斜坡上两轮自平衡运输车的鲁棒控制:一种Takagi-Sugeno描述子方法

Benyamine Allouche, L. Vermeiren, A. Dequidt, M. Dambrine
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引用次数: 5

摘要

在自主机器人和智能车辆领域,一个常见的问题是:如何设计和控制一个能够调查狭窄空间的城市交通工具?从机械角度来看,两轮运输车似乎是一个很好的选择,因为它占地面积小,而且有能力在急转弯时进行操纵。然而,这种车辆的设计需要两个层次的控制:一是自动平衡。第二个保证了速度跟踪。线性控制律的使用要求在假定车辆在平面上运动的前提下,围绕一个已知的先验平衡点对模型进行线性化。现在,假设车辆沿着一个未知的斜坡行驶。那么在设计控制器时,平衡点是未知的。线性化的模型变得不具有代表性。提出了一种自平衡两轮运输车的控制方法。目的是设计一个鲁棒控制器,使运输器沿未知斜率保持自然平衡。拟LPV方法,通过所谓的TS模糊模型和LMI约束将被提出。此外,将利用机械系统的自然描述符形式来设计控制律。最后一种选择允许降低LMI条件的保守性。最后通过仿真实验验证了该方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Robust control of two-wheeled self-balanced transporter on sloping ground: A Takagi-Sugeno descriptor approach
A commonly asked question in the field of autonomous robotics and intelligent vehicles is: How to design and control an urban transporter able to investigate narrow spaces? From a mechanical point of view, a two wheeled transporter seems to be a good alternative due to its small footprint and its ability to manoeuvre on tight turns. However, the design of this vehicle requires two level of control: One, for the auto-balancing. The second ensures a velocity tracking. The use of linear control law requires a linearisation of the model around an a priori known equilibrium point under the assumption that the vehicle moves on a plane surface. Now, assume that the vehicle is moving along an unknown slope. Then, the equilibrium point is not known while designing the controller. The linearized model becomes unrepresentative. This work present a control of self-balanced two wheeled transporter. The aim is to design a robust controller able to stabilize the transporter on its natural equilibrium along an unknown slope. A quasi LPV approach, through the so-called TS fuzzy model and LMI constraints will be proposed. Moreover, The natural descriptor form of the mechanical system will be used to design the control law. This last choice allows reducing the conservatism of the LMI conditions. Finally a simulation tests showed the effectiveness of our approach.
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