具有不确定性的扑翼微型飞行器抗干扰控制
Anti-disturbance Control of Flapping-Wing Micro Aerial Vehicle with Uncertainty
武晓晶 1杨乾 1孟凡华 1甄然1
作者信息
- 1. 河北科技大学电气工程学院,河北 石家庄 050018
- 折叠
摘要
研究了具有内部不确定性和外部干扰的扑翼微型飞行器的姿态和位置跟踪控制问题.利用神经网络对扑翼微型飞行器数学模型中复杂非线性和不确定性进行逼近估计,同时对于外部扰动,采用自适应技术来处理干扰对系统的影响.基于反步递推框架,引入一阶滤波器,设计了动态表面控制器,克服了传统反步递推设计中"微分爆炸"的局限性.进一步,利用Lyapunov稳定理论证明了扑翼飞行器姿态和位置闭环系统的稳定性和所有状态变量的半全局一致最终有界性.结果表明,所提控制器不仅能够使稳态误差更好地收敛,而且还提高了收敛速度.仿真结果验证了所提控制方法能够有效地处理不确定性和外部干扰,且能够很好地跟踪期望轨迹.
Abstract
In this paper,the attitude and position tracking control of Flapping-Wing Micro Aerial Vehicle(FW-MAV)with internal uncertainties and external disturbance was studied.A neural network is designed to approximate and to estimate the complex nonlinearity and uncertainties in the mathematical model of FWMAV.Meanwhile,this pa-per used adaptive technology to counteract the adverse effects of external disturbance.Based on the backstepping re-cursive framework,it can design a dynamic surface controller by introducing a first-order filter,which overcomes the limitation of"differential explosion"in traditional backstepping recursive design.Then,a Lyapunov function was pro-posed to prove the closed-loop system stability and the semi-global uniform ultimate boundedness of all state varia-bles.The results show that the proposed controller can not only make the steady-state error converge better,but also improve the convergence speed.Simulation results indicate that the control method can effectively deal with the uncer-tainties and external disturbances and can track the desired trajectories well.
关键词
自动控制/扑翼微型飞行器/神经网络/自适应控制/反步控制Key words
Automatic control/Flapping-wing micro aerial vehicle(FWMAV)/Neural network/Adaptive control/Backstepping control引用本文复制引用
基金项目
国家自然科学基金(62003129)
河北科技大学研究生创新资助项目(XJCXZZSS2022014)
出版年
2024
NETL
NSTL
万方数据