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Modeling quality monitoring method and system based on model prediction controller

A technology for model prediction and quality monitoring, applied in testing/monitoring control systems, general-purpose control systems, and control/regulating systems, etc., can solve the problem of low monitoring accuracy, process model mismatch and interference model mismatch, and cannot be diagnosed. The performance of the controller deteriorates and other problems, to achieve the effect of high feasibility, small impact, and low resource consumption

Inactive Publication Date: 2017-10-20
HUAZHONG UNIV OF SCI & TECH
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Problems solved by technology

[0007] Aiming at the above defects or improvement needs of the prior art, the present invention provides a modeling quality monitoring method and system based on a model predictive controller, thereby solving the problems of the prior art that cannot diagnose the reason for the performance deterioration of the controller, and does not Process model mismatch and interference model mismatch are separated, the technical problems of inability to effectively monitor model quality, and low monitoring accuracy

Method used

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  • Modeling quality monitoring method and system based on model prediction controller
  • Modeling quality monitoring method and system based on model prediction controller
  • Modeling quality monitoring method and system based on model prediction controller

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Embodiment 1

[0108] The Wood-Berry distillation column is a typical multiple-input and multiple-output system with large pure lag; the process is as follows image 3 As shown, the output is the overhead concentration X D (s) and the bottom liquid phase concentration X B (s), controlled by the top reflux flow R(s) and the bottom reboiler steam volume S(s); the process model is:

[0109]

[0110] Among them, s represents the Laplacian operator.

[0111] The process transfer function matrix of the Wood-Berry distillation column is:

[0112]

[0113] Among them, s represents the Laplacian operator.

[0114] The process sampling time is 1min / time, and the discretized process transfer function matrix is:

[0115]

[0116] Among them, q is a mathematical operator representing discretization.

[0117] The interference model takes the following diagonal matrix:

[0118]

[0119] Utilize the improved modeling quality monitoring method based on the model predictive controller provid...

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Abstract

The invention discloses a modeling quality monitoring method and a system based on a model prediction controller. The method comprises steps: the model prediction controller is used to control operation of a closed loop control system, and process output, process input and process external excitation are acquired; tracking errors of the closed loop control system are acquired; based on the process output and the process external excitation, a mixed higher-order autoregressive model is built for orthogonal projection, and a process estimation interference updating vector is obtained; a matrix model for the process external excitation is built, and a process estimation interference updating extension vector is obtained; and a process model quality monitoring index and a whole model quality index are used to detect process model mismatch and interference model mismatch in the closed loop control system, and the modeling quality of the closed loop control system is further monitored. The method and the system have the advantages of high feasibility, few resources consumed for processing, and high monitoring result accuracy.

Description

technical field [0001] The invention belongs to the field of model predictive control, and more specifically relates to a modeling quality monitoring method and system based on a model predictive controller. Background technique [0002] Model predictive control (Model Predictive Control, MPC) is an advanced model-based control method widely used in the field of industrial process control. It has the advantages of good control effect, strong robustness, and low requirements for model accuracy. [0003] The practical application of model predictive control in industrial processes is called model predictive controller (Model Predictive Controller, MPC Controller). The MPC controller has the characteristics of simple modeling, good dynamic control effect, and strong robustness, and has good control performance in the initial stage of production; however, as time goes by, the performance of the MPC controller will gradually decline, and finally even have to be switched to tradi...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G05B23/02
CPCG05B23/0243
Inventor 郑英刘磊凌丹
Owner HUAZHONG UNIV OF SCI & TECH
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