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四旋翼飞行器多模式稳定控制

Multi Mode Stability Control of Quadrotor
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摘要 针对四旋翼飞行器的飞行稳定问题,提出了一种多模式的控制策略.在系统建模时引入未知扰动.系统采用内外环控制的方式,外环为位置控制环,采用自适应RBF神经网络对扰动进行预测,并采用非奇异终端滑模控制器实现对未知扰动的补偿和位置跟踪,有效提高了系统的鲁棒性;内环为姿态控制环,采用具备3种姿态角解算模式的超螺旋非奇异终端滑模控制器,使姿态角保持在安全区间内,使飞行器更加稳定和安全.通过李雅普诺夫方程法证明系统的稳定性,并证明了系统误差可有限时间收敛.最后,通过仿真实验验证了所提出控制策略的有效性. Aiming at the flight safety problem of quadrotor,a multi-mode control strategy is proposed.The unknown disturbance is introduced into the system modeling.The system adopts internal and external loop control.The outer loop is a position control loop.The adaptive RBF neural network is used to predict the disturbance,and the nonsingular terminal sliding mode controller is used to realize the compensation for the unknown disturbance and position tracking,which effectively improves the robustness of the system;The inner loop is an attitude control loop,which uses a super spiral nonsingular terminal sliding mode controller with three attitude angle solving modes to keep the attitude angle within a safe range,making the aircraft more stable and safe.The stability of the system is proved by Lyapunov equation method,and the finite time convergence of the system error is proved.Finally,the effectiveness of the proposed control strategy is verified by simulation experiments.
作者 贾晓涵 付丽霞 JIA Xiaohan;FU Lixia(Faculty of Information Engineering and Automation,Kunming University of Science and Technology,Kunming 650500,China)
出处 《小型微型计算机系统》 CSCD 北大核心 2024年第3期570-575,共6页 Journal of Chinese Computer Systems
基金 云南省重大科技专项计划项目(202002AC080001)资助.
关键词 四旋翼 滑模控制 RBF神经网络 超螺旋算法 轨迹跟踪 quadrotor sliding mode control RBF neural network super-twisting algorithm path tracking
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