[1]张晓军,陆兴华.加入不确定扰动的无人机飞行轨迹跟踪控制[J].计算机技术与发展,2018,28(01):182-187.[doi:10.3969/ j. issn.1673-629X.2018.01.039]
 ZHANG Xiao-jun,LU Xing-hua.Flight Trajectory Tracking Control Algorithm for Unmanned AerialVehicle with Uncertain Disturbance[J].Computer Technology and Development,2018,28(01):182-187.[doi:10.3969/ j. issn.1673-629X.2018.01.039]
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加入不确定扰动的无人机飞行轨迹跟踪控制()
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《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
28
期数:
2018年01期
页码:
182-187
栏目:
应用开发研究
出版日期:
2018-01-10

文章信息/Info

Title:
Flight Trajectory Tracking Control Algorithm for Unmanned AerialVehicle with Uncertain Disturbance
文章编号:
1673-629X(2018)01-0182-06
作者:
张晓军陆兴华
广东工业大学华立学院,广东 广州 511325
Author(s):
ZHANG Xiao-junLU Xing-hua
Huali College Guangdong University of Technology,Guangzhou 511325,China
关键词:
不确定扰动气流无人机飞行轨迹跟踪控制
Keywords:
Key words:uncertain disturbanceair flowUAVflight trajectorytrackingcontrol
分类号:
TP273
DOI:
10.3969/ j. issn.1673-629X.2018.01.039
文献标志码:
A
摘要:
无人机在不确定气流扰动下容易出现飞行轨迹偏移,通过飞行轨迹跟踪控制可以提高无人机飞行中对不确定气流扰动的抗干扰性和稳健性。 传统方法采用滑膜同步协调控制方法,飞行参数的自整定性能受到扰动气流的误差漂移影响较大,控制性能不好。 提出一种基于多传感信息的自适应融合跟踪误差补偿的不确定气流扰动下无人机飞行轨迹跟踪控制算法。 对无人机飞行轨迹跟踪控制对象,在加入不确定气流下进行无人机飞行动力学模型构建,用多个连续时滞非光滑系统对无人机的定常运动进行运动平衡分解,进行多传感信息的自适应融合跟踪误差补偿,对无人机飞行轨迹的多传感器阵列
姿态参量全部量化信息进行自适应参量估计,采用反馈控制,实现飞行轨迹的自适应跟踪控制算法改进。 仿真结果表明,该控制算法进行无人机飞行轨迹跟踪控制的精度较高,品质较好,飞行轨迹的预测误差快速收敛到零,提高了飞行稳定性和抗扰动性。
Abstract:
There is flight trajectory deviation for Unmanned Aerial Vehicle (UAV) in the uncertain air flow disturbance of which the resistance and the robustness are improved by the flight trajectory tracking control. In traditional methods,the self tuning performance of the flight parameters is influenced by the error drift of the disturbed air flow,with poor control performance. Therefore,an adaptive fusion tracking error compensation method based on multi sensor information is proposed to control the flight trajectory tracking of UAV under uncertain disturbance. For the control object of UAV flight trajectory tracking,a UAV flight dynamics model is constructed in adding uncertain flow,with a continuous delay non smooth system of UAV motion exercise balance decomposition,adaptive fusion tracking error compensation of multi sensor information,adaptive parameter estimation of all quantitative information of multi-sensor array pose param-
eters for UAV flight trajectory. Using feedback control,the adaptive trajectory tracking control algorithm is improved. The simulation shows that the control algorithm owns higher precision and better quality in UAV flight trajectory tracking control,and the prediction error of flight trajectory converges to zero,improving the stability and anti disturbance of flight.
更新日期/Last Update: 2018-03-14