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
收藏
页码：45 / 48
页数：4
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