On the convergence of the self-tuning algorithms based on nonmodified least-squares

Radenkovic M.S.

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On the convergence of the self-tuning algorithms based on nonmodified least-squares

机译：基于非修正最小二乘的自整定算法的收敛性

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Self-tuning servo control based on a nonmodified least-squares algorithm is considered. The fundamental result of the analysis is that the passivity of the two time-varying operators depending on the noise process dynamics, regression vector, and the ponderation matrix sequence of the algorithm is essential for the global stability of the self-tuning regulator. The methodology can be applied to problems of adaptive prediction based on a nonmodified least-squares algorithm and system parameter identification by a least-squares algorithm with a priori prediction.

机译：考虑了基于非修正最小二乘算法的自整定伺服控制。分析的基本结果是，两个时变算子的无源性取决于噪声过程动力学，回归矢量和算法的考虑矩阵序列，对于自整定调节器的整体稳定性至关重要。该方法可以应用于基于未修改的最小二乘算法的自适应预测问题以及通过具有先验预测的最小二乘算法进行的系统参数识别。

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《IEEE Transactions on Automatic Control》 |1990年第5期|P.628-633|共6页
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Radenkovic M.S.;
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正文语种 eng
中图分类自动化系统;
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1. On the convergence of self-tuning stochastic servo algorithms based on stochastic approximation [J] . Stankovic S.S., Radenkovic M.S. IEEE Transactions on Automatic Control . 1989,第11期

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On the convergence of the self-tuning algorithms based on nonmodified least-squares

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