输入约束下多旋翼飞行机器人的大范围镇定控制

发布时间：2018-07-29 10:10

【摘要】：多旋翼飞行机器人具有良好的飞行稳定性,受到了越来越多的关注.而在某些特殊应用中,如:从较大飞行器上实施空投、瞬态失稳恢复等,往往需要多旋翼飞行机器人从一个高度不稳定的非零初始状态安全、快速地切换到稳定飞行模态,这就是所谓的大范围镇定控制问题.解决该问题面临的主要困难是如何在调节过程中避免飞行机器人进入到输入饱和区,从而引起周期旋转运动,导致系统完全失控.本文针对该问题,以四旋翼飞行机器人为例,详细分析了控制输入约束形式,并对6自由度模型进行了适当简化,构建了二维平面下考虑控制输入约束的非线性动力学模型;在此基础上,基于控制Lyapunov函数概念,提出了一种改进的广义逐点最小范数控制策略,构建了输入约束下的四旋翼飞行机器人大范围镇定控制器.该方法具有明确的解析控制结构,所设计的控制器满足四旋翼飞行机器人的全部控制输入约束.仿真结果表明,对比常规的线性化控制策略,该方法能在考虑控制约束的前提下避免控制器失效,实现四旋翼飞行机器人的大范围渐进稳定.
[Abstract]:Multi-rotor flying robot has been paid more and more attention because of its good flight stability. However, in some special applications, such as aerial drop from a larger aircraft, transient instability recovery, etc., it is often necessary for a multi-rotor flying robot to switch quickly from a highly unstable non-zero initial state to a stable flight mode. This is called the problem of large-scale stabilization control. The main difficulty in solving this problem is how to avoid the flight robot entering the input saturation area in the course of adjustment, thus causing periodic rotation motion, resulting in the system completely out of control. In order to solve this problem, the control input constraint form is analyzed in detail, and the six degree of freedom model is appropriately simplified, and a nonlinear dynamic model with control input constraints in two-dimensional plane is constructed. On this basis, based on the concept of control Lyapunov function, an improved generalized point-by-point minimum norm control strategy is proposed, and a large-scale stabilization controller for a four-rotor flying robot with input constraints is constructed. The method has a clear analytical control structure, and the designed controller meets all the control input constraints of the four-rotor flying robot. The simulation results show that compared with the conventional linearization control strategy, the proposed method can avoid the failure of the controller and realize the asymptotic stability of the four-rotor flying robot on a large scale without considering the control constraints.
【作者单位】：中国科学院沈阳自动化研究所机器人学国家重点实验室;中国科学院大学;奥克兰大学机械工程学院;
【基金】：基于知识学习的多旋翼飞行机器人非零初始状态控制方法研究(61273025) 非结构环境下基于非精确信息描述的机器人自主规划方法研究(61503369)资助~~
【分类号】：TP242

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