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Fractional order prediction function control method for optimizing heating furnace temperature through genetic algorithm

A technology of predictive function control and genetic algorithm, applied in the field of automation, can solve the problem that the control effect is not very good

Active Publication Date: 2016-09-21
HANGZHOU DIANZI UNIV
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Problems solved by technology

For fractional-order systems, traditional PID control methods and integer-order predictive function control methods are not very effective in controlling such objects, which requires us to study controllers with good control performance to control such systems described by fractional-order models. Actual controlled object

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  • Fractional order prediction function control method for optimizing heating furnace temperature through genetic algorithm
  • Fractional order prediction function control method for optimizing heating furnace temperature through genetic algorithm
  • Fractional order prediction function control method for optimizing heating furnace temperature through genetic algorithm

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Embodiment Construction

[0075] The present invention will be further described by taking the industrial heating furnace temperature control process as an example below.

[0076] In the temperature control process of industrial heating furnace, in order to evaluate the performance of the model, the real-time data of temperature are obtained from the actual application system of industrial production.

[0077] The specific steps of the genetic algorithm optimization of the fractional order predictive function control method of the industrial heating furnace system include:

[0078] Step 1. Establish the fractional linear model of the controlled object in the actual process. The specific method is:

[0079] 1.1 Collect the real-time input and output data of the actual process object, use the data to establish the fractional differential equation model of the controlled object at time t, the form is as follows:

[0080] c 2 y ( ...

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Abstract

The invention discloses a fractional order prediction function control method for optimizing heating furnace temperature through a genetic algorithm. A fractional order system is approximated as an integer order system by adopting an Oustaloup approximation method. A prediction output model is established based on an Oustaloup approximation model, and then an integer order prediction function control method is extended to the fractional order prediction function control method. A fractional order differential operator is introduced to a target function, and the differential operator is optimized by adopting the genetic algorithm so that the more reasonable control effect can be acquired through optimization. The control performance of the system can be effectively enhanced by the method.

Description

technical field [0001] The invention belongs to the technical field of automation, and relates to a fractional-order predictive function control method for optimizing the temperature of a heating furnace by a genetic algorithm. Background technique [0002] The chemical process is an important part of my country's process industry process, and its requirement is to supply qualified industrial products to meet the needs of my country's industry. For many complex objects, integer-order differential equations cannot be used to accurately describe them. Fractional-order differential equations can more accurately describe object characteristics and evaluate product performance. Predictive Function (PFC), as one of the advanced control methods, has the characteristics of small amount of calculation, strong robustness, and good control performance, and has been successfully applied in a large number of actual process control. For fractional-order systems, traditional PID control m...

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Application Information

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IPC IPC(8): G05D23/32G05B13/04
CPCG05B13/041G05B13/048G05D23/32
Inventor 张日东张俊锋王玉中
Owner HANGZHOU DIANZI UNIV
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