论文标题
半PE条件下的指数稳定自适应控制
Exponentially Stable Adaptive Control Under Semi-PE Condition
论文作者
论文摘要
提出了一种新颖的稳定自适应控制方法，以补偿具有分段稳定级别和nullspace的回归剂的轻度兴奋（S-PE）的轻度条件下匹配的参数不确定性。 It is based on the generalized dynamic regressor extension and mixing procedure developed earlier by the authors, does not require high adaptive gain or data stacks and ensures: 1) exponential convergence of the tracking error to zero and the parameter one to a bounded set when the regressor is s-PE, 2) adjustable parameters transients of first-order type (each scalar parameter is adjusted using a separate first-order scalar differential equation), 3)更改不确定性参数值的警觉性，4）当回归器不是S-PE时，所有信号的界限。所提出的方法的主要显着特征是，当控制器参数估计到与真实的值无法区分的值时，可以保证指数稳定性。数值实验的结果充分支持了理论分析，并证明了该方法的优势。
A novel method of exponentially stable adaptive control to compensate for matched parametric uncertainty under a mild condition of semi-persistent excitation (s-PE) of a regressor with piecewise-constant rank and nullspace is proposed. It is based on the generalized dynamic regressor extension and mixing procedure developed earlier by the authors, does not require high adaptive gain or data stacks and ensures: 1) exponential convergence of the tracking error to zero and the parameter one to a bounded set when the regressor is s-PE, 2) adjustable parameters transients of first-order type (each scalar parameter is adjusted using a separate first-order scalar differential equation), 3) alertness to change of the uncertainty parameters values, and 4) boundedness of all signals when the regressor is not s-PE. The main salient feature of the proposed approach is that the exponential stability is guaranteed when the controller parameters estimates converge to the values that are indistinguishable from the true ones. The results of numerical experiments fully support the theoretical analysis and demonstrate the advantages of the proposed method.
