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Stability monitoring method for closed-loop system driven by data

A closed-loop system, data-driven technology, applied in the direction of electrical digital data processing, special data processing applications, instruments, etc., can solve the lack of closed-loop system stability monitoring and other problems

Active Publication Date: 2018-11-23
HARBIN INST OF TECH
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] In order to solve the problem of lack of data-driven closed-loop system stability monitoring in the prior art, the present invention provides a data-driven closed-loop system stability monitoring method

Method used

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  • Stability monitoring method for closed-loop system driven by data
  • Stability monitoring method for closed-loop system driven by data
  • Stability monitoring method for closed-loop system driven by data

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Experimental program
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specific Embodiment approach 1

[0060] Specific implementation mode one: combine figure 1 , figure 2 To describe this embodiment, a data-driven closed-loop system stability monitoring method provided in this embodiment specifically includes the following steps:

[0061] Step 1. Collect the closed-loop data of the closed-loop system at a certain moment in the past, including the input signal, output signal and reference input signal of the closed-loop system;

[0062] Step 2, using the collected data to construct a Hankel matrix;

[0063]Step 3, carry out Cholesky decomposition to the constructed Hankel matrix, construct the stable image description of the system, the stable kernel description of the system, and obtain the normalized stable image description and the normalized stable kernel description;

[0064] Step 4, using the stable image description obtained in step 3 to calculate the stability margin;

[0065] Step 5. Set the monitoring threshold according to the stability margin, collect the curren...

specific Embodiment approach 2

[0067] Specific embodiment two: the difference between this embodiment and specific embodiment one is that step two specifically includes the following steps:

[0068] Step 21, using the feedback controller K(z)=(A, B, C, D) parameters in the closed-loop system to construct a stable filter Among them, A is the system matrix of the feedback controller, B is the input matrix of the feedback controller, C is the output matrix of the feedback controller, and D is the through matrix of the feedback controller;

[0069] Step 22. Calculate the filtered reference input signal w(z) by the following formula:

[0070]

[0071] Among them, ω(z) is the reference input signal;

[0072] Step two and three, select the appropriate dimension parameter s p ,s f and N, construct a Hankel matrix about the system filtered reference input signal w(z), input signal u(z), and output signal y(z):

[0073]

[0074]

[0075]

[0076]

[0077] in, w k Indicates the sampling value ...

specific Embodiment approach 3

[0079] Specific embodiment three: the difference between this embodiment and specific embodiment two is that step three specifically includes the following steps:

[0080] Step 31, do the following Cholesky decomposition to the constructed Hankel matrix:

[0081]

[0082]

[0083] in, and Represents the decomposed matrix;

[0084] Step 32. Build the stable image description of the system

[0085]

[0086] in, Describes the correspondence for the system stability image weight, Describes the correspondence for the system stability image weight;

[0087] Step 33, obtain the following left null space:

[0088]

[0089] in, corresponds to the left null space where weight, for the resulting left null space corresponding to components; build a stable core description of the system

[0090]

[0091] Step 3 and 4: Obtain the normalized stable image description and a normalized stable kernel description

[0092]

[0093]

[0094] in, ...

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Abstract

The invention provides a stability monitoring method for a closed-loop system driven by data and belongs to the technical field of data-driven error diagnosis and control. The method includes the steps of collecting closed-loop data of the closed-loop system at a certain moment in the past to construct a Hankel matrix at first; conducting Cholesky decomposition on the constructed Hankel matrix andfiguring out uniformized stable image description and uniformized stable kernel description; utilizing the stable image description obtained in step 3 to calculate a stability margin; according to the stability margin, setting a monitoring threshold value, collecting current closed-loop data of the system, and repeating the step above to obtain the current uniformized stable image description andkernel description of the system; calculating current lacunarity of the system; finally, combining the monitoring threshold value with the current lacunarity of the system to monitor the system in real time. The method solves the problem that monitoring of the stability of closed-loop systems driven by data falls short in the prior art. The method can be applied to online system error estimationand monitoring.

Description

technical field [0001] The invention belongs to the technical field of data-driven fault diagnosis and control, and in particular relates to a data-driven closed-loop system stability monitoring method. Background technique [0002] In recent years, driven by the rapid development of computer technology, electronics, information and communication technology, today's industrial systems, such as chemical production, machinery manufacturing, energy systems, etc., are becoming more and more integrated and complex while expanding in scale. come higher. In a complex industrial system, a local abnormal event may even cause the performance of the entire industrial system to decline or lead to major industrial accidents and huge economic losses. In order to improve economic efficiency and maintain industry competitiveness, the safety and reliability of modern industrial processes have become the most critical factors, and have received extensive attention from academia and industry....

Claims

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Application Information

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IPC IPC(8): G06F17/50
CPCG06F30/20
Inventor 罗浩尹珅刘天宇
Owner HARBIN INST OF TECH
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