标题： 无约束输入下未知欧拉-拉格朗日系统的无近似控制 显示英文标题

标题： Approximation-free Control of Unknown Euler-Lagrangian Systems under Input Constraints

摘要： 在本文中，我们为具有未知动态和规定输入约束的机器人系统提出了一种新颖的基于漏斗的跟踪控制算法。 采用欧拉-拉格朗日公式，这是机器人系统的一种常见建模方法，在本研究中用于解决性能与执行器安全之间的权衡。 我们建立了可行性条件，以确保跟踪误差在预定义的漏斗边界内演变，同时保持受控努力的有界性，这对于具有有限致动能力的机器人来说是一个关键考虑因素。 我们提出了两种无需近似的控制策略，用于这些条件被违反的情况：一种主动校正误差，另一种阻止进一步偏离。 最后，我们通过仿真和实验验证展示了该方法的鲁棒性能和安全性。 这项工作代表了基于漏斗控制的重要进展，增强了其在具有输入约束的实际机器人系统中的适用性。 显示英文摘要

摘要： In this paper, we present a novel funnel-based tracking control algorithm for robotic systems with unknown dynamics and prescribed input constraints. The Euler-Lagrange formulation, a common modeling approach for robotic systems, has been adopted in this study to address the trade-off between performance and actuator safety. We establish feasibility conditions that ensure tracking errors evolve within predefined funnel bounds while maintaining bounded control efforts, a crucial consideration for robots with limited actuation capabilities. We propose two approximation-free control strategies for scenarios where these conditions are violated: one actively corrects the error, and the other stops further deviation. Finally, we demonstrate the robust performance and safety of the approach through simulations and experimental validations. This work represents a significant advancement in funnel-based control, enhancing its applicability to real-world robotics systems with input constraints.