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首页> 外文期刊>Journal of robotic systems >Mixed Kinematic and Dynamic Sideslip Angle Observer for Accurate Control of Fast Off-Road Mobile Robots
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Mixed Kinematic and Dynamic Sideslip Angle Observer for Accurate Control of Fast Off-Road Mobile Robots

机译:混合运动学和动态侧滑角观测器,可精确控制快速越野移动机器人

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摘要

Automation in outdoor applications (farming, surveillance, military activities, etc.) requires highly accurate control of mobile robots, at high speed, although they are moving on low-grip terrain. To meet such expectations, advanced control laws accounting for natural ground specificities (mainly sliding effects) must be derived. In previous work, adaptive and predictive control algorithms, based on an extended kinematic representation, have been proposed. Satisfactory experimental results have been reported (accurate to within ±10 cm, whatever the grip conditions), but at limited velocity (below 3 m·s~(-1)). Nevertheless, simulations reveal that control accuracy is decreased when vehicle speed is increased (up to 10 m·s~(-1)). In particular, oscillations are observed at curvature transition. This drawback is due to delays in sideslip angle estimation, unavoidable at high speed because only an extended kinematic representation was used. In this paper, a mixed backstepping kinematic and dynamic observer is designed to improve observation of these variables: the slow-varying data are still estimated from a kinematic representation, which is then injected into a dynamic observer to supply reactive and reliable sliding variable (namely sideslip angle) estimation, without increasing the noise level. The algorithm is evaluated via advanced simulations (coupling Adams and MatLab software) investigating highspeed capabilities. Actual experiments at lower speed (experimental platform maximum velocity) demonstrate the benefits of the proposed approach.
机译:户外应用(耕作,监视,军事活动等)中的自动化要求对移动机器人进行高速,高精度的控制,尽管它们在低抓地力的地面上移动。为了达到这样的期望,必须得出解释自然地面特异性(主要是滑动效应)的先进控制法。在先前的工作中,已经提出了基于扩展运动学表示的自适应和预测控制算法。据报道,令人满意的实验结果(精确到±10 cm以内,无论抓握条件如何),但速度有限(低于3 m·s〜(-1))。然而,仿真表明,当车速提高时(高达10 m·s〜(-1)),控制精度会降低。特别地,在曲率转变处观察到振荡。这个缺点是由于侧滑角估计的延迟,这在高速下是不可避免的,因为仅使用了扩展的运动学表示。在本文中,设计了一种混合的反步运动学和动态观测器以改善对这些变量的观测:仍然从运动学表示中估算慢速数据,然后将其注入动态观测器中以提供反应性和可靠的滑动变量(即侧滑角)估算,而不会增加噪声水平。通过研究高速功能的高级仿真(耦合Adams和MatLab软件)对算法进行评估。较低速度(实验平台最大速度)的实际实验证明了该方法的好处。

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