Direct Adaptive Inverse Control via Fractional Least Mean Square

被引：0
|
作者：
Noronha, Rodrigo Possidonio [1 ]
机构：
[1] Fed Inst Educ Sci & Technol Maranhao, Dept Elect Engn, Imperatriz, Brazil
来源：
PROCEEDINGS OF 2021 GLOBAL CONGRESS ON ELECTRICAL ENGINEERING (GC-ELECENG 2021) | 2021年
关键词：
Adaptive Filter; Adaptive Inverse Control; FLMS; Fractional Control; Stochastic Gradient; GRADIENT DESCENT;
D O I：
10.1109/GC-ELECENG52322.2021.9788229
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
This work aims to perform the performance analysis of the Fractional Least Mean Square (FLMS) algorithm in the Direct Adaptive Inverse Control (DAIC) design, in terms of convergence speed and steady-state Mean Square Error (MSE), for the controller weight vector. The controller, obtained through inverse identification of the plant model, is based on a Finite Impulse Response (FIR) adaptive filter. To obtain non-conservative results, the performance analysis was performed in the presence of a sinusoidal reference signal and sinusoidal disturbance signal. As an increment of complexity to the DAIC design, the plant model is non-minimum phase.
引用
收藏
页码：80 / 85
页数：6
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