Nonlinear delay dynamic system model intelligent identification method

A dynamic system model, nonlinear dynamic technology, applied in general control systems, control/regulation systems, instruments, etc., can solve the problems of instability, fluctuations in the model switching process, and high complexity of local linear model identification
CN107526294AActive Publication Date: 2017-12-29XIAN ESWIN MATERIAL TECH CO LTD +1
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Patent Information

Authority / Receiving Office
CN ยท China
Current Assignee / Owner
XIAN ESWIN MATERIAL TECH CO LTD
Publication Date
2017-12-29

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Abstract

The present invention discloses a nonlinear delay dynamic system model intelligent identification method. The method includes the following steps that: an NARX neural network model difference equation is assumed; nonlinear dynamic system delay in a set NARX neural network model is determined; the input and output order of a nonlinear dynamic system is determined; the number of hidden layer neurons of a three-layer single-output NARX neural network is determined; a three-layer NARX neural network model is determined; and finally, the validity of the three-layer NARX neural network model is verified, if the validity of the three-layer NARX neural network model is successfully verified, the method terminates, otherwise, the input and output order of the three-layer NARX neural network model is adjusted. With the method of the invention adopted, the problems of high complexity and instability which is caused by severe fluctuation of the switching process of a plurality of local linear identification methods of an existing nonlinear delay dynamic system identification method which adopts the plurality of local linear identification methods to perform identification can be solved.
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Description

technical field

[0001] The invention belongs to the technical field of nonlinear dynamic system identification methods, and in particular relates to a nonlinear time-delay dynamic system model identification method. Background technique

[0002] Nonlinear time-delay dynamic systems are widely used in process control, model prediction and other fields. In these fields, sampling signals such as temperature, pressure, and flow of industrial sites are acquired and stored in real time by sensors. Based on a large amount of field sampling data, constructing a nonlinear dynamic model of an industrial process can improve the decision-making ability of the process.

[0003] The traditional nonlinear time-delay dynamic system identification method usually obtains the time-delay of the system, and uses the local linearization method to obtain the local linear model of the controlled object or a certain working point in the production process. Although the local model is widely used i...

Claims

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