Fuzzy Self-adaptive Proportional Integration Differential Control for Attitude Stabilization of Quadrotor UAV

The technology of attitude control for quadrotor unmanned aerial vehicles(UAVs) is one of the most important UAVs' research areas.In order to achieve a satisfactory operation in quadrotor UAVs having proportional integration differential(PID) controllers,it is necessary to appropriately adjust the controller coefficients which are dependent on dynamic parameters of the quadrotor UAV and any changes in parameters and conditions could affect desired performance of the controller.In this paper,combining with PID control and fuzzy logic control,a kind of fuzzy self-adaptive PID control algorithm for attitude stabilization of the quadrotor UAV was put forward.Firstly,the nonlinear model of six degrees of freedom(6-DOF) for quadrotor UAV is established.Secondly,for obtaining the attitude of quadrotor,attitude data fusion using complementary filtering is applied to improving the measurement accuracy and dynamic performance.Finally,the attitude stabilization control simulation model of the quadrotor UAV is build,and the self-adaptive fuzzy parameter tuning rules for PID attitude controller are given,so as to realize the online self-tuning of the controller parameters.Simulation results show that comparing with the conventional PID controller,this attitude control algorithm of fuzzy self-adaptive PID has a better dynamic response performance.

Fixed-Time Controller Design for a Quadrotor UAV with Asymmetric Output Error Constraints

In this article,a fixed-time tracking control strategy is proposed for a quadrotor UAV(QUAV)with external disturbance and asymmetric output error constraints.Firstly,a dynamic model of the QUAV is transformed into a strict feedback system with external disturbance,and it is decoupled into attitude subsystem and position subsystem for simplifying controller design.Secondly,an asymmetric tangent barrier Lyapunov function(ATBLF)is applied to solve the tracking error constraints problem,and a fixed-time control law is designed.Meanwhile,a fixed-time disturbance observer(FTDO)is designed to cope with external disturbance.Then,it is proved that the designed controller guarantees the tracking error remains within the constraint ranges and converges to zero in fixed-time by Lyapunov stability theory.Finally,the effectiveness of the proposed control scheme is verified by numerical simulations.

A Composite Adaptive Fault-Tolerant Attitude Control for a Quadrotor UAV with Multiple Uncertainties

In this paper,a composite adaptive fault-tolerant control strategy is proposed for a quadrotor unmanned aerial vehicle(UAV)to simultaneously compensate actuator faults,model uncertainties and external disturbances.By assuming knowledge of the bounds on external disturbances,a baseline sliding mode control is first designed to achieve the desired system tracking performance and retain insensitive to disturbances.Then,regarding actuator faults and model uncertainties of the quadrotor UAV,neural adaptive control schemes are constructed and incorporated into the baseline sliding mode control to deal with them.Moreover,in terms of unknown external disturbances,a disturbance observer is designed and synthesized with the control law to further improve the robustness of the proposed control strategy.Finally,a series of comparative simulation tests are conducted to validate the effectiveness of the proposed control strategy where a quadrotor UAV is subject to inertial moment variations and different level of actuator faults.The capabilities and advantages of the proposed control strategy are confirmed and verified by simulation results.

Fuzzy intelligent control method for improving flight attitude stability of plant protection quadrotor UAV

At present,the attitude control method of plant protection UAV is the classical PID control,but there are some imperfections in the PID control,such as the contradiction between speediness and overshoot,the weak anti-jamming ability and adaptability.The physical parameters of plant protection UAV are time-varying,and the airflow also interferes with it.The control ability of classical PID is limited,and its control parameters are fixed,and its anti-jamming ability and adaptability are not strong.Therefore,a fuzzy adaptive PID controller is proposed in this paper.Fuzzy logic control is used to optimize the control parameters of PID in order to improve the dynamic and static performance and adaptability of attitude control of plant protection UAV.In the process of research,the mathematical model of UAV is established firstly,then the fuzzy adaptive PID is designed,and then the simulation is carried out in Simulink.The simulation results show that the fuzzy adaptive PID controller has better dynamic and static control performance and adaptability than the traditional PID controller.Therefore,the proposed control method has excellent application value in the attitude of plant protection UAV.

