TY - GEN
T1 - Control Parameter Design for Hypersonic Vehicle via Improved Comprehensive Learning Pigeon-Inspired Optimization
AU - Xiang, Hongcheng
AU - Deng, Yimin
N1 - Publisher Copyright:
© 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
PY - 2023
Y1 - 2023
N2 - In this paper, an Active Disturbance Rejection Control (ADRC) system is proposed to address the complex disturbance during the flight of Hypersonic Vehicle (HV). To deal with difficulties in the manual control parameter design task, an Improved Comprehensive Learning Pigeon-Inspired Optimization (ICLPIO) algorithm is utilized by converting the parameter design problem to an optimization problem. The comprehensive learning strategy and the selective learning mechanism are introduced to improve the convergence rate and exploration performance in the parameters tuning for ADRC system of HV. To verify the advantages of the ICLPIO algorithm, the particle swarm optimization (PSO), the basic PIO, and the genetic algorithm (GA) are applied in the simulations as control groups. The results show that the presented method is superior to other optimization methods.
AB - In this paper, an Active Disturbance Rejection Control (ADRC) system is proposed to address the complex disturbance during the flight of Hypersonic Vehicle (HV). To deal with difficulties in the manual control parameter design task, an Improved Comprehensive Learning Pigeon-Inspired Optimization (ICLPIO) algorithm is utilized by converting the parameter design problem to an optimization problem. The comprehensive learning strategy and the selective learning mechanism are introduced to improve the convergence rate and exploration performance in the parameters tuning for ADRC system of HV. To verify the advantages of the ICLPIO algorithm, the particle swarm optimization (PSO), the basic PIO, and the genetic algorithm (GA) are applied in the simulations as control groups. The results show that the presented method is superior to other optimization methods.
KW - Active Disturbance Rejection Control (ADRC)
KW - Comprehensive learning strategy
KW - Hypersonic Vehicle (HV)
KW - Pigeon-Inspired Optimization (PIO)
UR - https://www.scopus.com/pages/publications/85151141658
U2 - 10.1007/978-981-19-6613-2_392
DO - 10.1007/978-981-19-6613-2_392
M3 - 会议稿件
AN - SCOPUS:85151141658
SN - 9789811966125
T3 - Lecture Notes in Electrical Engineering
SP - 4020
EP - 4028
BT - Advances in Guidance, Navigation and Control - Proceedings of 2022 International Conference on Guidance, Navigation and Control
A2 - Yan, Liang
A2 - Duan, Haibin
A2 - Deng, Yimin
A2 - Yan, Liang
PB - Springer Science and Business Media Deutschland GmbH
T2 - International Conference on Guidance, Navigation and Control, ICGNC 2022
Y2 - 5 August 2022 through 7 August 2022
ER -