Thermal power plant circulating fluidized bed boiler bed temperature control method based on fuzzy control

Abstract

The invention discloses a thermal power plant circulating fluidized bed boiler bed temperature control method based on fuzzy control, and the method comprises the steps: carrying out the modeling of a boiler bed temperature control system, and designing a fuzzy PID controller based on the modeling data of the boiler bed temperature control system; performing a simulation test on the modeled boiler bed temperature control system by using Matlab software, and adjusting and optimizing parameters of a fuzzy PID controller according to a simulation test result; a command'fuzzy 'is input to activate the adjusted and optimized fuzzy PID controller, and a Mamdani type fuzzy PID controller is generated; the modeling data of the boiler bed temperature control system are input into a Mamdani type fuzzy PID controller, an actual control instruction is generated, the actual control instruction is output to a controlled object, and fuzzy PID control over the controlled object is achieved. According to the thermal power plant circulating fluidized bed boiler bed temperature control method, the fuzzy PID controller with the self-adaptive parameter adjusting function is adopted, parameters of the fuzzy PID controller can be automatically optimized, and therefore more accurate control over the thermal power plant circulating fluidized bed boiler bed temperature is achieved.

Description

Technical Field

[0001] The invention relates to the technical field of boiler bed temperature control system in thermal power plants, and in particular to a fuzzy control-based bed temperature control method for circulating fluidized bed boilers in thermal power plants. Background Art

[0002] In recent years, due to the different operating modes of circulating fluidized bed coal-fired boilers in commercial operation, their structure, bed temperature control methods and complexity have also changed accordingly. Many of these boilers operating overseas or in large domestic ones are equipped with external heat exchangers. This type of circulating fluidized bed coal-fired boiler design makes bed temperature control relatively easy, and the bed temperature can be regulated by simply adjusting the heat input of the external heat exchanger. In the common circulating fluidized bed coal-fired boilers in China, additional external heat exchangers are usually not equipped, but high-temperature cyclone separators that are adiabatic or steam-cooled are used. The furnace wall of the boiler is water-cooled, and the high heat load area at the bottom is covered with high-temperature anti-wear materials. A superheater is set at the top of the furnace. This boiler design is simple and efficient, but the operation of controlling the bed temperature is relatively complicated because the heat of the external heat exchanger cannot be adjusted to control the bed temperature.

[0003] At present, in China, boiler management mainly relies on manual operation and switch control. Manual control relies on the operator to control based on his long-term operating experience, which is often difficult to improve control accuracy or reduce costs. Switch control operates according to the set temperature standard: set an upper and lower temperature limit. If the actual temperature exceeds this range, the boiler will start heating; if it is within this range, it will stop heating. Both methods have major problems, so a more suitable control method should be adopted. Summary of the invention

[0004] The purpose of this application is to provide a bed temperature control method for a circulating fluidized bed boiler in a thermal power plant based on fuzzy control in order to address the technical defects existing in the prior art.

[0005] The technical solution adopted to achieve the purpose of this application is:

[0006] A method for controlling the bed temperature of a circulating fluidized bed boiler in a thermal power plant based on fuzzy control. The boiler bed temperature control system includes a fuzzy PID controller, an actuator, a controlled object and a detection device.

[0007] The detection device is connected to the controlled object, and is used to monitor the state of the controlled object in real time, and convert the state of the controlled object into an electronic signal; the detection device is connected to the fuzzy PID controller through an input interface, and is used to input the electronic signal into the fuzzy PID controller, and convert the electronic signal into an analog signal through the fuzzy PID controller; the fuzzy PID controller is connected to the execution structure through an output interface, and is used to convert the analog signal into an actual control instruction; the execution structure is connected to the controlled object, and is used to control and adjust the controlled object according to the actual control instruction;

[0008] The method for controlling the bed temperature of a circulating fluidized bed boiler in a thermal power plant comprises the following steps:

[0009] Step 1, modeling the boiler bed temperature control system, and designing a fuzzy PID controller based on the modeling data of the boiler bed temperature control system;

[0010] Step 2, using Matlab software to simulate and test the boiler bed temperature control system modeled in step 1, and optimizing the parameters of the fuzzy PID controller in step 1 according to the simulation test results;

[0011] Step 3, enter the command "fuzzy" to activate the fuzzy PID controller tuned in step 2 and generate a Mamdani type fuzzy PID controller;

[0012] Step 4: input the modeling data of the boiler bed temperature control system into a Mamdani type fuzzy PID controller to generate actual control instructions, and output the actual control instructions to the controlled object to realize fuzzy PID control of the controlled object.

