Temperature control method

Abstract

The invention provides a temperature control method. The method comprises the following steps of (1) controlling a system model G(s) to define e and e& to be the deviation and the deviation change rate between a temperature preset value and an actual measurement value respectively through a first-order inertia hysteresis link having the interference and parameter uncertainty; (2) identifying modelparameters by adopting the relay feedback method, and obtaining a PID (proportion integration differentiation) initial value of the fuzzy PID based on a Z-N formula method; (3) based on an optimizedfuzzy rule, conducting the self-adaptive adjustment on PID parameters on the basis of the initial value according to the deviation e and the deviation change rate e&; and (4) determining a quantization factor of the fuzzy PID according to the variable-theory domain thought. According to the invention, the optimal temperature control performance is realized.

Description

technical field [0001] The invention relates to the field of temperature controllers, in particular to a temperature control method. Background technique [0002] Temperature is one of the basic parameters in the industrial production process, because the measurement and control effect of temperature is often closely related to various technical and economic indicators such as production efficiency, production safety, and energy management. As temperature measurement controllers are widely used in industrial environments, the requirements for temperature control accuracy, stability, and reliability are getting higher and higher. As the core technology of the temperature measurement controller, the temperature control algorithm has received great attention from scholars. Since the traditional single PID (proportion, integral, derivative) algorithm can no longer meet the control requirements, various The parameter self-tuning PID algorithm was born. The self-tuning PID algor...

AI Technical Summary

Problems solved by technology

As the core technology of the temperature measurement controller, the temperature control algorithm has received great attention from scholars. Since the traditional single PID (proportion, integral, derivative) algorithm can no longer meet the control requirements, various Parameter self-tuning PID algorithm was born

The self-tuning PID algorithm based on model parameter identification has been widely used in industry, but its parameter tuning effect depends heavily on the system model and is easily disturbed by environmental changes, so it is difficult to achieve high control accuracy

In engineering practice of self-tuning PID based on fuzzy algorithm, the initial value of PID has a great influence on its control performance, and fuzzy rules and quantization factors also have certain restrictions on its parameter tuning effect

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