Adaptive robust output feedback control for attitude tracking of quadrotor unmanned aerial vehicles

This work proposes a new adaptive robust output feedback control method for attitude reference tracking of a quadrotor unmanned aerial vehicle without using the angular velocity measurements. By using the K-filters well known in the adaptive control community, the necessity of velocity measurements or estimating is avoided. The attitude system model is transformed into a second-order model where the angular velocity measurements are not involved. However, the model includes mismatched uncertainties which should be estimated and compensated by the disturbance observers (DOBs). The controller is designed in a backstepping manner, and the dynamic surface technique is adopted to avoid the explosion of the controller complexity. For each Euler angle axis, the prescribed performance control technique is adopted to ensure a prescribed performance, the lumped disturbance is compensated by a DOB, and furthermore an adaptive law is introduced to adaptively update the corresponding uncertain inertia parameter which affects the control performance significantly. The control performance of the overall control system is analyzed rigorously from the viewpoint of input-to-state practical stability. In addition, it is shown how the adaptive laws contribute to improving the control performance. And simulation examples are provided to demonstrate the performance of the proposed method.     

四旋翼PIDNN控制器设计

针对传统四旋翼PID控制器参数整定困难和控制效果难以达到最优的问题,综合了传统PID控制器工程意义明确、参数整定简便以及神经网络的非线性映射和自学习的优点,构造了四旋翼神经网络PID(PIDNN)控制器。以神经网络的非线性映射特点和自学习能力优化了传统PID控制器的控制效果,借助PID控制器的构造特点,解决了神经网络层数、节点数和连接权重初值选取困难的问题。最后,通过仿真实验验证了算法的合理性和有效性。     

四旋翼飞行器鲁棒自适应姿态控制器设计

为实现四旋翼飞行器姿态的稳定控制,针对该系统的非线性、易受外界干扰和参数摄动影响等问题,提 出一种鲁棒自适应控制方法。首先通过分析四旋翼飞行器的工作原理,建立了动力学模型;其次在线性化飞行器模 型的基础上,设计了基于最优二次型鲁棒伺服控制方法的姿态控制器;然后应用模型参考自适应控制方法设计了自 适应补偿器消除系统不确定性的影响;最后对加入了鲁棒自适应控制的飞行器进行仿真。仿真结果表明：该控制器 具有稳定精确的指令跟踪性能和强鲁棒性,能够在复杂环境下实现稳定良好的姿态控制。     

Cooperative SLAM using fuzzy Kalman filtering for a collaborative air-ground robotic system

ABSTRACT

This paper presents a three-dimensional (3D) cooperative simultaneous location and mapping (SLAM) method for a collaborative air-ground robotic system, designed to manage an indoor quadrotor flying done together with a Mecanum-wheeled omnidirectional robot (MWOR) in indoor unknown and no GPS environments. An ORB (Oriented Fast and Rotated BRIEF)-SLAM 2.0 (ORB- SLAM 2.0) approach is used to produce a 3D map and discover the position of the indoor quadrotor simultaneously, and a particle-filter SLAM (FastSLAM 2.0) approach is employed to build the 2D map of the global environment for the MWOR. A more accurate 3D quadrotor position estimation (QPE) method for the quadrotor is proposed with the assistance of the MWOR. A cooperative SLAM using fuzzy Kalman filtering is proposed to fuse the outputs of the ORB-SLAM 2.0, FastSLAM 2.0, and QPE approaches, in order to localize the quadrotor more accurately. Both SLAM approaches, quadrotor position estimation method and cooperative SLAM have been implemented in the robotic operation system (ROS) environment. Moreover, the cooperative SLAM method is exploited to achieve landing of the quadrotor atop the MWOR. Five experiments are conducted to show the effectiveness and superiority of the proposed cooperative SLAM method.     

