Gaussian process model-based predictive control method for multi-variable nonlinear dynamic system model

A Gaussian process model, nonlinear dynamic technology, applied in adaptive control, general control system, control/regulation system, etc., can solve the problems of complex controller design, increased controller calculation, complex training process, etc. Improved nonlinear processing capability, time-saving control problems, and easy parameter optimization
CN110609476AActive Publication Date: 2019-12-24TAIYUAN UNIV OF TECH
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
TAIYUAN UNIV OF TECH
Publication Date
2019-12-24

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Abstract

The invention discloses a Gaussian process model-based predictive control method for a multi-variable nonlinear dynamic system model, belongs to the technical field of predictive control of the multi-variable nonlinear dynamic system model and aims at solving the technical problem of providing improvement of the Gaussian process model-based predictive control method for the multi-variable nonlinear dynamic system model. The technical scheme adopted for solving the technical problem is as follows: the predictive control method comprises the following steps of (1) building an external dynamic PLS framework; (2) predicting output data and obtaining a plurality of single-input and single-output systems in hidden space through decoupling of a dynamic GP-PLS model; (3) carrying out control by using the dynamic GP-PLS model and designing a model predictive controller in each single-input and single-output system; (4) obtaining an optimum control action through minimizing an objective function; and (5) reconstructing the model predictive control result in the hidden space back to original space and controlling the original space. The Gaussian process model-based predictive control method is applied to the multi-variable nonlinear dynamic system model.
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Description

technical field

[0001] The invention discloses a multivariable nonlinear dynamic system model predictive control method based on a Gaussian process model, and belongs to the technical field of predictive control of multivariable nonlinear dynamic system models. Background technique

[0002] With the rapid development of industry and information science and technology, the scale of industrial production is getting larger and larger, and the production process and production process are becoming more and more complex, which poses a major challenge to traditional mechanism modeling and control strategies, especially in Petroleum, chemical, metallurgy, machinery and other industries for application. Model Predictive Control (MPC), as an advanced computer control algorithm, estimates and calculates the system's future state optimization sequence based on the current and past operating states of the system. The first input value of the optimization sequence is used on the system. ...

Claims

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