期刊文献+

基于粒子群算法的飞行控制律参数设计研究 被引量:3

Research on Parameter Design of Flight Control Law Based on Particle Swarm Optimization Algorithm
下载PDF
导出
摘要 无人机控制策略采用俯仰高度控制、油门空速控制和侧偏距控制。在设计的适应度函数中引入高度误差、相角裕度和幅值裕度,利用粒子群算法迭代寻找适应度函数最优值确定控制器参数。对无人机纵向高度运动和横侧向位置运动进行仿真,通过各控制器的阶跃响应和开环频率特性曲线,验证了粒子群算法得到的控制器参数满足设计要求。在仿真中引入离散突风,进一步验证通过粒子群算法得到的控制器参数的可靠性,说明粒子群算法简捷、快速、可靠的优点。 Research on the parameter optimization design of longitudinal and lateral channel controller is de-veloped in this paper based on PSOCParticle Swarm Optimization)algorithm. Control strategies include the control of UAV ( unmanned aircraft vehicle) height, velocity and lateral offset. Height error, phase margin and magnitude margin are added to the fitness function to find the best value of fitness function based on PSO. Besides, simulations are completed for the longitudinal and lateral control of UAV to prove the effec-tiveness of controller parameters obtained via PSO by evaluating the step response and bode plots. Simula-tions under wind gust are completed as well to prove the reliability of controller parameters obtained by PSO and also the advantages of PSO such as simplicity, fastness,and reliability.
作者 魏星
出处 《西安航空学院学报》 2017年第1期3-7,共5页 Journal of Xi’an Aeronautical Institute
关键词 粒子群优化算法 无人机高度控制 复杂气流扰动 PID控制结构 particle swarm optimization algorithm UAV height control complex airflow disturbance PID control structure
  • 相关文献

参考文献3

二级参考文献38

  • 1唐强,王建元,朱志强.基于粒子群优化的三维突防航迹规划仿真研究[J].系统仿真学报,2004,16(9):2033-2036. 被引量:53
  • 2杜萍,杨春.飞行器航迹规划算法综述[J].飞行力学,2005,23(2):10-14. 被引量:62
  • 3白晓利,韩亮.基于数字地图预处理的低空突防飞行路线规划[J].北京航空航天大学学报,2005,31(8):853-857. 被引量:13
  • 4David Frelinger, Joel Kvitky, William Stanley. Proliferated autonomous weapons[R]. Santa Monica: Rand Corporation.
  • 5Corey Schumacher, Phillip R Chandler, Steven Rasmussen. Task allocation for wide area search munitinos[D]. Anchorage: Wright-Patterson Air Force Base, 2002.
  • 6Robert Dunkel III. Investigation of cooperative behavior in autonomous wide area search munitions[D]. Ohio: Air Force Institute of Technology, 2002.
  • 7Orhan Gozaydin. Analysis of cooperative behavior for autonomous wide area search munitions[R]. Ohio: Air Force Institute of Technology, 2002.
  • 8Kendall Nygard, Phillip Chandler, Meir Pachter. Dynamic network flow optimization models for air vehicle resource allocation[C]. American Control Conf. Arlington, 2001: 25 -27.
  • 9Schumacher C J, Chandler P R, Rasmussen S J. Task allocation for wide area search munitions via iterative network flow optimization [C]. Proc of the AIAA Guidance, Navigation, and Control Conf. Monterey, 2002: 3472-3477.
  • 10Ryan J L, Bailey T G, Moore J T, et al. Unmanned aerial vehicles (UAV) route selection using reactive Tabu search [J]. Military Operations Research, 1999, (4): 5-24.

共引文献284

同被引文献13

引证文献3

二级引证文献28

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部