Two-layer formation-containment fault-tolerant control of fixed-wing UAV swarm for dynamic target tracking

This paper tackles the formation-containment control problem of fixed-wing unmanned aerial vehicle(UAV)swarm with model uncertainties for dynamic target tracking in three-dimensional space in the faulty case of UAVs’actuator and sensor.The fixed-wing UAV swarm under consideration is organized as a“multi-leader-multi-follower”structure,in which only several leaders can obtain the dynamic target information while others only receive the neighbors’information through the communication network.To simultaneously realize the formation,containment,and dynamic target tracking,a two-layer control framework is adopted to decouple the problem into two subproblems:reference trajectory generation and trajectory tracking.In the upper layer,a distributed finite-time estimator(DFTE)is proposed to generate each UAV’s reference trajectory in accordance with the control objective.Subsequently,a distributed composite robust fault-tolerant trajectory tracking controller is developed in the lower layer,where a novel adaptive extended super-twisting(AESTW)algorithm with a finite-time extended state observer(FTESO)is involved in solving the robust trajectory tracking control problem under model uncertainties,actuator,and sensor faults.The proposed controller simultaneously guarantees rapidness and enhances the system’s robustness with fewer chattering effects.Finally,corresponding simulations are carried out to demonstrate the effectiveness and competitiveness of the proposed two-layer fault-tolerant cooperative control scheme.

Prediction of electric-powered fixed-wing UAV endurance

To overcome the problems encountered in predicting the endurance of electricpowered fixed-wing unmanned aerial vehicles(UAVs),which were stemmed from the dynamic changes in electric power system efficiency and battery discharge characteristics under different operating conditions,the required battery power model and battery discharge model were studied.The required battery power model was determined using an approximate model of electric power system efficiency based on wind tunnel testing and the self-adaptive penalty function.Furthermore,current correction and ambient temperature correction terms were proposed for the trained Kriging model representing the discharge characteristics under standard operation,and then the discharged capacity-terminal voltage model was established.Through numerical integration of this model with the required battery power model,the electric-powered fixed-wing UAV endurance prediction model was obtained.Laboratory tests indicated that the proposed endurance model could precisely calculate the battery discharge time and accurately describe the battery discharge process.The similarity of the theoretical and flight test results reflected the accuracy of the proposed endurance model as well as the importance of considering dynamic changes in power system efficiency in endurance calculations.The proposed endurance model meeting precision requirements can be used in practical engineering applications.

小型固定翼无人机自主起飞控制系统

为了能够增强小型固定翼无人机在起飞阶段的安全性和稳定性,设计了固定翼无人机自主起飞控制系统,并实现其功能。首先在三维空间内建立无人机起飞阶段的六自由度运动数学模型;根据无人机受力不同,将无人机起飞分为3个阶段,并分析每个阶段的动力学和运动学规律;搭建无人机自主起飞硬件实物平台,设计、制作并调试飞行控制板,结合无人机自身特性和控制任务要求,对所用的电机等元件进行选型以及对电路板进行焊接与底层调试。基于上述条件设计PID控制器,在有风扰动情况下对开环、闭环控制下无人机的起飞进行仿真,通过对比分析以及不断调整控制参数,以达到理想的控制效果,通过实地飞行实验,以验证该控制系统的可行性和稳定性。

无人机防滑刹车系统输出受限容错控制

研究了基于滑模观测器的无人机防滑刹车系统执行机构故障的容错控制方法。在考虑外界不确定干扰的同时,对执行机构故障的防滑刹车系统进行建模,构造非线性滑模观测器,利用滑模等值原理重构出执行机构故障值。将重构出的故障引入补偿控制律设计中,并结合障碍李雅普诺夫函数反演方法设计容错控制律,使得输出滑移率保持在一定约束区间内,通过构造干扰自适应估计器,消除了未知干扰和模型不确定性对系统的影响,基于李雅普诺夫理论及相关原理证明了该闭环系统半全局一致最终有界,最后通过仿真验证了所提方法的有效性。