Fuzzy control method for zinc smelting and roasting process based on trend event drive

Abstract

The invention provides a fuzzy control method for a zinc smelting and roasting process based on trend event driving. By setting a temperature set value and a control period N, and according to a real-time sampling temperature value of a sensor, a temperature deviation is calculated and a temperature trend is extracted, when a working condition changes or a preset control period is reached, fuzzy control is performed in time according to the temperature trend and the temperature deviation, and the problem of difficulty in assessing the working condition and decrease of control performance of afuzzy controller caused by dynamic characteristics of a roasting process and on-site environment constraints is improved.

Description

technical field [0001] The invention relates to the technical field of fuzzy control, in particular to a trend event-driven fuzzy control method for zinc smelting and roasting process. Background technique [0002] The roasting process is the first process in the zinc smelting process. In this process, the mixed zinc concentrate is sent to the roaster for full combustion, and zinc calcine, sulfur dioxide, smoke and other products are produced. Zinc calcine is the main raw material in the zinc hydrometallurgy process, and its product quality is crucial to the production of downstream processes. The main purpose of the roasting process is to ensure the product quality of the zinc calcine, that is, to increase the soluble zinc rate of the zinc calcine and reduce the content of insoluble impurities. Since the quality of zinc calcine mainly depends on the composition of the mixed zinc concentrate and the temperature of the roasting process, the most important problem in the roas...

AI Technical Summary

Problems solved by technology

However, due to the dynamic characteristics of the roasting process and the constraints of the on-site environment, the general control period in the industrial site is selected to be more than ten minutes, which is much longer than the sampling period once per minute. Due to changes in working conditions and various disturbances in the roasting process, inaccurate or erroneous evaluation results may be obtained, resulting in a decline in the performance of the fuzzy controller; if the control cycle is shortened, due to the large It takes a while to reflect the temperature change after the feed amount is adjusted, so frequent adjustments to the feed amount will lead to instability of the roasting system, and the performance of the fuzzy controller will also decline

Therefore, there is a need for a fuzzy control method that can solve the problem of difficult evaluation of working conditions and degradation of fuzzy controller control performance due to the dynamic characteristics of the roasting process and site environmental constraints.

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