SSNN toolbox for non-linear system identification

12th European Workshop on Advanced Control and Diagnosis

Luzar, Marcel^1 ; Czajkowski, Andrzej^1

Institute of Control and Computation Engineering, University of Zielona Góra, ul. Podgórna 50, Zielona Góra

65-246, Poland^1

关键词: Identification process;    Input and outputs;    MATLAB environment;    Neural network parameters;    Neural network toolboxes;    Non-linear system identification;    Robust fault diagnosis;    State space form;   

Others  :  https://iopscience.iop.org/article/10.1088/1742-6596/659/1/012008/pdf
DOI  :  10.1088/1742-6596/659/1/012008

来源: IOP

【 摘 要 】

The aim of this paper is to develop and design a State Space Neural Network toolbox for a non-linear system identification with an artificial state-space neural networks, which can be used in a model-based robust fault diagnosis and control. Such toolbox is implemented in the MATLAB environment and it uses some of its predefined functions. It is designed in the way that any non-linear multi-input multi-output system is identified and represented in the classical state-space form. The novelty of the proposed approach is that the final result of the identification process is the state, input and output matrices, not only the neural network parameters. Moreover, the toolbox is equipped with the graphical user interface, which makes it useful for the users not familiar with the neural networks theory.