Coordination system prediction controller based on iterative learning for steam extraction heating generator set

Abstract

The invention discloses a coordination system prediction controller based on iterative learning for a steam extraction heating generator set. The deviations of electric power, main steam pressure andsteam extraction pressure are transmitted to the prediction controller by a prediction control algorithm based on iterative learning in combination with the coordination object characteristics of a heating unit. The optimized values of a boiler combustion ratio command, a main steam valve regulating command and a steam extraction valve regulating command are obtained by uniform optimization and calculation. The controller mainly consists of a prediction module, a calculation module, an execution module and a memory module, wherein the prediction module is used for predicting the output of eachfuture sampling moment; the calculation module is used for calculating an optimal control increment within a control range according to a set performance index; the execution module is used for applying an optimal control rule obtained through calculation to a system; and the memory module is used for storing current iteration information in order to modify the control rate at next iteration. Through the adoption of the controller, the stability and security of multivariable process control can be effectively ensured. Moreover, the algorithm process is clear; coding is convenient; and the engineering demand can be met.

Description

technical field [0001] The invention relates to a predictive controller of a coordinating system of steam extraction and heat supply generator sets based on iterative learning, which belongs to the field of thermal power engineering and automatic control. Background technique [0002] In the 1970s, Astrom and Wittenmark first proposed self-calibration control technology, which was successfully applied in paper mills. In the late 1970s, on this basis, predictive control gradually developed. Since this century, people have increasingly applied predictive control to other fields, and it can be found in transportation, civil engineering, energy, aerospace and medical treatment. The advantages of predictive control in dealing with optimization problems with constrained control make it widely used in many industries. [0003] The idea of ​​iterative learning was first proposed by Japanese scholar Uchiyama in 1978, and pioneered by Arimoto et al. in 1984. It continuously repeats...

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Problems solved by technology

[0004] As far as the field of thermal control is concerned, in the face of today's large, complex and uncertain thermal objects, the early PID control system obviously cannot meet the needs of the rapid development of the power industry.

At present, the design of thermal control systems has made some progress in all aspects, but we see that many of them are still implemented by traditional control algorithms and decoupling control methods. With the continuous development of industrial production, these control theories and Methods show increasingly apparent limitations

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