie
AU - Shardt, Yuri A.W.
AU - Ju, Bingfeng
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2024
Y1 - 2024
N2 - Safeguarding high voltage direct current (HVDC) systems against direct current faults is an inherently demanding task. A promising solution to tackle this challenge is the application of piezoelectrically actuated fast mechanical switches (PA-FMS). However, mechanical resonance and random vibrations in the travel curves of P A-FMS have a substantial impact on their control accuracy. To tackle this challenge, a robust-tube model predictive control (RTMPC) strategy is developed. RTMPC drives the disturbed system state into the minimal robustly positively invariant (mRPI) set centered on the target and ensures that constraints are satisfied. The error feedback gain is calculated using the proposed linear matrix inequality (LMI) based method to minimize the effect of disturbances on the trajectory. An efficient outer approximation method is used to compute the mRPI set. Simulation results show that the critically damped travel curves have been achieved, along with a reduction of the external disturbances by 98%.
AB - Safeguarding high voltage direct current (HVDC) systems against direct current faults is an inherently demanding task. A promising solution to tackle this challenge is the application of piezoelectrically actuated fast mechanical switches (PA-FMS). However, mechanical resonance and random vibrations in the travel curves of P A-FMS have a substantial impact on their control accuracy. To tackle this challenge, a robust-tube model predictive control (RTMPC) strategy is developed. RTMPC drives the disturbed system state into the minimal robustly positively invariant (mRPI) set centered on the target and ensures that constraints are satisfied. The error feedback gain is calculated using the proposed linear matrix inequality (LMI) based method to minimize the effect of disturbances on the trajectory. An efficient outer approximation method is used to compute the mRPI set. Simulation results show that the critically damped travel curves have been achieved, along with a reduction of the external disturbances by 98%.
KW - Robust-tube model predictive control
KW - additive uncertainty
KW - fast mechanical switch
KW - high voltage direct current
KW - underdamped
UR - https://www.scopus.com/pages/publications/105000375828
U2 - 10.1109/AIAC63745.2024.10899529
DO - 10.1109/AIAC63745.2024.10899529
M3 - 会议稿件
AN - SCOPUS:105000375828
T3 - 2024 2nd International Conference on Artificial Intelligence and Automation Control, AIAC 2024
SP - 230
EP - 236
BT - 2024 2nd International Conference on Artificial Intelligence and Automation Control, AIAC 2024
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2nd International Conference on Artificial Intelligence and Automation Control, AIAC 2024
Y2 - 20 December 2024 through 22 December 2024
ER -