TY - GEN
T1 - Establishment of EHA Performance Degradation Model Based on PMSM and Its Active Fault Tolerant Control
AU - Xin, Zhaozhou
AU - Wang, Shaoping
AU - Zhang, Chao
N1 - Publisher Copyright:
© ESREL 2021. Published by Research Publishing, Singapore.
PY - 2021
Y1 - 2021
N2 - The electro-hydrostatic actuator (EHA) is currently the most widely used and most mature actuation method. It has the advantages of high control accuracy, good stability and high reliability. As the power source of the hydraulic pump in the EHA, the motor can drive the load to run with or without load through positive and negative rotation. This article takes the rudder control system of an underwater vehicle as an example, first analyzes the working principle of EHA, and proposed an EHA model based on permanent-magnet synchronous motor (PMSM). By analyzing the different performance degradation degrees of different parameters of the motor, and comparing it with the traditional brushless DC motor model and its performance degradation to verifiy the validity and accuracy of the model. Then combined with adaptive active fault-tolerant control (AFTC) based on Radial Basis Function Neural Network (RBFNN) to provide a basis for reliability analysis based on EHA.
AB - The electro-hydrostatic actuator (EHA) is currently the most widely used and most mature actuation method. It has the advantages of high control accuracy, good stability and high reliability. As the power source of the hydraulic pump in the EHA, the motor can drive the load to run with or without load through positive and negative rotation. This article takes the rudder control system of an underwater vehicle as an example, first analyzes the working principle of EHA, and proposed an EHA model based on permanent-magnet synchronous motor (PMSM). By analyzing the different performance degradation degrees of different parameters of the motor, and comparing it with the traditional brushless DC motor model and its performance degradation to verifiy the validity and accuracy of the model. Then combined with adaptive active fault-tolerant control (AFTC) based on Radial Basis Function Neural Network (RBFNN) to provide a basis for reliability analysis based on EHA.
KW - Active Fault-tolerant Control
KW - Electro-hydrostatic Actuator
KW - Performance Degradation
KW - Permanent-Magnet Synchronous Motor
KW - Rbf neural network
UR - https://www.scopus.com/pages/publications/85135498085
U2 - 10.3850/978-981-18-2016-8_681-cd
DO - 10.3850/978-981-18-2016-8_681-cd
M3 - 会议稿件
AN - SCOPUS:85135498085
SN - 9789811820168
T3 - Proceedings of the 31st European Safety and Reliability Conference, ESREL 2021
SP - 3117
EP - 3124
BT - Proceedings of the 31st European Safety and Reliability Conference, ESREL 2021
A2 - Castanier, Bruno
A2 - Cepin, Marko
A2 - Bigaud, David
A2 - Berenguer, Christophe
PB - Research Publishing, Singapore
T2 - 31st European Safety and Reliability Conference, ESREL 2021
Y2 - 19 September 2021 through 23 September 2021
ER -