Compared with the quad-rotor unmanned aerial vehicle (UAV), the coaxial twelve-rotor UAV has stronger load carrying capacity, higher driving ability and stronger damage resistance. This paper focuses on its robust adaptive control. First, a mathematical model of a coaxial twelve-rotor is established. Aiming at the problem of model uncertainty and external disturbance of the coaxial twelve-rotor UAV, the attitude controller is innovatively adopted with the combination of a backstepping sliding mode controller (BSMC) and an adaptive radial basis function neural network (RBFNN). The BSMC combines the advantages of backstepping control and sliding mode control, which has a simple design process and strong robustness. The RBFNN as an uncertain observer, can effectively estimate the total uncertainty. Then the stability of the twelve-rotor UAV control system is proved by Lyapunov stability theorem. Finally, it is proved that the robust adaptive control strategy presented in this paper can overcome model uncertainty and external disturbance effectively through numerical simulation and prototype of twelve-rotor UAV tests.
Altitude regulation is a fundamental problem in UAV(unmanned aerial vehicles) control to ensure hovering and autonomous navigation performance.However,data from altitude sensors may be unstable by interference.A digital-filter-based improved adaptive Kalman method is proposed to improve accuracy and reliability of the altitude measurement information.A unique sensor data fusion structure is designed to make different sensors switch automatically in different environment.Simulation and experimental results show that an improved Sage-Husa adaptive extended Kalman filter(SHAEKF) is adopted in altitude data fusion which means that altitude error is limited to 1.5m in high altitude and 1.2m near the ground.This method is proved feasible and effective through hovering flight test and three-dimensional track flight experiment.
In order to meet the application requirement of a certain long wavelength infrared （LWIR） seeker, a small volume, light weight and passively athermalized infrared OR） objective is designed in this paper. The two-lens telephoto struc- ture is adopted by merely using aluminum alloy as the housing material. By balancing the thermo-optical coefficient and thermal expansion coefficient of materials, an athermalized IR seeker with effective focal length of 90 mm and F number of 1.2 is achieved. The whole optical length is 75 ram, and the weight is only 234 g. The objective can remain fine imaging quality under temperature range from -40 ℃ to 60 ℃, which is beneficial to the lightweight design oflR seekers.
The robust attitude control for a novel coaxial twelve-rotor UAV which has much greater payload capacity,higher drive capability and damage tolerance than a quad-rotor UAV is studied. Firstly,a dynamical and kinematical model for the coaxial twelve-rotor UAV is designed. Considering model uncertainties and external disturbances,a robust backstepping sliding mode control( BSMC) with self recurrent wavelet neural network( SRWNN) method is proposed as the attitude controller for the coaxial twelve-rotor. A combinative algorithm of backstepping control and sliding mode control has simplified design procedures with much stronger robustness benefiting from advantages of both controllers. SRWNN as the uncertainty observer is able to estimate the lumped uncertainties effectively.Then the uniformly ultimate stability of the twelve-rotor system is proved by Lyapunov stability theorem. Finally,the validity of the proposed robust control method adopted in the twelve-rotor UAV under model uncertainties and external disturbances are demonstrated via numerical simulations and twelve-rotor prototype experiments.
针对微管类（直径0~300μm）零件的夹持需求,基于有限元分析设计了一种非对称式压电驱动的微夹持器.该微夹持器采用柔性铰链实现压电陶瓷输出位移的传递和放大.采用平行四杆机构实现夹钳末端的平行移动.通过检测柔性铰链处应变的方法,间接地测量夹持力和位移信息.微夹持器的实验特性显示位移的放大倍率为5.6倍,夹持器末端夹钳可以实现平行移动.力和位移标定实验中显示夹持力的分辨力在2.41 m N,位移的分辨力在0.22μm,且力/位移与应变具有很好的线性关系.采用增量式PID的控制算法对系统进行力/位移的闭环控制.以微型玻璃管（直径150μm）夹持为例,系统的阶跃响应实验显示,系统的力/位移控制可以实现无超调.实验结果表明增量式PID控制算法可以实现对本微夹持器力/位移的准确、稳定控制.
To overcome the shortcomings of traditional artificial spraying pesticides and make more efficient prevention of diseases and pests,a coaxial sixteen-rotor unmanned aerial vehicle(UAV)with pesticide spraying system is designed.The coaxial sixteen-rotor UAV’s basic structure and attitude estimation method are explained.The whole system weights 25 kg,cruising speed can reach 15 m/s,and the flight time is more than 20 min.When the UAV takes large load,the traditional extended Kalman filter(EKF)attitude estimation method can not meet the work requirements under the condition of strong vibration,the attitude measure accuracy is poor and the attitude angle divergence is easily caused.Hence an attitude estimation method based on EKF algorithm with 22 dimensional state vector is proposed which can solve these problems.The UAV system consists of STM32F429 as controller,integrating following measure sensors:accelerometer and gyroscope MPU6000,magnetometer LSM303D,GPS NEO-M8N and barometer.The attitude unit quaternion,velocity,position,earth magnetic field,biases error of gyroscope,accelerometer and magnetometer are introduced as the inertial navigation systems(INS)state vector,while magnetometer,global positioning system(GPS)and barometer are introduced as observation vector,thus making the estimate of the navigation information more accurate.The control strategy of coaxial sixteen-rotor UAV is based on the control method of combining active disturbance rejection control(ADRC)and proportion integral derivative(PID)control.Actual flight data are used to verify the algorithm,and the static experiment shows that the precision of roll angle and pitch angle of the algorithm are±0.1°,the precision of yaw angle is±0.2°.The attitude angle output of MTi sensor is used as reference.The dynamic experiment shows that the accuracy of attitude estimated by EKF algorithm is quite similar to that of MTi’s output,moreover,the algorithm has good real-time performance which meets the need of high maneuverability of agricultural UAV.
