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Journal of ZheJiang University (Engineering Science)  2021, Vol. 55 Issue (12): 2359-2364    DOI: 10.3785/j.issn.1008-973X.2021.12.016
    
Cascade TD-PID control algorithm for coaxial anti-propeller unmanned aerial vehicle based on tracking differentiator
Si-xiao WANG1(),Wen-jun ZHAO2,Hao ZHANG1,3,*(),Yong GAO1,Pu-sen LI1
1. Faculty of Information Science and Engineering, Ocean University of China, Qingdao 266100, China
2. Beijing Satellite Navigation Center, Beijing 100094, China
3. Pilot National Laboratory for Marine Science and Technology, Qingdao 266100, China
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Abstract  

A cascade TD-PID control algorithm based on the tracking differentiator was proposed to improve unmanned aerial vehicle (UAV) flight stability, in view of the problem that the traditional PID control algorithm was not ideal for the under-driven and highly coupled nonlinear system control effect of coaxial anti-propeller UAV. The coaxial anti-propeller UAV flight system was designed, and the cascade TD-PID control algorithm based on the tracking differentiator was proposed for the attitude control of the UAV. The outer loop was the traditional PID algorithm, and the inner loop used two tracking differentiators to improve the dynamic performance of the system through cascade control. The simulation model of the control system was set up in Matlab /Simulink for simulation testing. Simulation results show that compared with the traditional cascade PID control algorithm, the overtone of the proposed control algorithm is smaller , and the system stability is greatly improved. The control effect of cascade TD-PID control algorithm and cascade PID control algorithm was compared through flight test. Test results show that the proposed control algorithm can effectively reduce the system overtone, and improve system stability and anti-jamming ability.



Key wordscoaxial anti-propeller      unmanned aerial vehicle (UAV)      attitude control      tracking differentiator(TD)      cascade TD-PID control algorithm      overtone     
Received: 25 January 2021      Published: 31 December 2021
CLC:  TP 273  
Fund:  国家自然科学基金资助项目(91938204,41527901,61701462);山东省支持青岛海洋科学与技术试点国家实验室重大科技专项(2018SDKJ0210);中央军委装备发展部装备预研领域基金重点项目(61404160502)
Corresponding Authors: Hao ZHANG     E-mail: wangsixiao1516@163.com;zhanghao@ouc.edu.cn
Cite this article:

Si-xiao WANG,Wen-jun ZHAO,Hao ZHANG,Yong GAO,Pu-sen LI. Cascade TD-PID control algorithm for coaxial anti-propeller unmanned aerial vehicle based on tracking differentiator. Journal of ZheJiang University (Engineering Science), 2021, 55(12): 2359-2364.

URL:

https://www.zjujournals.com/eng/10.3785/j.issn.1008-973X.2021.12.016     OR     https://www.zjujournals.com/eng/Y2021/V55/I12/2359


基于微分跟踪器的共轴反桨无人机串级TD-PID控制算法

针对传统PID控制算法对共轴反桨无人机的欠驱动、强耦合非线性系统控制效果不理想的问题,提出基于微分跟踪器的串级TD-PID控制算法,以提高无人机飞行稳定性. 设计共轴反桨无人机飞行系统,针对无人机的姿态控制提出基于微分跟踪器的串级TD-PID控制算法:外环为传统PID算法,内环使用2个微分跟踪器,通过串级控制改善系统动态性能. 在Matlab/Simulink中搭建控制系统的仿真模型进行仿真试验. 仿真结果表明:相较于传统串级PID控制算法,所提控制算法超调量更小,系统稳定性有较大提高. 对比串级TD-PID控制算法与串级PID控制算法控制效果的飞行试验结果表明:所提控制算法能有效减少系统超调量,提升系统稳定性和抗干扰能力.


关键词: 共轴反桨,  无人机(UAV),  姿态控制,  微分跟踪器(TD),  串级TD-PID控制算法,  超调量 
指标 指标值 指标 指标值
mmax/kg ≤15 Hmax/m 10
meff/kg 2 vmax/(m·s?1) 20
L/mm ≤1 200 θmax/(°) 俯仰/横滚:?15~15
偏航:?90~90
R/mm ≤160 θerr/(°) ±1
Tab.1 Coaxial anti-propeller UAV design index
Fig.1 Coaxial anti-propeller UAV flight structure
Fig.2 Control block diagram of UAV system
Fig.3 Schematic diagram of cascade TD-PID controller
Fig.4 Simulation model of two control algorithms in Matlab/Simulink environment
Fig.5 Comparison of simulation results of two control algorithms in Matlab/Simulink environment
通道 控制算法 Tr QO/%
俯仰/滚转通道 串级PID 0.248 16.20
TD-PID 0.218 2.30
偏航通道 串级PID 0.321 10.20
TD-PID 0.265 6.86
Tab.2 Comparison of step response simulation results
控制器 ${k_{{\rm{p}}\theta }} $ ${k_{{\rm{i}}\theta }} $ ${k_{{\rm{d}}\theta }} $ ${r_{01}}$ ${h_{01}}$ ${h_{1}}$ ${r_{02}}$ ${h_{02}}$ ${h_{2}}$
俯仰/滚转通道 4.5 0.012 0.010 550 0.032 0.002 200 0.020 0.002
偏航通道 3.0 0.009 0.015 550 0.015 0.001 200 0.013 0.001
Tab.3 Coaxial anti-propeller UAV cascade TD-PID controller parameter table
Fig.6 Flight diagram of UAV
Fig.7 Waveform comparison of flight data under two control algorithms
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