横列式双旋翼矢量飞行器的改进ADRC姿态控制算法

doi:10.12305/j.issn.1001-506X.2021.10.33

摘要/Abstract

摘要：

横列式双旋翼矢量飞行器具备飞行时间长、风阻小、机动性强等优点, 但其机械结构复杂, 状态之间耦合严重, 抗干扰能力弱。针对其控制特性提出一种基于改进自抗扰控制(active disturbance rejection control, ADRC)的姿态抗干扰解耦控制算法, 该算法利用扩张状态观测器(extended state observer, ESO)实现姿态干扰和状态间耦合项的跟踪和估计, 将非线性多输入多输出(multiple input multiple output, MIMO)系统转化成线性单输入单输出(single input single output, SISO)系统, 采用改进的粒子群优化算法(particle swarm optimization, PSO)对姿态控制系统进行参数优化。通过仿真结果验证了该算法具备良好的抗干扰能力，并设计了实际的飞行控制系统, 进行了飞行器的悬停试验, 实现了稳定悬停。

关键词: 双旋翼, 可倾转, 自抗扰控制, 动态反馈线性化, 干扰估计

Abstract:

The tilting dual-fan vector Unmanned aerial vehicle has the advantages of long flight time, small wind resistance and strong maneuverability, but its mechanical structure is complex, the coupling between the states is serious, and the anti-interference ability is weak. According to its control characteristics, an anti-interference decoupling control algorithm based on improved active disturbance rejection control (ADRC) is proposed, extended state observer (ESO) is used to track and estimate the attitude disturbance and the coupling term between states.The nonlinear multiple input multiple output (MIMO) system was transformed into linear single input single output (SISO) system. An improved particle swarm optimization (PSO) algorithm is used to optimize the parameters of the attitude control system, the simulation results showed that the algorithm has good ability of resisting external disturbance and coupling disturbance, the actual flight control system is designed and the hovering test of the aircraft is carried out, the stable hovering of the aircraft is realized.

Key words: dual-fan, tilting, active disturbance rejection controller (ADRC), dynamic feedback linearization, interference estimation

中图分类号:

V249

杨立本, 魏文军, 杨剑锋, 李泰国, 王栋. 横列式双旋翼矢量飞行器的改进ADRC姿态控制算法[J]. 系统工程与电子技术, 2021, 43(10): 2976-2983.

Liben YANG, Wenjun WEI, Jianfeng YANG, Taiguo LI, Dong WANG. Improved ADRC attitude control algorithm for tilting dual-fan vector aircraft[J]. Systems Engineering and Electronics, 2021, 43(10): 2976-2983.

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算法	粒子个数
算法	20	30	40	50
传统PSO	64.929 4	128.994 2	193.406 1	258.073 9
本文算法	65.047 1	129.900 9	193.853 0	258.696 2

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