An improved adaptive firefly algorithm for PI parameter optimization of permanent magnet synchronous motor
- Resource Type
- Conference
- Authors
- Wang, Shuwen; Wang, Siwen; Wang, Runtao
- Source
- 2019 IEEE International Conference on Computation, Communication and Engineering (ICCCE) Computation, Communication and Engineering (ICCCE), 2019 IEEE International Conference on. :1-4 Nov, 2019
- Subject
- Communication, Networking and Broadcast Technologies
Computing and Processing
Engineering Profession
Power, Energy and Industry Applications
Robotics and Control Systems
Signal Processing and Analysis
Optimization
Brightness
Wind speed
Wind power generation
Fans
Permanent magnets
Sociology
PMSM
Multidimensional population mechanism
Improved adaptive firefly algorithm
PI controller
- Language
A parameter optimization algorithm for the PI controller of permanent magnet synchronous motor (PMSM) based on improved adaptive firefly algorithm (IAFA) is proposed. The PI parameters of current and speed are set by improved adaptive firefly algorithm. This paper introduces 7 dimensions firefly population and adaptive step adjustment mechanism in the algorithm, which is fast and convenient to obtain the optimal solution accurately. The traditional parameter optimization method usually uses an operator to get the target parameter after repeated debugging in the actual system, which is inefficient and relies heavily on production experience. In order to optimize this problem, multidimensional population and adaptive step adjustment strategy are proposed to speed up the iteration and get the global optimal. The results demonstrate that PMSM-IAFA has fast convergence rate and high computational accuracy. It significantly outperforms the other state-of-the-art FA variants in majority of the tested instances.