[0013] In the above technical solution, the modeling of the boiler bed temperature control system includes collecting actual operation data and analyzing the dynamic characteristics and nonlinear characteristics of the boiler bed temperature control system.

[0014] In the above technical solution, the tuning of the parameters of the fuzzy PID controller in step 1 according to the simulation test results includes:

[0015] The parameters of the fuzzy PID controller are fuzzily associated with the error E and the error change rate EC, and the values ​​of the error E and the error change rate E are monitored in real time. The parameters of the fuzzy PID controller are adjusted according to the values ​​of the error E and the error change rate E.

[0016] In the above technical solution, the fuzzy PID controller includes three parts: fuzzification, rule base design and defuzzification. The fuzzification includes modeling data as input data and converting the input data into fuzzy sets; the rule base design includes defining corresponding mapping rules between fuzzy sets; the defuzzification includes converting the fuzzy sets output by fuzzification into actual control instructions, and using the actual control instructions as the input of the control object.

[0017] The beneficial effects of the present invention are as follows:

[0018] The bed temperature control method of a circulating fluidized bed boiler in a thermal power plant of the present invention has a fuzzy PID controller with an adaptive parameter adjustment function, which can automatically optimize the parameters of the fuzzy PID controller, thereby achieving more accurate control of the bed temperature of the circulating fluidized bed boiler in a thermal power plant. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the technical solutions in the present application or the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0020] Figure 1 The present invention is a composition principle diagram of a bed temperature control system for a circulating fluidized bed boiler in a thermal power plant.

[0021] Figure 2 It is the structural diagram of the fuzzy controller of the present invention.

[0022] Figure 3 This is a waveform comparison diagram between the fuzzy PID controller of the present invention and the traditional PID controller. DETAILED DESCRIPTION

[0023] In order to enable those skilled in the art to better understand the technical solution of the present invention, the technical solution of the present invention is further described below in conjunction with specific embodiments.

[0024] A bed temperature control system for circulating fluidized bed boilers in thermal power plants based on fuzzy control, see Figure 1 , including a fuzzy PID controller, an actuator, a controlled object and a detection device.

[0025] The detection device is connected to the controlled object (boiler) and is used to monitor the state of the controlled object in real time and convert the state of the controlled object into an electronic signal; the detection device is connected to the fuzzy PID controller through an input interface and is used to input the electronic signal into the fuzzy PID controller and convert the electronic signal into an analog signal through the fuzzy PID controller; the fuzzy PID controller is connected to the execution structure through an output interface and is used to convert the analog signal into an actual control instruction; the execution structure is connected to the controlled object and is used to control and adjust the controlled object according to the actual control instruction.

[0026] The actuator includes a DC motor, an AC motor, a stepping motor or a servo motor.

[0027] See also Figure 2 The fuzzy PID controller includes a fuzzification interface, a fuzzy inference engine, a defuzzification interface and a knowledge base. The input quantity is quantified by using the fuzzification interface, and the input quantity is projected to a certain digital level (the digital level is usually a digital interval symmetrical to 0) by using the quantization function; the information in the knowledge base and the fuzzy inference engine are used to simulate the reasoning and decision-making thinking method of people, activate the corresponding control rules under certain input conditions, and give appropriate fuzzy control output; through the defuzzification interface, the fuzzy control output obtained by fuzzy reasoning is converted into accurate data.

[0028] A method for controlling the bed temperature of a circulating fluidized bed boiler in a thermal power plant based on fuzzy control, see Figure 1 , including the following steps:

[0029] Step 1: Model the boiler bed temperature control system, and design a fuzzy PID (proportional-integral-differential) controller based on the modeled data of the boiler bed temperature control system.

[0030] The modeling of the boiler bed temperature control system includes collecting actual operation data and analyzing the dynamic characteristics and nonlinear characteristics of the boiler bed temperature control system.

[0031] Step 2: Use Matlab software to simulate and test the boiler bed temperature control system modeled in step 1, and optimize the parameters of the fuzzy PID controller in step 1 according to the simulation test results.

[0032] The simulation test of the boiler bed temperature control system includes: setting different input signals (step signals) and observing the performance indicators of the boiler bed temperature control system. Figure 3The fuzzy PID controller and the traditional PID controller are connected to an oscilloscope, and the control output waveforms of the two PID controllers are compared (the yellow line represents the step signal, the red line represents the fuzzy PID controller waveform, and the blue line represents the waveform of the traditional PID controller). The stability of the boiler bed temperature control system using the fuzzy PID controller is enhanced, and the overshoot and adjustment time are reduced. The dynamic response of the boiler bed temperature control system using the fuzzy PID controller in this embodiment is smoother and faster.

