@ARTICLE{Zhang_Mingfeng_Research_2023,
 author={Zhang, Mingfeng and Xu, Chuntian and Xu, Deying and Ma, Guoqiang and Han, Han and Zong, Xu},
 volume={71},
 number={6},
 journal={Bulletin of the Polish Academy of Sciences Technical Sciences},
 pages={e147344},
 howpublished={online},
 year={2023},
 abstract={PID controllers are crucial for industrial control because of their simple structure and good robustness. In order to further improve the accuracy of PID controllers, this paper proposes an improved sparrow search algorithm (ISSA) to prevent the problem of the algorithm being prone to falling into the local optimum at the late stage of iteration. Based on the standard sparrow search algorithm, the position update formula and the step size control parameter are optimized to help quickly jump out of the local, and to obtain the optimal solution in the whole domain. Finally, to verify the accuracy and stability of the improved algorithm, nine standard test functions are first simulated. Then, the PID parameter optimization tests are finished with the chilled water and battery charging systems, where the lifting load and applying perturbation are carried out. Both the simulation and test results show that ISSA improves the convergence speed and accuracy, and performs better in terms of stability.},
 type={Article},
 title={Research on improved sparrow search algorithm for PID controller parameter optimization},
 URL={http://journals.pan.pl/Content/129002/PDF/BPASTS_2023_71_6_3745.pdf},
 doi={10.24425/bpasts.2023.147344},
 keywords={improved sparrow search algorithm, PID controller, parameter optimization},
}