Safe Tracking Control of an Uncertain Euler-Lagrange System with Full-State Constraints using Barrier Functions.

Iman Salehi, Ghananeel Rotithor, Daniel Trombetta, Ashwin P Dani
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引用次数: 10

Abstract

This paper presents a novel, safe tracking control design method that learns the parameters of an uncertain Euler-Lagrange (EL) system online using adaptive learning laws. A barrier function (BF) is first used to transform the full-state constrained EL-dynamics into an equivalent unconstrained dynamics. An adaptive tracking controller is then developed along with the parameter update law in the transformed state space such that the states remain bounded for all time within a prescribed bound. A stability analysis is developed that considers the EL-dynamics' uncertainty, yielding a semi-globally uniformly ultimately bounded (SGUUB) tracking error and the parameter estimation error. The controller design is validated in simulations using a two-link planar manipulator. The results show the proposed method's ability to track the reference trajectory while remaining inside each of the predefined state bounds.

具有全状态约束的不确定欧拉-拉格朗日系统的障函数安全跟踪控制。
本文提出了一种新的、安全的跟踪控制设计方法,利用自适应学习规律在线学习不确定欧拉-拉格朗日系统的参数。首先利用势垒函数(BF)将全态约束el动力学转化为等效的无约束动力学。然后,根据变换后的状态空间中的参数更新规律,设计了一种自适应跟踪控制器,使状态始终保持在规定的范围内。建立了考虑el动力学不确定性的稳定性分析,得到了半全局一致最终有界(SGUUB)跟踪误差和参数估计误差。通过双连杆平面机械臂的仿真验证了该控制器的设计。结果表明,该方法能够跟踪参考轨迹,同时保持在每个预定义的状态边界内。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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CiteScore
1.70
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