Parameters identification of UCAV flight control system based on predator-prey particle swarm optimization

被引:18
作者
Duan HaiBin [1 ]
Yu YaXiang [1 ]
Zhao ZhenYu [2 ]
机构
[1] Beihang Univ, Sch Automat Sci & Elect Engn, Sci & Technol Aircraft Control Lab, Beijing 100191, Peoples R China
[2] Sci & Technol Electron Opt Control Lab, Luoyang 410079, Peoples R China
关键词
uninhabited combat aerial vehicle (UCAV); particle swarm optimization (PSO); parameters identification; predator-prey;
D O I
10.1007/s11432-012-4754-9
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
With the improvement of the aircraft flight performance and development of computing science, uninhabited combat aerial vehicle (UCAV) could accomplish more complex tasks. But this also put forward stricter requirements for the flight control system, which are the crucial issues of the whole UCAV system design. This paper proposes a novel UCAV flight controller parameters identification method, which is based on predator-prey particle swarm optimization (PSO) algorithm. A series of comparative experimental results verify the feasibility and effectiveness of our proposed approach in this paper, and a predator-prey PSO-based software platform for UCAV controller design is also developed.
引用
收藏
页码:1 / 12
页数:12
相关论文
共 21 条
  • [1] Comparison of different cooperation strategies in the prey-predator problem
    Di Gesu, V.
    Lenzitti, B.
    Lo Bosco, G.
    Tegolo, D.
    [J]. 2006 INTERNATIONAL WORKSHOP ON COMPUTER ARCHITECTURE FOR MACHINE PERCEPTION AND SENSING, 2006, : 108 - 112
  • [2] Duan H.B., 2005, Ant Colony Algorithms: Theory and Applications
  • [3] Optimal Formation Reconfiguration Control of Multiple UCAVs Using Improved Particle Swarm Optimization
    Duan, Hai-bin
    Ma, Guan-jun
    Luo, De-lin
    [J]. JOURNAL OF BIONIC ENGINEERING, 2008, 5 (04) : 340 - 347
  • [4] Progress in control approaches for hypersonic vehicle
    Duan HaiBin
    Li Pei
    [J]. SCIENCE CHINA-TECHNOLOGICAL SCIENCES, 2012, 55 (10) : 2965 - 2970
  • [5] New development thoughts on the bio-inspired intelligence based control for unmanned combat aerial vehicle
    Duan HaiBin
    Shao Shan
    Su BingWei
    Zhang Lei
    [J]. SCIENCE CHINA-TECHNOLOGICAL SCIENCES, 2010, 53 (08) : 2025 - 2031
  • [6] Design and realization of hybrid ACO-based PID and LuGre friction compensation controller for three degree-of-freedom high precision flight simulator
    Duan, Haibin
    Liu, Senqi
    Wang, Daobo
    Yu, Xiufen
    [J]. SIMULATION MODELLING PRACTICE AND THEORY, 2009, 17 (06) : 1160 - 1169
  • [7] Guangping Qi, 2009, 2009 International Conference on Information and Automation (ICIA), P1331, DOI 10.1109/ICINFA.2009.5205123
  • [8] Multiobjective control of power plants using particle swarm optimization techniques
    Heo, Jin S.
    Lee, Kwang Y.
    Garduno-Ramirez, Raul
    [J]. IEEE TRANSACTIONS ON ENERGY CONVERSION, 2006, 21 (02) : 552 - 561
  • [9] Particle Swarm Optimization considering the concept of predator-prey behavior
    Higashitani, Mitsuharu
    Ishigame, Atsushi
    Yasuda, Keiichiro
    [J]. 2006 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION, VOLS 1-6, 2006, : 434 - +
  • [10] Jin GD., 2009 INT WORKSH INT, P1