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基于鲁棒优化算法的小型无人机模糊控制器研究
引用本文:孙大伟,许国栋.基于鲁棒优化算法的小型无人机模糊控制器研究[J].电光与控制,2012,19(6):62-65.
作者姓名:孙大伟  许国栋
作者单位:中国空空导弹研究院,河南洛阳,471009
摘    要:简要论述了小型无人机的经典H2/H∞鲁棒优化算法,并在此优化控制算法基础上,对模糊控制器开展了研究,模糊控制器的知识库主要依据原型无人机的实验数据搭建。为了验证模糊控制器的控制品质和鲁棒性,在小型无人机的静态参数(高度、角度)控制回路上将模糊控制器与原型控制器进行了结合,使之成为鲁棒模糊控制器。对小型无人机鲁棒模糊控制系统参数的控制品质和鲁棒性进行了计算,并将这些特性和原型机进行了比较。仿真结果表明,采用模糊控制器的控制系统鲁棒性提高了近一个数量级。

关 键 词:小型无人机  鲁棒性  最优化  模糊控制
收稿时间:2011/9/21

Fuzzy Autopilots for SUAV Based on Robust Optimization Algorithm
SUN Dawei , XU Guodong.Fuzzy Autopilots for SUAV Based on Robust Optimization Algorithm[J].Electronics Optics & Control,2012,19(6):62-65.
Authors:SUN Dawei  XU Guodong
Affiliation:(China Airborne Missile Academy,Luoyang 471009,China)
Abstract:The robust optimization algorithm of classic H2/H∞ for Small Unmanned Aerial Vehicle (SUAV) was discussedbased on which the fuzzy autopilot was studied.The knowledge base of the fuzzy autopilot was established by using the experimental data of a prototype UAV.In order to verify the robust properties and performance of the fuzzy autopilotthe fuzzy autopilot and the prototype controller were combined into the robust fuzzy autopilot in static parameters (heightangle) control loop of the SUAV.The performance and robustness of the robust fuzzy control system parameters for SUAVs were calculated out which were compared with these of a prototype controller.The simulation results show that the control system robustness of the fuzzy autopilot was increased by nearly one order of magnitude.
Keywords:Small Unmanned Aerial Vehicle (SUAV)  robustness  optimization  fuzzy control
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