Intelligent modeling, observation, and control for nonlinear systems

被引：28
|
作者：
Schröder, D [1 ]
Hintz, C [1 ]
Rau, M [1 ]
机构：
[1] Tech Univ Munich, Inst Elect Dr, D-80333 Munich, Germany
来源：
IEEE-ASME TRANSACTIONS ON MECHATRONICS | 2001年 / 6卷 / 02期
关键词：
intelligent observer; nonlinear system; recurrent neural network;
D O I：
10.1109/3516.928725
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
In this paper, we present identification methods for nonlinear mechatronic systems. First, we consider a system consisting of a known linear part and an unknown static nonlinearity, With this approach, using an intelligent observer, it is possible to identify the nonlinear characteristic and to estimate all unmeasurable system states. The identification result of the nonlinearity and the estimated system states are used to improve the controller performance. Secondly, the first approach is extended to systems where both the linear parameters and the nonlinear characteristic are unknown. This is achieved by implementing the intelligent observer as a structured recurrent neural network.
引用
收藏
页码：122 / 131
页数：10
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