[0033] The step of tuning the parameters of the fuzzy PID controller in step 1 according to the simulation test results includes:

[0034] The parameters of the fuzzy PID controller (proportional gain K o , integral gain K i and differential gain K d ) is fuzzily associated with the error E and the error change rate EC, and the values ​​of the error E and the error change rate E are monitored in real time. The parameters of the fuzzy PID controller are adjusted according to the values ​​of the error E and the error change rate E to adapt to different K values ​​corresponding to different errors E and EC. p , K i , K d need.

[0035] The tuning of the parameters of the fuzzy PID controller in step 1 may be performed by trial and error, expert experience or adaptive method. The trial and error method includes continuously trying different fuzzy PID controller parameters and summarizing parameters with better performance (stability, rapidity and accuracy) after multiple experiments; the expert experience includes communicating and consulting with experts with rich experience and knowledge in the problem field to obtain guidance and suggestions for solving the problem; the adaptive method includes adjusting the parameters of the fuzzy PID controller according to the actual operating conditions of the boiler bed temperature control system to achieve better performance and adapt to environmental changes.

[0036] Step 3: Enter the command "fuzzy" to activate the fuzzy PID controller tuned in step 2 and generate a Mamdani type fuzzy PID controller.

[0037] The fuzzy PID controller includes three parts: fuzzification, rule base design and defuzzification. The fuzzification includes modeling data as input data and converting the input data into fuzzy sets; the rule base design includes defining corresponding mapping rules between fuzzy sets; the defuzzification includes converting the fuzzy sets output by fuzzification into actual control instructions and using the actual control instructions as the input of the control object.

[0038] Step 4: input the modeling data of the boiler bed temperature control system into a Mamdani type fuzzy PID controller to generate actual control instructions, and output the actual control instructions to the controlled object to realize fuzzy PID control of the controlled object.

[0039] The above is only a preferred embodiment of the present invention. It should be pointed out that, for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principle of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A method for controlling bed temperature of circulating fluidized bed boiler in thermal power plant based on fuzzy control, characterized in that: The boiler bed temperature control system includes a fuzzy PID controller, an actuator, a controlled object and a detection device. The detection device is connected to the controlled object, and is used to monitor the state of the controlled object in real time, and convert the state of the controlled object into an electronic signal; the detection device is connected to the fuzzy PID controller through an input interface, and is used to input the electronic signal into the fuzzy PID controller, and convert the electronic signal into an analog signal through the fuzzy PID controller; the fuzzy PID controller is connected to the execution structure through an output interface, and is used to convert the analog signal into an actual control instruction; the execution structure is connected to the controlled object, and is used to control and adjust the controlled object according to the actual control instruction; The method for controlling the bed temperature of a circulating fluidized bed boiler in a thermal power plant comprises the following steps: Step 1, modeling the boiler bed temperature control system, and designing a fuzzy PID controller based on the modeling data of the boiler bed temperature control system; Step 2, using Matlab software to perform simulation test on the boiler bed temperature control system modeled in step 1, and optimizing the parameters of the fuzzy PID controller in step 1 according to the simulation test results; Step 3, enter the command "fuzzy" to activate the fuzzy PID controller tuned in step 2 and generate a Mamdani type fuzzy PID controller; Step 4: input the modeling data of the boiler bed temperature control system into a Mamdani type fuzzy PID controller to generate actual control instructions, and output the actual control instructions to the controlled object to realize fuzzy PID control of the controlled object.

2. The bed temperature control method of a circulating fluidized bed boiler in a thermal power plant according to claim 1, characterized in that: The modeling of the boiler bed temperature control system includes collecting actual operation data and analyzing the dynamic characteristics and nonlinear characteristics of the boiler bed temperature control system.

3. The bed temperature control method of a circulating fluidized bed boiler in a thermal power plant according to claim 1, characterized in that: The step of tuning the parameters of the fuzzy PID controller in step 1 according to the simulation test results includes: The parameters of the fuzzy PID controller are fuzzily associated with the error E and the error change rate EC, and the values ​​of the error E and the error change rate E are monitored in real time. The parameters of the fuzzy PID controller are adjusted according to the values ​​of the error E and the error change rate E.

4. The bed temperature control method of a circulating fluidized bed boiler in a thermal power plant according to claim 1, characterized in that: The fuzzy PID controller includes three parts: fuzzification, rule base design and defuzzification. The fuzzification includes modeling data as input data and converting the input data into a fuzzy set; the rule base design includes defining a fuzzy set The defuzzification includes converting the fuzzy set of the fuzzified output into actual control instructions. And the actual control instruction is used as the input of the control object.

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