Fast Active Fault-Tolerant Control for a Quadrotor UAV Against Multiple Actuator Faults

This paper proposes a fast adaptive fault estimator-based active fault-tolerant control strategy for a quadrotor UAV against multiple actuator faults.A fast adaptive fault estimation algorithm is designed to estimate the unknown actuator fault parameters.By synthesizing the fast adaptive fault estimator with the embedded control law,an active fault-tolerant control mechanism is established to compensate the adverse e®ects of multiple actuator faults.The e®ectiveness of the proposed strategy is validated through both numerical simulations and experimental tests.

Adaptive trajectory tracking controller design for a quadrotor UAV with payload variation

Purpose-The purpose of this paper is to enhance the quadrotor’s capability of short-distance delivery to satisfy the large demand for quadrotor,which is used for goods distribution in huge warehouses,under time-varying payload and external wind disturbance.Design/methodology/approach-A trajectory tracking controller design based on the combination of an adaptive sliding mode control(ASMC)method and the active disturbance rejection control(ADRC)technique is proposed.Besides,an inner-outer loop control system structure is adopted.Findings–Simulation results of different trajectory tracking verify the effectiveness and robustness of the proposed tracking control method under various conditions,including parameter uncertainty and external wind disturbance.The proposed control strategy ensures that quadrotor UAV is capable of tracking linear and spiral trajectory well whether it loads or unloads goods in the presence of the external wind disturbance.Originality/value-The proposed method of designing a trajectory tracking controller is based on an integral ADRC and ASMC scheme so as to deal with the trajectory tracking problem for a quadrotor with payload variation.

Wind disturbance rejection control based on the dynamic parameters estimation of quadrotors UAV

The turbulence or gust in quadrotor flight environment causes drastic changes in the unmanned aerial vehicle(UAV)aerodynamic parameters.Especially,rotor thrust coefficient and reaction torque coefficient of the UAV encounter uncertainty fluctuation,which may undermine the control performance.A real-time estimation strategy for these aerodynamic parameters is proposed to improve the identification on the disturbance.First,the unscented Kalman filter(UKF)algorithm is used to estimate the UAV states and aerodynamic parameters.Then,a double-loop structure,consisting of position and attitude,is designed for the trajectory tracking control.In the outer loop,a proportional-derivative controller is adopted to carry out position tracking and provide Euler angle references for the inner loop,called attitude controller.Moreover,the attitude controller is designed using an inverse dynamic technique.The main contribution of this study is to propose a joint estimation on the aerodynamic parameters with wind disturbance as well as the UAV states.This strategy plays an important role in refining time-varying parameters of wind disturbance.A number of simulations are executed to verify the effectiveness of the proposed method.

基于自适应RBF神经网络具有模型不确定性的四旋翼无人机指定时间预设性能控制方法

四旋翼无人机具有强耦合和欠驱动的特点,在飞行过程中很容易受到外界干扰,进而影响整个无人机系统的稳定性和精度。为此,提出了一种基于RBF神经网络的指定时间预设性能约束控制策略。首先,针对四旋翼无人机的不确定数学模型难以精确建立,并且在执行任务过程中存在外部未知扰动问题,提出了一种基于指定时间预设性能控制方法,将四旋翼无人机的轨迹跟踪问题转换为对位置子系统和姿态子系统的期望指令跟踪问题;其次,在设计控制器过程中,为了解决“微分爆炸”问题产生的滤波器误差,引入一种新型滤波误差补偿方法,通过RBF神经网络逼近外部未知扰动,并将预测结果补偿给控制器以提高轨迹跟踪的鲁棒性。最后,应用仿真模拟方法验证无人机控制系统稳定性和性能优势,通过飞行试验验证,微风聚拢环境下实际飞行轨迹与仿真模拟结果趋于一致,自主轨迹跟踪起降位置偏差小于1 cm,证明了所提出算法的有效性。

基于模糊增益滑模四旋翼无人机自适应容错控制

针对四旋翼无人机执行器故障下的轨迹跟踪问题,提出一种基于模糊增益滑模的自适应容错控制方法.首先,针对直接控制通道利用自适应机构在线估计执行器故障并加以补偿,采用基于模糊增益的滑模控制器设计可调控制器以满足鲁棒性要求.针对间接驱动通道设计基于模糊增益的滑模控制器,从而实现无人机全通道的容错控制设计,该方法具有良好的容错能力的同时,能很好地抑制系统颤振,获得平滑的控制信号.最后,对四旋翼无人机在不同控制器下的轨迹追踪性能进行了对比仿真,结果表明,系统在故障以及扰动下具有良好的飞行性能.

