Data-driven gradient descent direct adaptive control for discrete-time nonlinear SISO systems

被引：0

作者：

Faculty of Electrical Engineering, University of Banja Luka, Banja Luka, Bosnia and Herzegovina ^{[1
]}

机构：

[1] Faculty of Electrical Engineering, University of Banja Luka, Banja Luka

来源：

Electron. | / 1卷 / 39-45期

关键词：

Data-driven controller; Direct adaptive control; Discrete time; Gradient descent algorithms; Nonlinear SISO systems;

D O I：

10.7251/ELS1418039K

中图分类号：

学科分类号：

摘要：

A novel data-driven gradient descent (GD) adaptive controller, for discrete-time single-input and single output (SISO) systems, is presented. The controller operates as the least mean squares (LMS) algorithm, applied to a nonlinear system with feedback. Normalization of the learning rate parameter provides robustness of the overall system to modeling errors and environment nonstationarity. Convergence analysis reveals that the controller forces tracking error to zero, with bounded control signal and the controller weights. The experiments on the benchmark systems support the analysis.

引用

页码：39 / 45

页数：6

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