Intelligent PID Control Method for Quadrotor UAV with Serial Humanoid Intelligence

Quadrotor unmanned aerial vehicles(UAVs)are widely used in inspection,agriculture,express delivery,and other fields owing to their low cost and high flexibility.However,the current UAV control system has shortcomings such as poor control accuracy and weak anti-interference ability to a certain extent.To address the control problem of a four-rotor UAV,we propose a method to enhance the controller’s accuracy by considering underactuated dynamics,nonlinearities,and external disturbances.A mathematical model is constructed based on the flight principles of the quadrotor UAV.We develop a control algorithm that combines humanoid intelligence with a cascade Proportional-Integral-Derivative(PID)approach.This algorithm incorporates the rate of change of the error into the inputs of the cascade PID controller,uses both the error and its rate of change as characteristic variables of the UAV’s control system,and employs a hyperbolic tangent function to improve the outer-loop control.The result is a double closed-loop intelligent PID(DCLIPID)control algorithm.Through MATLAB numerical simulation tests,it is found that the DCLIPID algorithm reduces the rise time by 0.5 s and the number of oscillations by 2 times compared to the string PID algorithm when a unit step signal is used as input.A UAV flight test was designed for comparison with the serial PID algorithm,and it was found that when the UAV planned the trajectory autonomously,the errors in the X-,Y-,and Z-directions were reduced by 0.22,0.21,and 0.31 m,respectively.Under the interference environment of artificial wind about 3.6 m·s^(-1),the UAV hovering error in X-,Y-,and Z-directions are 0.24,0.42,and 0.27 m,respectively.The simulation and experimental results show that the control method of humanoid intelligence and cascade PID can improve the real-time,control accuracy and anti-interference ability of the UAV,and the method has a certain reference value for the research in the field of UAV control.

An adaptive backstepping sliding mode method for flight attitude of quadrotor UAVs

To overcome nonlinear and 6-DOF(degrees of freedom)under-actuated problems for the attitude and position of quadrotor UAVs,an adaptive backstepping sliding mode method for flight attitude of quadrotor UAVs is proposed,in which an adaptive law is designed to online estimate the parameter variations and the upper bound of external disturbances and the assessments is utilized to compensate the backstepping sliding mode control.In addition,the tracking error of the design method is shown to asymptotically converge to zero by using Lyapunov theory.Finally,based on the numerical simulation of quadrotor UAVs using the setting parameters,the results show that the proposed control approach can stabilize the attitude and has hover flight capabilities under the parameter perturbations and external disturbances.

Three-dimensional multi-constraint route planning of unmanned aerial vehicle low-altitude penetration based on coevolutionary multi-agent genetic algorithm

To address the issue of premature convergence and slow convergence rate in three-dimensional (3D) route planning of unmanned aerial vehicle (UAV) low-altitude penetration,a novel route planning method was proposed.First and foremost,a coevolutionary multi-agent genetic algorithm (CE-MAGA) was formed by introducing coevolutionary mechanism to multi-agent genetic algorithm (MAGA),an efficient global optimization algorithm.A dynamic route representation form was also adopted to improve the flight route accuracy.Moreover,an efficient constraint handling method was used to simplify the treatment of multi-constraint and reduce the time-cost of planning computation.Simulation and corresponding analysis show that the planning results of CE-MAGA have better performance on terrain following,terrain avoidance,threat avoidance (TF/TA2) and lower route costs than other existing algorithms.In addition,feasible flight routes can be acquired within 2 s,and the convergence rate of the whole evolutionary process is very fast.

