Open AccessReaction Control System Optimization for Maneuverable Reentry Vehicles Based on Particle Swarm Optimization
Author(s) -
Hang Gui,
Rong Sun,
Wei Chen,
Bin Zhu
Publication year - 2020
Publication title -
discrete dynamics in nature and society
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.264
H-Index - 39
eISSN - 1607-887X
pISSN - 1026-0226
DOI - 10.1155/2020/6518531
Subject(s) - particle swarm optimization , inertia , computer science , convergence (economics) , reentry , control theory (sociology) , parametric statistics , mathematical optimization , scheme (mathematics) , control (management) , mathematics , algorithm , medicine , mathematical analysis , statistics , physics , cardiology , classical mechanics , artificial intelligence , economics , economic growth
This paper presents a new parametric optimization design to solve a class of reaction control system (RCS) problem with discrete switching state, flexible working time, and finite-energy control for maneuverable reentry vehicles. Based on basic particle swarm optimization (PSO) method, an exponentially decreasing inertia weight function is introduced to improve convergence performance of the PSO algorithm. Considering the PSO algorithm spends long calculation time, a suboptimal control and guidance scheme is developed for online practical design. By tuning the control parameters, we try to acquire efficacy as close as possible to that of the PSO-based solution which provides a reference. Finally, comparative simulations are conducted to verify the proposed optimization approach. The results indicate that the proposed optimization and control algorithm has good performance for such RCS of maneuverable reentry vehicles.