LMI-based neurocontroller for state-feedback guaranteed cost control of discrete-time uncertain system

被引：0
|
作者：
Mukaidani, H [1 ]
Ishii, Y [1 ]
Bu, N [1 ]
Tanaka, Y [1 ]
Tsuji, T [1 ]
机构：
[1] Hiroshima Univ, Grad Sch Educ, Higashihiroshima 7398524, Japan
来源：
IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS | 2005年 / E88D卷 / 08期
关键词：
guaranteed cost control; additive gain perturbations; neural networks; LMI;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
The application of neural networks to the state-feedback guaranteed cost control problem of discrete-time system that has uncertainty in both state and input matrices is investigated. Based on the Linear Matrix Inequality (LMI) design, a class of a state feedback controller is newly established, and sufficient conditions for the existence of guaranteed cost controller are derived. The novel contribution is that the neurocontroller is substituted for the additive gain perturbations. It is newly shown that although the neurocontroller is included in the discrete-time uncertain system, the robust stability for the closed-loop system and the reduction of the cost are attained.
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页码：1903 / 1911
页数：9
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