Backstepping-Sliding mode Control Performance Enhancement using Close Loop Identification for Quadrotor Trajectory Tracking

A. Parsa, A. Kalhor, M. A. Atashgah
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引用次数: 2

Abstract

In this paper, using both linear and nonlinear identification methods based on iterative and recursive least-square, the performance of a backstepping-sliding mode control system of a quadrotor in the presence of uncertainties is improved. At first, the dynamic model of a quadrotor is introduced and descriptive equations are presented in an appropriate state-space in order to design a controller based on backstepping method. Then the backstepping-sliding mode controller is designed using virtual controller for trajectory tracking. In this control system, the control performance is not satisfied because of the physical uncertainties existed in quadrotor. Consequently, an online identification method is introduced and used to improve the performance of the controller. In this regard, some parameters, which are linear in the model structure, are identified by least square error technique and iterative least square method is used for identifying other parameters. The results indicate that the steady-state error is decreased and the ability of tracking of a desired trajectory in the presence of uncertainties is increased. Furthermore, the result demonstrate the stabilization of roll and pitch angles, while, the method prevents the vibration of control forces.
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基于闭环辨识的四旋翼飞行器反步滑模控制性能增强
本文采用基于迭代和递推最小二乘的线性和非线性辨识方法,改进了存在不确定性的四旋翼反步滑模控制系统的性能。首先介绍了四旋翼飞行器的动力学模型,在适当的状态空间中建立了描述方程,从而设计了基于反步法的控制器。然后利用虚拟控制器设计了反步滑模控制器进行轨迹跟踪。在该控制系统中,由于四旋翼机存在物理不确定性,导致控制性能不理想。因此,引入了一种在线辨识方法,并用于改进控制器的性能。对于模型结构中线性的部分参数,采用最小二乘误差技术进行辨识,其他参数采用迭代最小二乘方法进行辨识。结果表明,该方法减小了系统的稳态误差,提高了系统在存在不确定性的情况下对目标轨迹的跟踪能力。结果表明,该方法具有一定的横摇角和俯仰角的稳定性,同时防止了控制力的振动。
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