Selection method for economic goal-optimized self-adaptive backoff of chemical process predictive control system

Abstract

The invention discloses a selection method for the economic goal-optimized self-adaptive backoff of a chemical process predictive control system, which comprises the following steps: determining an economic goal of an enterprise production unit, establishing a variable steady-state optimization constraint relationship of a control unit, determining production variable operating restrictions, obtaining an LQG performance index based on the relationship between control and output, adjusting weight to construct a discrete point set based on the relationship between control and output variance, fitting a nonlinear variance adjusting reference, solving an optimization proposition to determine optimal set values and optimal backoff values for control and output, and automatically refreshing thesettings of the predictive control device based on changes of production. The method can avoid the blindness of the experience set value of the enterprise production device predictive control goal, the conservatism of the manual backoff value setting and the imperfection and the infeasibility of the present MVC reference theoretical method in the physical production process, becomes a self-adaptive optimization and backoff strategy which can be practically put into service in the chemical process, raises the production yield, saves energy and reduces emission and improves economic benefits ofthe enterprise to a greater extent.

Description

technical field [0001] The invention relates to the field of economic performance optimization of process industry control systems such as petroleum and chemical industry, and in particular relates to an economic target optimization self-adaptive backoff selection method of a chemical process predictive control system. Background technique [0002] In recent years, the advanced control strategy (APC, Advanced Process Control) represented by the predictive control technology (MPC, Model Predictive Control) has been widely used in the process industries such as petroleum, chemical industry, paper making, pharmaceuticals, etc. , environmental protection, high yield, low consumption, etc. have provided important guarantees, and the economic benefits have been significantly improved. However, there are still some problems to be solved urgently in the promotion and operation of APC. On the one hand, APC needs to increase investment and maintenance costs. Whether it can provide a ...

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Problems solved by technology

At present, the target setting value of MPC in the industrial process is usually set according to experience, and there is still a lack of effective evaluation methods for whether it is optimal, and there is a large room for economic performance improvement; at the same time, uncertainties such as disturbances lead to inevitable fluctuations in process variables , in order to ensure the safety of production, the back-off value is usually manually set for the constraints of process variables. If the setting is too large, it will lead to conservatism and loss of economic benefits. Therefore, the optimal adaptive back-off mechanism according to production changes has important practical value

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