Open AccessPID Parameter Tuning for Buck Controllers Based on an Improved Differential Evolution Algorithm
Author(s) -
Yang Zhao,
QX Qiu,
Xia Zhao
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/2029/1/012059
Subject(s) - overshoot (microwave communication) , pid controller , control theory (sociology) , differential evolution , crossover , convergence (economics) , buck converter , computer science , algorithm , stability (learning theory) , population , converters , mathematics , engineering , control engineering , voltage , temperature control , telecommunications , demography , control (management) , artificial intelligence , machine learning , sociology , economics , economic growth , electrical engineering
With the wide application of Buck converters, it is of great significance to select the optimal PID controller parameters to ensure the dynamic and steady-state performance of the Buck converters. On this basis, a PID parameter tuning method based on an improved differential evolution algorithm is proposed. Also, a crossover approach with population generation across orders of magnitude, elastic boundary absorption, and retention of some combined features is put forward. In addition, an adaptive mutation factor, and a cost function that suppresses overshoot and is sensitive to the tuning time are designed. The results of 10 tests show that the differential evolution algorithm fails in the case of parameters in a range cross orders of magnitude, while the algorithm proposed in this paper enables a better combination of PID parameters selected in terms of speed and stability, with a wide search space and stable convergence results.