Time series prediction and intelligent control combined online parameter adjustment method and system

Abstract

The invention discloses a time series prediction-based wavelet neural network online PID adjustment method and a system using the same. The method specifically comprises the steps of initiating the parameters, computing the control parameters and rectifying the online adjustment parameters, computing the control amount, computing or acquiring the system output and computing the prediction result; the system specifically comprises a control decision device, an online adjuster, a control executer, a controlled object, an online predictor, a control perturbation source and a prediction perturbation source; the control decision device is used for realizing the parameter initiation; the online adjuster is used for computing the control parameters and rectifying the online adjustment algorithm parameters; the control executer is used for computing the control amount; the online predictor is used for computing the prediction result; and the control decision device is also used for judging whether the algorithm is finished. According to the method, the wavelet neural network and the classic control method are combined to solve the problem of dependence on the parameter configuration work before the system operates in the control field, so that the control system has the effects of prediction, learning, online parameter optimization and self-adaptation.

Description

[0001] technical field [0002] The invention proposes a parameter online setting method combining time series prediction and intelligent control and a system using the method, which can be applied to fields such as control and intelligent control, artificial intelligence and auxiliary decision-making. Background technique [0003] So far, the characteristics of the control methods of control science research are: (1) the control method of the control system is composed of the control algorithm and the control parameters; (2) the control algorithm is described by certain rules (models, formulas); (3) the control There are two forms of parameter configuration and tuning methods: (3.1) The control parameters are initially configured, initially tuned and finally tuned before the formal operation of the control system. After the formal operation, the control parameters are fixed, such as proportional differential integral control method, fuzzy control methods, etc.; (3.2) Control ...

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Problems solved by technology

The problem with this method is that it cannot deal with the three types of characteristics of the controlled object like the classical proportional differential integral control

[0010] The characteristic of the predictive control method is that the adjustment basis of the control parameters increases the prediction of the results after the control is implemented, so the control has the advanced nature; but the problem of this method is that it cannot deal with the three types of controlled objects like the classical proportional differential integral control. In addition to the characteristics, there is also the problem of the dependence of the method on the model of the controlled object. If the prediction model is inaccurate, it will lead to inaccurate prediction results. The prediction method is based on the mathematical model of the controlled object, and the accuracy and reliability of the prediction results are lacking. Assure;

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