小型四旋翼无人机姿态控制研究

针对小型无人机无法搭载高精度、体积大的传感器,从而无法获得高精度姿态信息的问题,基于STM32单片机的无人机结构和飞行姿态控制原理,采用MPU6050姿态信息采集模块运动处理单元DMP进行姿态解算,并应用卡尔曼滤波技术提升了姿态数据的准确性。为了更好地选择控制算法,分别使用串级PID控制方法、滑模控制算法和LQR控制算法进行仿真实验。结果表明,将滤波算法与控制算法相结合可以使小型四旋翼无人机具备更出色的操纵性能及更好的稳定性,双闭环结构串级PID控制方法可在3 s内使无人机稳定,具有更好的稳态特性和抗干扰特性。

基于分数阶滑模控制的无人机轨迹跟踪控制器设计

四旋翼无人机在农业、工业和国防等领域广泛应用,但其复杂的系统特性和对扰动的敏感性使得控制变得困难。首先,考虑分数阶方法具有良好的鲁棒性以及调节灵活性的优点,将整数阶积分滑模面和改进的分数阶指数趋近律相结合,设计出了一种新的分数阶积分滑模控制器。然后,将所设计的分数阶积分滑模控制器应用于四旋翼无人机轨迹跟踪控制问题。仿真结果表明,所提控制器作用下的四旋翼无人机进行轨迹跟踪时响应速度快、无超调,且对外界干扰具有较强的鲁棒性。

考虑滑块动态特性的变质心四旋翼无人机双回路控制

针对滑块动态特性引入的附加干扰力矩造成系统姿态抖动强烈的问题,开展变质心四旋翼无人机滑块参数设计与姿态/伺服双回路控制研究。通过建立双滑块变质心四旋翼无人机八自由度运动模型,明确了滑块的引入对系统的影响,给出了与滑块动态特性相关的各项附加干扰力矩;分析并设计了滑块的安装位置、质量以及行程等参数,降低滑块对系统的耦合与干扰;最后以滑块驱动力作为控制量,设计了姿态/伺服双回路动态滑模控制器,同时利用非线性扰动观测器对复合扰动进行估计和补偿,并进行了仿真试验。仿真结果表明,在考虑滑块动态特性的情况下,所设计的控制器能够实现对变质心四旋翼无人机的姿态控制,并具有良好的抗干扰性能与鲁棒性。

基于区间二型模糊PID的四旋翼无人机姿态控制

针对传统PID控制与一型模糊控制在四旋翼无人机姿态控制中响应速度慢、超调量大等问题,提出了一种区间二型模糊控制与传统PID控制相结合的控制算法。首先,在一型模糊系统的基础上对系统的单值前件和后件进一步模糊化形成区间前件和后件,更适于处理模糊信息。其次,利用具有停止条件的改进迭代算法(enhanced iterative algorithm with stop condition,EIASC)进行降型过程中开关点的计算,减少了计算时间,并将求解出的参数变化量作为初始PID控制参数值的补偿。最后,在建立的四旋翼无人机动力学模型上对所提算法进行仿真验证,仿真结果表明,所提算法比传统PID控制算法和一型模糊PID控制算法具有更快的响应速度、更高的稳态精度和更小的超调量。

拓扑切换下基于SO(3)的四旋翼时变编队跟踪控制

针对有向拓扑切换条件下的多四旋翼无人机时变编队跟踪控制问题,在领航-跟随策略下,利用局部邻居状态信息构造了性能约束下基于特殊正交群SO(3)的一致性控制协议。在该协议中,领航无人机的信息仅能提供给邻居无人机,且邻居无人机集合会发生变化。采用特殊正交群SO(3)空间中的旋转矩阵表征四旋翼的姿态,在此基础上设计姿态控制器,提高了编队控制的收敛速度。仿真实验表明,当有向拓扑切换的驻留时间大于固定阈值且满足时变编队跟踪控制可行性条件时,采用所设计控制律可使集群系统实现时变编队队形控制,验证了所提算法的有效性。

