Adaptive backstepping control for a two-wheeled autonomous robot
Adaptive backstepping control for a two-wheeled autonomous robot
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发表时间：
2009-11
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通讯作者：
T. Nomura;Y. Kitsuka;H. Suemitsu;T. Matsuo
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作者：
T. Nomura;Y. Kitsuka;H. Suemitsu;T. Matsuo
本文以ZMP公司的两轮倒立摆式自主机器人--e-nuvo-wheel为研究对象，进行了反步控制设计。[5]的文件。首先，我们推导出一个二阶运动方程的角度和设计一个自适应积分反推控制器，以稳定的角度在[1，3]建模的方式。该控制器需要全状态测量。在输出反馈的情况下，需要K滤波器或观测器反推[7，8]。然而，控制器的结构变得复杂。我们提出了基于自适应更新律的非基于模型的微分器。由于非基于模型的微分器不需要信号的动态结构的知识，我们可以使用它作为未知的非线性系统的速度估计器。接下来，我们用非基于模型的微分器的估计来代替速度测量。最后，所提出的控制器的仿真和实验结果。
In this paper, we deal with the backstepping control design of the two-wheeled inverted-pendulum-type autonomous robot, the e-nuvo-wheel, made in ZMP Inc. [5]. First, we derive a second-order motion equation of the angle and design an adaptive integral backstepping controller to stabilize the angle in the manner of the modeling in [1, 3]. This controller requires the full-state measurements. In the output feedback case, the K filter or the observer backstepping is needed [7, 8]. However, the structure of the controller becomes complicated. We have presented the non-model-based differentiator based on the adaptive update law citewada. Since the non-model-based differentiator does not need the knowledge of the dynamic structure of the signal, we can use it as a velocity estimator for unknown nonlinear systems. Next, we replace the velocity measurement with the estimates by the non-model-based differentiator. Finally, simulation and experimental results for the proposed controller are presented.