改进PID的无人机飞行姿态角控制消颤算法  

Flight attitude angle control and anti-chatter algorithm for UAV based on improved PID

作　　者：陆兴华[1] 詹世尉 余文权[1] 黄臣炜 LU Xing-hua ZHAN Shi-wei YU Wen-quan HUANG Chen-wei(Huali College,Guangdong University of Technology,Guangzhou 511325, China)

机构地区：[1]广东工业大学华立学院,广东广州511325

出　　处：《传感器与微系统》2017年第3期116-119,共4页Transducer and Microsystem Technologies

基　　金：2015年广东省教育厅重点平台及科研项目青年创新人才类项目(自然科学类)(2015KQNCX218);2016年广东省大学生科技创新培育项目(pdjh2016b0940)

摘　　要：无人机在整个纵平面飞行过程中,由于飞行姿态角的大幅度变化以及气流的作用,导致机身颤抖,影响飞行稳定性。提出一种基于PID变结构控制的无人机飞行姿态角控制消颤算法,首先进行了无人机飞行姿态角控制系统的被控对象参量分析,构建无人机在姿态角变化剧烈、大迎角飞行时的三通道模型,采用变结构控制方法进行控制器设计。结合小扰动原理和Lyapunov稳定性原理进行扰动抑制和稳定性证明,采用梯度算法调整权值进行飞行姿态角控制的消颤处理,采用自适应算法在线调整权值实现PID变结构控制改进。仿真结果表明:采用该算法进行无人机飞行姿态角控制和消颤处理,大幅度提高无人机飞行定姿的精度,横滚角、俯仰角和航向角的控制精度有较大提高,稳定性和收敛性较好,确保了无人机飞行稳定性。Aiming at problem that UAV in the whole longitudinal plane flight process,due to the large range of flight attitude angle and the effect of air flow,resulting in trembling,affecting flight stability,present a control and anti-chatter algorithm for UAV flight attitude angle based on PID variable structure control. Parametric analysis on controlled object of flight attitude angle control system is carried out. Three-channel model for UAV in dramatic change of attitude angle,large angle of attack flight,controller is designed with variable structure control method.The disturbance rejection and stability are proved by small perturbation theory and Lyapunov stability theory.Gradient algorithm is used to adjust weights for anti-chatter processing by flight attitude angle control. The adaptive algorithm is used to online adjust the weights to realize improvement of PID variable structure control. The simulation results show that using this algorithm to control attitude angle of UAV and realize anti-chatter,precision of UAV flight attitude is greatly improved,the control precision of roll angle,pitch angle and heading angle is greatly improved,stability and convergence are good,which ensure flight stability of UAV.

关 键 词：无人机 神经网络 变结构控制 姿态角 

分 类 号：TP273[自动化与计算机技术—检测技术与自动化装置]