Based on the analysis of the dynamic characteristics of the boiler water level, this paper optimizes the boiler water level control system by using the parameter immune optimization algorithm. By comparing the control effect of the immune optimized PID controller with that of the ordinary water level controller through software simulation, the conclusion that the control effect of the parameter immune optimization is better than that of the conventional control method is verified. The water level of the drum inside the boiler is the main index and parameter for its safe and efficient operation. It must be maintained within a reasonable range.
The regulated parameters in the control loop of boiler feed water automatic regulation are the drum water level (H), and the regulated amount of feed water regulating valve is the feed water flow (W). The inner volume of the drum can be divided into three parts: the steam volume above the evaporation surface, the steam volume under the evaporation surface and the water volume. The dynamic characteristics of steam generation system can be expressed by the dynamic characteristics of drum pressure and drum water level.
There are four factors affecting disturbance parameters of water level regulating object: disturbance of feed water flow, including variation of feed water pressure and opening and closing of regulator valves of dampers; variation of steam load, including variation of pipeline resistance and opening and closing of regulator valves of load equipment; various factors affecting fuel calorific value; change of drum pressure and water level, from change of heat load Consider the change of chemical or steam load. The disturbance of boiler water level control system mainly comes from three aspects: furnace load disturbance, steam flow disturbance and feed water flow disturbance. The influence of furnace load disturbance is slow and lagging, and can be eliminated by heat load regulator in fuel automatic regulation system. Therefore, thermostatic element the main factors of disturbing water level are steam flow disturbance and feed water flow disturbance. Boiler water level control system is a compound control system which combines feed-forward and feedback. Its main control signal is drum water level, feed-forward signal is steam flow and feed-back signal is feed-water flow. The essence of the control system is two closed loops, one is an internal loop composed of feed water flow, control valve, feed water flow regulator and regulator, the other is an external loop composed of an internal loop and a drum water level controller. In order to improve the control quality without affecting the stability of the closed loop, the steam flow rate and its steam diverter are designed outside the closed loop.
In order to compare, this paper uses ordinary PID controller and parameter immune optimization PID controller to simulate and analyze the control effect of water level control system. General PID controller parameter setting. The parameters of the boiler drum water level control system are set as follows by the ordinary PID controller: 0.
0667, = 3, = 1, = 0.2 according to the references. Parametric immune optimization PID controller parameter setting.
The controller uses immune optimization algorithm to adjust the parameters of the PID controller to obtain better dynamic characteristics.
Punishment measures are added to the program, and the overshoot is taken as an optimal index to reduce its impact. In the simulation, the values of each parameter are: = 0.998, = 0.002, = 2, = 99. Real-coded immune algorithm was used to optimize the population size. After 150 generations of evolution, 30% activation ratio, 6 times clone multiple, 6:1 immune supplement ratio and 10% mutation rate were obtained. The descent curve of objective function is obtained by simulation with MATlAB software. The observation curve shows that the optimization is near the 28th generation, and the value of the objective function decreases by 16% after optimization, which has a significant optimization effect. After setting, the parameters of the immune PID controller are:,,,,,,. The gain is set to: = 0.
0666, = 2, = 0.9, = 0.3. In this paper, considering the two most important factors, the performance of the two controllers of the boiler water level control system is simulated and analyzed by using MATLAB software.
30% response to steam flow disturbance. At 0.01s, 30% disturbance of steam flow occurs. The simulation results of the response of two kinds of PID controllers are shown in Figure 1. From the simulation results, it can be seen that the maximum fluctuation of the water level of the ordinary PID controller is 0.36, and the fluctuation of the parameter immune optimization PID controller is 0.15, and the fluctuation is small. This shows that the control effect of parameter immune optimization PID controller is better than that of ordinary controller in overcoming steam disturbance. Response of feed water disturbance system. The simulation results of the response of two kinds of PID controllers are shown in Fig. 2 when the disturbance signal of feed water is added at 0.01s.
From the simulation results, it can be seen that the influence of feed water flow disturbance on water level control system is smaller than that of steam flow disturbance, but the simulation value comparison between the two controllers is obvious: the maximum fluctuation of water level of ordinary PID controller is 0.008, and the maximum fluctuation of water level of parameter immune optimization PID controller is 0.0036. This shows that the control effect of parameter immune optimization PID controller is better than that of ordinary controller in overcoming feed water disturbance.
In this paper, according to the dynamic characteristics of the water level of industrial boiler drum, the parameter immune optimization of the water level controller is carried out. In order to verify the optimization results, the ordinary PID controller and the parameter immune optimization PID controller of the water level control system of boiler drum are modeled and simulated by using MATlAB simulation software. The simulation results prove that the parameter immune optimization P The ID controller has better control quality, and this optimization method has better application prospects and popularization value.