四旋翼不确定干扰前馈补偿与反步滑模姿态控制

针对四旋翼控制中由外部不确定干扰和系统参数不确定引起的具有时变特性的不确定界干扰问题,设计一种不确定干扰前馈补偿的反步滑模姿态抗干扰控制方法.采用牛顿欧拉方法建立带不确定干扰的四旋翼6自由度动力学模型,然后采用非线性干扰观测器对姿态系统中的不确定干扰进行观测估计,进而基于不确定干扰估计量的前馈补偿设计反步滑模控制器,最...     

四旋翼飞行器设计与平稳控制仿真研究

近年来,军用和民用市场的广阔应用需求和独特的优势促进了四旋翼飞行器(Quadrotor Helicopter)的发展。根据自主设计制作的样机,建立了四旋翼飞行器的动力学和动力系统动力学模型,并把卡尔曼滤波器应用于姿态解算,PID控制器用于姿态控制。仿真和试飞结果表明,所提出的控制策略是可行的,验证了动态模型建立的有效性。     

卡尔曼滤波在四旋翼飞行器姿态测量中的应用

针对简单均值滤波很难满足要求的不足,介绍一种四旋翼飞行器系统飞行姿态测量的新算法。在使用传统的加速度传感器获取数据的基础上,使用卡尔曼滤波的方法,将加速度传感器数据和陀螺仪数据进行融合,以单片机为核心的惯性测量单元进行试验。结果表明,该算法能避免动态噪声对加速度传感器数据的影响,提高四旋翼飞行器姿态测量的精度。     

Vision-based tracking control of quadrotor for a moving target with nonlinear angular velocity observer

In this article, an automatic tracking process for unmanned aerial vehicle (UAV) system to follow the target with maneuverability is developed, and a vision-based control method is proposed. At first, the image-based visual servoing (IBVS) position control technology is applied without any prior target information for the algorithm practicability. Besides, consider the situation with unavailable angular velocity measurement, a thorough nonlinear attitude controller with an observer based on contraction is proposed. Finally, the whole UAV system stability is demonstrated to be uniformly ultimately bounded, and the bound can be arbitrarily small. Simulation and experiment results are presented to show effectiveness of the designed controller.     

基于 ESKF-MPC 的四旋翼无人机轨迹跟踪控制

四旋翼无人机的轨迹跟踪控制容易受到风扰和测量噪声的影响,针对上述问题, 提出了一种基于扩展状态卡尔曼滤波 (extended state based Kalman filter, ESKF)的模型预测控制(model predictive control, MPC)方法。 首先, 采用牛顿-欧拉方法建 立风扰影响下的四旋翼无人机动力学模型; 然后, 位置控制采用基于误差模型的 MPC 方法, 利用 ESKF 估计风扰并对控制量 进行前馈补偿; 采用反馈线性化方法将姿态动力学模型线性化, 并设计基于 ESKF-MPC 的姿态控制器;最后, 仿真结果表明测 量噪声方差为 0. 000 1 时该方法的位置跟踪均方误差比自抗扰控制方法的误差小 0. 013 m, 当方差大于 0. 000 1 时自抗扰控制 方法使得系统不稳定,而本文的方法仍可以实现较好的位置跟踪。     

基于四旋翼无人机的二次屏柜巡检系统

随着人们对于电力的需求量越来越大,相应的电力巡检的要求也越来越高。文中设计了基于四旋翼无人机的二次屏柜巡检系统。为解决无人机在室内GPS拒止问题,文中通过AprilTag算法配合传感器高度信息,实现无人机室内飞行路径规划功能、姿态矫正、自主飞行;在机载树莓派内存入任务程序,该程序将利用飞控和传感器实现对任务地点二维码的寻找和判断,并在达到指定点后执行拍摄任务;通过局域网将采集的图像传输到地面服务器,并输入到预先训练好的CNN网络模型中进行异常检测;依据识别结果判断二次屏柜是否工作正常,并将检测结果上传到显示平台。最终项目在贵州铜仁变电站室内二次屏柜现场测试成功。