Asymptotic Tracking for Systems With Structured and Unstructured Uncertainties
Asymptotic Tracking for Systems With Structured and Unstructured Uncertainties
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DOI：
10.1109/tcst.2007.908227
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发表时间：
2006-12
影响因子：
4.8
通讯作者：
P. Patre;W. MacKunis;C. Makkar;W. Dixon
中科院分区：
文献类型：
--
作者：
P. Patre;W. MacKunis;C. Makkar;W. Dixon
具有不确定非线性动力学的系统控制一直是几十年来的主流研究领域。以前为不确定非线性系统开发的控制策略的一般趋势是，系统的不确定性越非结构化，就需要更多的控制努力（即高增益或高频反馈）来应对不确定性，从而降低系统的稳定性和性能（例如，一致最终有界稳定性）。本文简要说明了如何将基于自适应模型的前馈项（用于线性参数化不确定性）与误差符号（RISE）反馈项（用于加性有界扰动）的鲁棒积分合并，用于产生具有混合非结构化和结构化不确定性的欧拉-拉格朗日系统的渐近跟踪结果。实验结果表明，减少了控制工作量，减少了均方根跟踪误差。
The control of systems with uncertain nonlinear dynamics has been a decades-long mainstream area of focus. The general trend for previous control strategies developed for uncertain nonlinear systems is that the more unstructured the system uncertainty, the more control effort (i.e., high gain or high-frequency feedback) is required to cope with the uncertainty, and the resulting stability and performance of the system is diminished (e.g., uniformly ultimately bounded stability). This brief illustrates how the amalgamation of an adaptive model-based feedforward term (for linearly parameterized uncertainty) with a robust integral of the sign of the error (RISE) feedback term (for additive bounded disturbances) can be used to yield an asymptotic tracking result for Euler-Lagrange systems that have mixed unstructured and structured uncertainty. Experimental results are provided that illustrate a reduced root-mean-squared tracking error with reduced control effort.