摘要
为了提高八旋翼植保无人机的可控制性,对无人机喷洒过程中药箱进行了分析和建模,推导出长方体药箱质量和转动惯量随时间变化的公式,进一步得到了植保无人机精确的时变性动力学模型.为了验证模型的正确性和先进控制律的控制效果,设计自适应反步终端滑模姿态控制器,第一步采用典型反演控制;第二步应用终端滑模控制,使最后状态在有限时间内收敛到理想值;第三步设计了自适应控制律以消除未知干扰的影响,设计的控制器均满足Lyapunov稳定性理论.对控制器进行了仿真和试验验证,控制效果与模糊PID姿态控制器进行对比分析,结果表明:建立的时变性动力学模型可以使自适应反步终端滑模控制器良好地应用到无人机上,姿态角控制效果得到明显改善,试验中姿态角误差分别降低了25.57%,24.21%和19.41%,同时控制器对外界未知干扰不敏感,且具有较强的鲁棒性.
To improve the controllability of plant protection ummanned aerial vehicle( UAV) with eight rotors,the level of liquid in the tank is analysed and modelled during pesticide spraying process. As a result,formulas for the liquid mass and moment of its inertia are presented in terms of time,causing an accurate dynamical model in time domain. To validate the correctness and effectiveness of the model,attitude controllers are designed by using adaptive backstepping terminal sliding mode control technology. Firstly,the typical backstepping control method is used,then the terminal sliding mode control is introduced for the last state to converge the ideal value in a finite period of time,finally,an adaptive control law is established to eliminate uncertain disturbances. All the designed controllers have met the Lyapunov stability criterion. These proposed controllers are simulated and tested,whose results are compared with those of fuzzy PID attitude controller. The results show that the proposed dynamic model make the adaptive backstepping terminal sliding mode controller applicable for the plant protectionUAV. Compared with Fuzzy PID controllers,the effectiveness of attitude controller is improved greatly,the errors in attitude angle are reduced by 25. 57%,24. 21% and 19. 41% in the experiment,respectively. Additionally,the controllers are insensitive to random disturbances and subject to a nicer robustness property.
出处
《排灌机械工程学报》
EI
CSCD
北大核心
2015年第11期1006-1012,共7页
Journal of Drainage and Irrigation Machinery Engineering
基金
山西省自然科学基金资助项目(20120321008-01)
关键词
植保无人机
药箱建模
控制器设计
滑模控制
仿真与试验
plant protection UAV
liquid tank modeling
controller design
sliding mode control
simulation and experiment