Modeling and simulation of quadrotor UAV based on Simscape

In order to speed up and simplify the design of the quadrotor unmanned aerial vehicle(UAV)and carry out experimental simulation and verification of relevant control algorithms,this paper analyzed the system dynamics model of the mechanical structure and flight principle of the quadrotor aircraft,and used the Newton-Euler method to derive the non-linear dynamic equations.Aiming at improving the modeling accuracy and system integrity of the quadrotor,the physical system modeling was combined with the CAD software and the Matlab/Simscape toolbox.The three-dimensional quadrotor solid model built by CAD software was imported into the Simscape simulation platform to construct the body and power system model of the quadrotor.Based on this,the control algorithm designed by Simulink was added to the simulation platform to facilitate the experiment verification and parameter tuning.The simulation results show that the designed aircraft can achieve hover and tracking well and meet the control performance requirements of the system.

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.

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.

基于能耗优化的四旋翼无人机航迹规划:分段式高斯伪谱法

在四旋翼无人机航迹规划中引入能耗优化策略以延长其飞行时间,能够显著提升其实用性和经济性。为此,提出了一种基于分段式高斯伪谱法的能耗最优航迹规划算法。首先,构建了四旋翼无人机运动学-能耗综合模型,能定量描述无人机运动学及能耗间耦合关系;其次,基于此模型,将考虑能耗优化的航迹规划问题转化为带约束的连续时间优化问题;最后,设计了分段式高斯伪谱法求解出优化航迹,其中通过滑动选取优化子区间的方法,在航点数量较多的复杂飞行任务中有效缩短了计算时间,同时提升了轨迹的平滑性和航点跟踪准确性。仿真和实验结果表明,与传统定航点飞行相比,所提算法能大幅降低飞行能耗,与常用优化算法相比,所提算法在保证能耗优化效果的同时,所需计算时间更短,航点跟踪精度更高。

Application of UAV in Road Safety in Intelligent Areas

With the continuous development of remote sensing(RS)technology,the surface information can be collected conveniently and quickly by using the popular unmanned aerial vehicle(UAV).The application of UAV low altitude RS technology in road safety in intelligent area has certain practical significance.It can provide safety warning for most drivers,and provide auxiliary decision-making for the road supervision department.Through the collection,processing,calculation and analysis of the road image,the UAV can find out the road obstacles with potential safety hazards,identify the road pit,calculate the radius and depth of the road pit through the digital mapping system,predict the accident risk according to different speed and provide scientific basis for the road safety monitoring.At the same time,UAV can provide repair scheme for damaged roads,estimate the quantity of materials needed for repair,and achieve the target of resource saving and efficiency improvement.The experimental results show that the UAV can not only provide scientific prediction information for driving safety,but also provide relatively accurate material consumption for road repair.

Adaptive leader follower control for multiple quadrotors via multiple surfaces control

Based on the multiple surface and fixed undirected communication topology, the adaptive leader follower contrul for multiple quadrotors is discussed. Our approach is based on leader follower architecture. Multiple surface control （MSC） is used to design consensus controller to make multiple quadrotors construct a formation during flying with the presence of uncertainty item caused by the ground effect during landing or taking off. Simulation results are presented to validate the effectiveness of the proposed controller.

四旋翼农业无人机模块化设计及有限元分析

为进一步提高四旋翼农业无人机的升级、装配和维修效率,拓展农业无人机的应用范围,提出一种针对农业无人机的模块化设计方法。首先,综合分析四旋翼农业无人机中任意零件间在连接固定、功能和几何参数层面的相关关系,构建零件关系图,将相关性强的零件聚类成部件,并计算部件在各层面的相关性矩阵。其次,利用AHP赋予各层面不同权值,计算部件间综合强度相关性矩阵,依据模块评判原则合并部件。最后,建立模块结构,根据作业需求组合相应模块,并对关键功能模块进行静动态特性分析。研究结果表明:该模块化设计方法将28个无人机零件简化为6个独立的模块;无人机更新换代时,只需对相应发生改变的模块进行重新设计制造;模块的独立性简化装配的工艺流程,降低维修成本;6个模块可以组合成喷洒无人机或播撒无人机,使无人机不仅适用于农药的喷洒,也适用于种子和肥料的撒播;通过对中央舱模块的有限元分析,其最大应力为23.889 MPa,远小于碳纤维最大抗拉强度4 780 MPa,前四阶固有频率都大于无人机工作时最高频率32.75 Hz,以及其最大形变量为0.004 635 9 mm,满足无人机极限工况下的形变要求。

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。

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.

