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Adaptive Closed-Loop Identification and Tracking Control of an Aerial Vehicle with Unknown Inertia Parameters ?

机译:具有未知惯性参数的空中车辆的自适应闭环识别和跟踪控制参数

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In this paper, the problem of adaptive closed-loop parameter estimation and tracking control of a six degree of freedom (6-DOF) nonlinear quadrotor unmanned aerial vehicle (UAV) is studied. To manage the complexity of the problem, the system dynamics is decomposed into two subsystems, i.e. translational dynamics and rotational dynamics. A nested control architecture is adopted to develop both adaptive tracking control and parameter estimation. To stabilize the outer loop, a virtual control input is proposed using a proportional-derivative (PD) controller to track the x, y and z positions. The rotational dynamics of UAV contains unknown inertia parameters appearing in the control structure as well as in a nonlinear dynamic term. An adaptive tracking scheme is designed using the certainty equivalence principle to handle both parameter estimation and tracking control in a closed-loop. The idea behind the controller design is to cancel the nonlinear term in the inner loop by estimating the unknown system parameters. The stability of the whole closed-loop system is proved with a rigorous analytical study. Moreover, the performance of the proposed controller is verified with several numerical analyses.
机译:在本文中,研究了自适应闭环参数估计问题和六个自由度(6-DOF)非线性四轮机会无人航空车(UAV)的追踪控制。为了管理问题的复杂性,系统动态被分解为两个子系统,即翻译动态和旋转动态。采用嵌套的控制架构来开发自适应跟踪控制和参数估计。为了稳定外环,使用比例衍生(Pd)控制器提出虚拟控制输入以跟踪X,Y和Z位置。 UAV的旋转动态包含在控制结构中出现的未知惯性参数以及非线性动态术语。使用确定性等效原理设计自适应跟踪方案,以处理闭环中的参数估计和跟踪控制。控制器设计背后的想法是通过估计未知的系统参数来取消内环中的非线性术语。通过严格的分析研究证明了整个闭环系统的稳定性。此外,所提出的控制器的性能被验证有几个数值分析。

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