四旋翼无人机鲁棒嵌套饱和控制

针对四旋翼无人机在执行任务中,动力系统受到输入饱和限制,传统嵌套饱和控制算法收敛条件严格、收敛速度慢、稳态精度不高、鲁棒性不强等问题,提出了一种四旋翼无人机鲁棒嵌套饱和控制算法。首先,设计了条件相对放松的嵌套饱和控制算法,降低了设计难度,并且给出了闭环系统的稳定性证明。其次,基于条件放松的嵌套饱和控制算法,引入自耦PD和补偿函数观测器,提升系统的响应速度,稳态精度以及鲁棒性,并利用Lyapunov稳定性原理证明了闭环系统的全局稳定性。最后,将所提算法与传统嵌套饱和控制算法和PD控制算法进行了仿真对比,结果表明:本文提出的算法在暂态性能、稳态性能和鲁棒性上都是最优。

基于滑模自适应迭代学习的四旋翼无人机轨迹跟踪

针对四旋翼无人机轨迹跟踪问题,在考虑外部扰动的情况下,提出一种滑模自适应迭代学习的控制算法。所设计的控制器由两部分组成:第一部分是滑模子控制器,作为四旋翼无人机系统的反馈控制器;第二部分是迭代学习子控制器,作为无人机系统的前馈控制器。在迭代学习过程中,迭代学习子控制器的增益可以根据轨迹跟踪误差自适应改变,能够提高四旋翼无人机的轨迹跟踪效果。最后通过软件仿真对所提出的四旋翼无人机轨迹跟踪算法的有效性进行验证。

基于自抗扰的四旋翼无人机控制方法

针对四旋翼无人机在飞行过程中存在的外部干扰和模型不确定性的问题,采用自抗扰控制(ADRC)方法实现姿态控制。同时对ADRC进行改进:针对扩张状态观测器(ESO)中误差增益过大、容易引起误差反复切换产生抖振的情况,构造nfal函数来代替fal函数,实现抗扰能力和抖振之间的平衡;采用遗传算法对ADRC中的参数进行整定,提高了参数整定效率。在仿真系统中,证明改进后的ADRC方法抗扰性能在一定程度上有所提高;在基于Links-RT实时仿真系统的无人机飞控半实物(HIL)实验平台中,验证了该控制方法的有效性。

基于视觉伺服的四旋翼吊挂抗摆控制方法

四旋翼吊挂飞行时载荷的摆动会显著影响无人机的操纵性和稳定性,无人机运动会引起负载振荡,严重威胁控制系统的安全。针对无人机从起飞阶段加速跟踪远距离时变期望轨迹,尤其是弧形轨迹的过渡过程中,吊挂载荷摆动频率较高的问题,提出了一种基于视觉伺服的三闭环轨迹跟踪和载荷抗摆控制方法,通过对期望姿态角指令进行修正,减小载荷摆动对无人机的影响。对不同吊挂载荷质量以及载荷质量突变的情况进行了分析,仿真和飞行实验结果表明,该抗摆控制策略不但可以极大地降低吊挂载荷的摆动频率,还能使无人机平稳跟踪期望飞行轨迹。

迭代学习的四旋翼无人机重复航迹跟踪控制实验研究

新工科建设以强化学生的工程实践与创新能力的思想为指导,为应对新的要求并推进实验实践教学改革,设计一种适应于本科生工程实践训练的四旋翼无人机飞行实验平台。该实验平台结合机械、信号处理、自动控制等学科知识,以四旋翼无人机为研究对象,分析四旋翼无人机动力模型,研究和设计迭代控制算法。采用Simulink进行仿真,以北京航空航天大学可靠飞行控制组研发的RflySim无人机模拟器平台搭建所设计的实验平台。最后,进行现场实际测试和航迹跟踪飞行测试,测试结果符合实验的预期,且航迹跟踪准确。所设计系统易于激发学生的参与兴趣,能够有效提高学生的动手能力及工程实践技能。

全驱动倾转四旋翼式飞枪的建模与控制

欠驱动的机/枪一体式四旋翼飞枪位置和姿态的控制存在耦合,无法实现带俯仰角的悬停射击,移动射击过程中火控策略复杂。设计了一种全驱动的倾转四旋翼无人机,并以此作为飞枪载体,在实现系统解耦的同时,简化了控制分配方法。首先通过牛顿欧拉法对系统进行数学建模,然后利用反步法设计控制器并证明系统稳定性,最后通过Simulink进行仿真实验。实验结果表明:本文设计的全驱动飞枪模型可实现位置和姿态的解耦控制,跟踪误差小,可满足飞枪悬停射击、移动射击的射击要求,适用于实时性要求高的飞/火控系统。