Abstract This paper presents a computation efficient Immersion and Invariance (I&I) adaptive control method for the tracking control problem of Euler–Lagrange mechanical systems with parametric uncertainties. By employing a generalized velocity observer, the proposed controller retains the basic advantages of the I&I design and requires much less extension on extra closed-loop system states when compared with the frequently used filter-based I&I adaptive control method, and the initial value constraint in the filer-based I&I to achieve “parameter lock” is also removed. Compared with the existing dynamic-scaling-based I&I adaptive control methods, the requirement of the priori knowledge on the exact bounds of unknown parameters is avoided. In addition, the dynamic gains in the proposed control method have linear relationship with the scaling factor instead of quadric, which could reduce the growth speed of the dynamic gains and avoid possible closed-loop performance degradation.

中文翻译：

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具有参数不确定性的欧拉-拉格朗日机械系统的无惯性计算高效浸入和不变性自适应跟踪控制

摘要 本文针对具有参数不确定性的欧拉-拉格朗日机械系统的跟踪控制问题，提出了一种计算效率高的沉浸和不变性（I&I）自适应控制方法。通过采用广义速度观测器，与常用的基于滤波器的 I&I 自适应控制方法相比，所提出的控制器保留了 I&I 设计的基本优点，并且需要更少的额外闭环系统状态扩展，以及初始值约束用于实现“参数锁定”的基于文件管理器的 I&I 也被删除。与现有的基于动态标度的 I&I 自适应控制方法相比，避免了对未知参数精确界限的先验知识的要求。此外，