多四旋翼无人机编队自适应容错控制

针对四旋翼无人机在编队控制时受到执行器故障的影响,引起无人机之间跟踪误差的问题,而传统PID控制的固定参数无法适用于四旋翼无人机面临复杂的环境,因此设计了模糊自适应PID容错控制器以及多无人机的滑模协同控制器.首先,针对执行器故障无人机进行系统建模,给定领导无人机的参考轨迹,通过设计的模糊自适应PID控制器使得执行器故障的无人机跟踪给定轨迹.其次,基于滑模控制理论,设计编队协同控制器,控制Follower无人机与Leader无人机之间的距离误差趋近于零,实现期望的编队队形.最后,通过仿真实验对比结果表明,所设计方法超调量小,鲁棒性强,对四旋翼无人机有较好的控制效果.

风扰下变质量四旋翼轨迹跟踪控制

针对存在风扰和变质量负载扰动的四旋翼无人机轨迹跟踪控制问题,提出了一种基于降阶广义比例积分观测器的动态面模糊滑模控制方法。首先,建立含风扰和变质量负载扰动的四旋翼无人机系统模型;其次,结合四旋翼无人机系统模型设计降阶广义比例积分观测器估计外界风扰;再次,设计动态面滑模控制器,并采用模糊控制模糊化切换增益,以此有效地抑制抖振;然后,通过Lyapunov稳定性证明四旋翼无人机系统的稳定性;最后,通过Matlab-Simulink进行3种控制方法的仿真比较。仿真结果表明,当存在风扰和变质量负载扰动时,该控制方法抗风扰能力更强,稳定性更好,位姿跟踪精度更高。

基于SSA优化PID在四旋翼无人机轨迹跟踪中的研究

在大多数应用中,四旋翼无人机要按照预期轨迹连续准确的飞行。PID控制在无人机控制应用广泛,但是参数难以选择,参数设置不当会导致结果不佳,对实际控制应用的适应性差。为了实现四旋翼无人机精确轨迹跟踪,文中提出使用麻雀搜索算法对PID控制器的参数进行整定优化的方法。首先对四旋翼无人机进行建模,用麻雀搜索算法对模型中的PID控制器参数整定,最后在Simulink中进行轨迹跟踪实验。实验结果表明麻雀搜索算法优化后的PID控制器使四旋翼无人机轨迹跟踪的精度高,跟踪速度快。

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。

改进麻雀搜索算法的四旋翼PID参数优化设计

针对四旋翼无人机PID控制器参数人工整定复杂、费时且难以确保最优的问题,提出一种基于改进麻雀搜索算法的PID参数优化方法,用于四旋翼无人机控制系统。首先引入Piecewise混沌映射,增强初始种群分布的均匀性;其次在探索者位置更新公式中加入动态惯性权重,提升算法全局优化性能;最后结合自适应混合变异策略和历史最优值,增强变异的多样性、提高算法的搜索效率及精度。仿真结果表明,相比于标准麻雀搜索算法、粒子群算法和遗传算法,用改进麻雀搜索算法优化串级PID控制器参数,能够使控制系统具有更快的响应速度、更高的稳态精度。

基于干扰补偿的四旋翼无人机轨迹跟踪控制

针对带有未知外部扰动的四旋翼无人机轨迹稳定跟踪问题,设计了一种基于干扰补偿的控制策略。针对四旋翼无人机位置环设计PID位置控制器,并基于干扰估计器对外部干扰进行补偿。通过姿态解算得到期望姿态,并针对四旋翼无人机姿态环设计具有强鲁棒性能的INDI姿态控制器,通过Simulink进行仿真对比试验。实验结果表明,该控制策略可实现带有未知外部扰动条件下的四旋翼无人机轨迹跟踪能力。