A double-inlet and double-outlet ball mill control system and control method based on rbf neural network predictive control

Abstract

An RBF neural network predictive control-based control system and control method for a double-input double-output ball mill, the control system comprising an RBF neural network model-based predictive controller, a control quantity initialization module and a controlled object, wherein the controlled object is a double-input double-output ball mill model which outputs a discrete controlled quantity generated after a continuous controlled quantity is discretized and a controlled quantity current set value, and same are inputted to the control quantity initialization module and the predictive controller; the control quantity initialization module outputs a control quantity initial value that is inputted to the predictive controller; and the predictive controller outputs a discrete control vector that is converted by a zero-order holder into a continuous control quantity and then is outputted to the double-input double-output ball mill model. The present control method uses an RBF neural network forward model and an RBF neural network inverse model to achieve predictive control of the controlled object. The described method may control and adjust the system in advance, and is suitable for the control of a large lag system. The controlled quantity has a fast response, and a small overshoot amount, and is simultaneously very robust.

Description

technical field [0001] The invention relates to thermal power engineering and an automatic control system and method, in particular to a double-inlet and double-outlet ball mill control system and control method based on RBF neural network predictive control. Background technique [0002] With the advancement of energy-saving renovation projects for thermal power units, reducing coal consumption and power consumption has become a hot research topic in the direction of energy conservation. As one of the large-scale important component systems of common power plants, the double-inlet and double-outlet ball mill pulverized coal preparation system can consume 15% to 25% of the plant's electricity consumption, and has huge energy-saving potential. Therefore, by studying the optimization of the pulverization system Controlling and improving the operating efficiency of the system is of great significance for energy-saving transformation. The double-inlet and double-outlet ball mil...

AI Technical Summary

Problems solved by technology

The double-inlet and double-outlet ball mill pulverization system is a multi-variable and large-delay time-varying nonlinear system. If the traditional PID control is used, the ideal effect cannot be achieved. Therefore, we need to explore other better control schemes.

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