Adaptive State-Space Neuro-Fuzzy Control

被引：0

作者：

Gil, Paulo ^{[1
,2
,3
]}

Oliveira, Tiago ^{[2
]}

Cardoso, Alberto ^{[3
]}

Palma, Luis ^{[1
,2
]}

机构：

[1] CTS UNINOVA, Monte De Caparica, Portugal

[2] Univ Nova Lisboa, Dept Elect Engn, Fac Sci & Technol, Campus Caparica, Lisbon, Portugal

[3] Univ Coimbra, CISUC, Coimbra, Portugal

来源：

2018 15TH INTERNATIONAL CONFERENCE ON ELECTRICAL ENGINEERING/ELECTRONICS, COMPUTER, TELECOMMUNICATIONS AND INFORMATION TECHNOLOGY (ECTI-CON) | 2018年

关键词：

UNSCENTED KALMAN FILTER;

D O I：

暂无

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

This paper proposes a new general adaptive state-space Neuro-Fuzzy control framework. It combines a eight-layered neuro-fuzzy architecture with a state feedback quadratic stabilising controller. Both the model and controller are updated online within a constrained unscented Kalman filter. Results from a benchmark Multi-Input and Multi-Output system demonstrate the effectiveness of the proposed approach.

引用

页码：45 / 48

页数：4

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