Boiler drum water level control method based on fuzzy neural network PID (Proportion Integration Differentiation) control

A fuzzy neural network and boiler drum technology, which is applied in the fields of industrial automation control and process industry, can solve the difficulty of coordinated debugging of fuzzy neural network PID control strategy and control system, affect the application effect of boiler drum water level control, and update the control strategy online. The efficiency is difficult to grasp and other problems, so as to improve the communication efficiency, improve the adaptive ability, and improve the real-time performance

Active Publication Date: 2014-08-06
IAP FUJIAN TECH CO LTD
4 Cites 18 Cited by

AI-Extracted Technical Summary

Problems solved by technology

Although these methods can achieve good control results in the laboratory research stage, when they are applied to the actual industrial control system, due to the differences between the fuzzy neural network PID control and the traditional control in design, development, debugging, operation, etc. Larg...
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Abstract

The invention provides a boiler drum water level control method based on fuzzy neural network PID (Proportion Integration Differentiation) control. The method comprises the following steps: analyzing characteristics and modeling conditions of a boiler drum water level control system; modeling a control object of the boiler drum water level control system; finishing the development of components of a fuzzy neural network PID control system in configuration software; realizing control logic of the boiler drum water level control system through component configuration in the configuration software; testing the control effect on the boiler drum water level, from the fuzzy neural network PID control system in the configuration software. According to the method, the shortcomings of conventional PID control are overcome and the self-adaptability of the control system is improved; a fuzzy neural network PID control algorithm is integrated in the configuration software in a manner of components, so that the efficiency of communication between a control strategy and a control station is improved, and the real-time property of online operation of the advanced control strategy is greatly improved.

Application Domain

Water feed control

Technology Topic

Pid control algorithmControl effect +11

Image

  • Boiler drum water level control method based on fuzzy neural network PID (Proportion Integration Differentiation) control
  • Boiler drum water level control method based on fuzzy neural network PID (Proportion Integration Differentiation) control
  • Boiler drum water level control method based on fuzzy neural network PID (Proportion Integration Differentiation) control

Examples

  • Experimental program(1)

Example Embodiment

[0017] See figure 2 with image 3 As shown, the present invention is a method for boiler drum water level control based on fuzzy neural network PID control. The boiler drum water level control system involved in the method (such as figure 2 Shown) It is composed of a fuzzy neural network PID control system and a boiler drum water supply system; the method includes the following steps:
[0018] Step 1. Analyze the characteristics and modeling conditions of the boiler drum water level control system; specifically: Step 10. Obtain the control object of the boiler drum water level control system and the influencing factors of the control object. The control object is the steam drum and the control object The influencing factors include changes in water supply, combustion, steam load and steam pressure;
[0019] Step 20: Obtain the dynamic characteristics of the steam drum water level control. The dynamic characteristics include: when the feedwater flow of the boiler drum water level control system produces a step disturbance, the change of the steam drum water level is related to the steam flow generation order of the boiler drum water level control system. The change of the water level of the steam drum when the disturbance occurs;
[0020] Step 30: Determine the modeling conditions of the boiler drum water level control system according to the control object, the influencing factors of the control object, and the dynamic characteristics of the drum water level control. The modeling conditions include: dividing the boiler drum water supply system into evaporation District (such as figure 1 (Shown), the evaporation zone includes three links of downcomer, riser and steam drum; the water density of the evaporation zone is calculated according to the saturated water density; the total parameters of the three links are expressed by the system outlet value; the pressure in the evaporation zone is everywhere Same; the feedwater of the economizer of the boiler steam drum feedwater system does not contain steam and when it enters the steam drum, it does not exchange heat with the water in the steam drum, but directly enters the downcomer;
[0021] Step 2. Analyze the characteristics of the control object of the fuzzy neural network PID control system, and model the control object of the boiler drum water level control system according to the characteristics and modeling conditions obtained from the analysis of step 1;
[0022] Step 3. According to the modeling result of the control object and the fuzzy neural network PID control algorithm, the development of the components of the fuzzy neural network PID control system is completed in the configuration software; the development of the components involves the component name and icon , Input and output parameters, component control parameters, and fuzzy neural network PID control algorithm call.
[0023] Step 4. The control logic of the boiler drum water level control system is realized through the component configuration in the configuration software; the control logic of the boiler drum water level control system is combined with the conventional control components through the fuzzy neural network PID control system components State to achieve; the conventional control components include analog setter components, intermediate analog components, differential regulator components, subtractor components, drawing components;
[0024] Step 5. Test the control effect of the fuzzy neural network PID control system on the boiler drum water level in the configuration software; specifically: according to the dynamic characteristics of the drum water level control, under different control conditions, the fuzzy neural network PID control Test the control effect of the boiler drum water level, analyze the control performance indicators, and investigate the anti-disturbance ability of the boiler drum water level control system; the control conditions include no disturbance of the feedwater flow and steam flow, and the feedwater flow and steam flow separately or simultaneously Generates a step disturbance signal; the control performance index includes adjustment time, overshoot, and steady-state margin.
[0025] The boiler drum water level control system uses a fuzzy neural network PID controller. The fuzzy neural network PID control system takes the deviation value e of the drum water level and the deviation value ec as input, and its output terminal is connected to the boiler drum water supply system Use the fuzzy neural network to construct a fuzzy neural network system so that fuzzy rules can be extracted and optimized online; the fuzzy neural network system is composed of an input layer, a fuzzification layer, a fuzzy inference layer, a rule calculation layer, and an output layer connected in sequence; The principle of the PID controller is to derive the formula of the dynamic model of the fuzzy neural network system, and obtain the three basic parameters corresponding to the PID controller, namely the gain coefficient, the integral time coefficient and the derivative time coefficient; through the adjustment of these three parameters , Can realize the fuzzy neural network to optimize the PID parameters; and realize the control of the boiler drum water level through the PID controller.
[0026] Wherein, the control strategy of the fuzzy neural network PID control can be edited and realized in the configuration software, and the control strategy can be directly run in the control station of the boiler drum water level control system to improve the execution efficiency of the control method. The intermediate calculation process of the control strategy of the fuzzy neural network PID control can be monitored in a graphical manner, and online debugging can be carried out according to different situations.
[0027] In short, the method for controlling the boiler drum water level based on the fuzzy neural network PID control of the present invention is suitable for the simulation control system of the drum water level, and can also be popularized and applied to the actual control system of the drum water level. The control strategy of the fuzzy neural network PID control provided by the present invention can be directly edited and realized in the configuration software. The execution of the control strategy can be downloaded to the control station through the communication interface of the configuration software for execution. The execution of the advanced control strategy of the steam drum water level and The efficiency of updating has been effectively improved.
[0028] The foregoing descriptions are only preferred embodiments of the present invention, and all equivalent changes and modifications made in accordance with the scope of the patent application of the present invention shall fall within the scope of the present invention.
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