@inproceedings{8feab4013fa141c5a8b3498f6819e23e,
title = "Multi-objective particle swarm optimization for control laws design",
abstract = "In order to overcome the difficult of large amount of calculation and to satisfy multiple design indicators in the design of control laws, an improved multi-objective particle swarm optimization (PSO) algorithm was used to design control laws of aircraft. Firstly, the hybrid concepts of genetic algorithm were introduced to particle swarm optimization (PSO) algorithm to improve the algorithm. Then based on aircraft flying quality the reference models were built, and then the tracking error, settling time and overshoot were used as the optimization goal of the control laws design. Based on this multi-objective optimize problem the attitude hold control laws were designed. The simulation results show the effectiveness of the algorithm.",
keywords = "Attitude hold control, Genetic hybrid, Multi-objective particle swarm optimization",
author = "Liu, \{Xiao Xiong\} and Heng Xu and Yan Wu and Li, \{Peng Hui\}",
year = "2013",
doi = "10.4028/www.scientific.net/AMM.333-335.1361",
language = "英语",
isbn = "9783037857502",
series = "Applied Mechanics and Materials",
pages = "1361--1365",
booktitle = "Measurement Technology and Engineering Researches in Industry",
note = "2013 2nd International Conference on Measurement, Instrumentation and Automation, ICMIA 2013 ; Conference date: 23-04-2013 Through 24-04-2013",
}