Heating furnace temperature computer control method based on process neural network

Abstract

The invention discloses a heating furnace temperature computer control method based on a process neural network. The computer control method includes the steps: 1 building a heating furnace temperature forecasting model based on the process neural network: (1) acquiring and fitting data; (2) forecasting a temperature value of a heating furnace by a three-layer process neural network forecasting model; (3) performing learning and training by a gradient descent method until an error function is smaller than 0.5, and stopping training; 2 subtracting the temperature value of the (k+1) heatingfurnace forecasted by the three-layer process neural network forecasting model in the step 1 from a given temperature value to obtain temperature deviation, adjusting the temperature deviation by a PID (proportion integration differentiation) controller to control a temperature adjuster in the heating furnace, adjusting the actual temperature value of the (k+1) heating furnace in the heating furnace and enabling the deviation between the actual temperature value and the given temperature value not to exceed + / -1 DEG C. The temperature of the heating furnace can be stably controlled in thethermostatic process, so that the deviation between the internal temperature value and the given temperature value does not exceed + / -1 DEG C.

Description

technical field [0001] The present invention relates to the computer field, and more specifically, the present invention relates to a computer control method for heating furnace temperature based on process neural network. Background technique [0002] The process neural network is an extension of the traditional artificial neural network in the time domain, and its input and corresponding connection weights can be time-varying functions. Because of its nonlinear time-varying mapping capability, process neural networks do not require special modeling in advance when used in problem solving, and can fully reflect the time-cumulative effects that actually exist in time-varying systems, and are suitable for complex nonlinear process modeling. [0003] Multi-temperature zone electric heating furnaces are widely used in many fields of scientific research and production practice. Temperature control plays a pivotal role in metallurgy, chemical industry, machinery, materials and ot...

AI Technical Summary

Problems solved by technology

In the modern complex industrial production process, the strong coupling, time-varying, large delay, large inertia, nonlinear and other characteristics common to thermal objects increase the difficulty of the design of the automatic control system, so the process of heating and constant temperature of the heating furnace is accurate. It is difficult to establish a mathematical model. At present, the heating furnace adopts the traditional control method, but the model of the constant temperature process has not been established, which cannot ensure the stable control of the temperature of the constant temperature process.

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