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。
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.
出处
《电光与控制》
北大核心
2012年第6期62-65,共4页
Electronics Optics & Control
关键词
小型无人机
鲁棒性
最优化
模糊控制
Small Unmanned Aerial Vehicle （SUAV）
robustness
optimization
fuzzy control
