Multi-varible system structural colsed-loop distinguishing method based on step response test

A technology of step response and identification method, applied in the application field of multi-variable system, can solve the problems of complex identification process, difficult selection of relay signal parameters, affecting control effect, etc.
CN1487268AInactive Publication Date: 2004-04-07SHANGHAI JIAO TONG UNIV

Patent Information

Authority / Receiving Office
CN Β· China
Patent Type
Applications(China)
Current Assignee / Owner
SHANGHAI JIAO TONG UNIV
Publication Date
2004-04-07
Estimated Expiration
Not applicable Β· inactive patent

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Abstract

The present invention belongs to the field of multi-variable system application technology. Via one set of simple and practical step response test, the distinction in powerfully coupled multi-variable system is amalyzed into the distinction in several single-in single-out systems so as to obtain precise transfer function model of the multi-variable system. Specially, the process includes four steps of initialization, step response test, synthesis of multi-variable process and parameter distinction in synthesized subprocess. The present invention can realize the real-time on-line distinction of the multi-variable system, and has less impact of step test signal required for system distinction on the normal operation of the control system and no special requirement of distinction algorithm in signal amplitude. The method of the present invention is suitable for industrial process control, robot, aeronautics, astronautics and other multi-variable systems.
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Description

technical field

[0001] The invention relates to a structured closed-loop identification method for a multivariable system, in particular to a structured closed-loop identification method for a multivariable system based on a step response test, and belongs to the technical field of multivariable system applications. Background technique

[0002] The identification and control of multivariable systems has always been a difficult point in the control field due to the strong coupling relationship within the system. Traditional multivariable control methods, such as the inverse Nyquist curve method and the characteristic root locus method, require a transfer function matrix model or a frequency response matrix model of the known process in the entire operating frequency range. However, it is very difficult for the existing identification technology to obtain the above-mentioned accurate model. In order to effectively solve the coupling problem in multivariable systems, soft sen...

Claims

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