Study of two-cell immune feedback control for water level of boiler drum based on gray prediction
Due to the ‘false water level’ phenomenon in power station makes the traditional control strategy can't be a good solution to the problem, a two-cell immune feedback control strategy based on gray prediction for water level of boiler drum in power station is proposed, which using the function of gray prediction with strong self-adaptability and advanced control functions, and learning from bio-feedback mechanism of the immune system and regulating rule of response process. Through lots of simulation studies, it can achieve a more satisfied control quality with strong robustness and anti-jamming capability. Meanwhile, the structure and algorithm of the control strategy are simple and easy to engineering implementation.
Boiler Drum Level Control Using Internal Model Controller
The water level of boiler drum is one of the crucial control parameters for any process industry which reflects the control of mainly boiler load and feed water indirectly. If the level exceeds the limits, boiler water carryover into the superheater or the turbine may cause damage resulting in extensive maintenance costs. If the level is low, overheating of the water wall tubes may cause tube ruptures and serious accidents, resulting in expensive repairs, downtime, and injury or death to personnel.A rupture or crack most commonly occurs where the tubes connect to the drum. Damage may be a result of numerous or repeated low drum level conditions where the water level is below the tube entry into the drum. Boiler drum is one of the typical multi-input multi-output systems, and also shows high nonlinearities, time varying response and a transportation lag. Conventionally, such system has been controlled using PID (proportional, integral, derivative) controller. Due to presence of nonlinearity (dead time) boiler drum performance can be affected when it is controlled by PID controller.Moreover PID controller produces larger settling time. To have an effective tracking of set point, an internal model based control (IMC) methodology can be implemented.The transfer function for drum level is obtained using mathematical modeling and transfer function for steam flow rate is obtained using system identification tool box.single element control is implemented using PID and IMC controllers.Three element control is implemented using cascade structure in which PID is used in primary and secondary loops.From the performance criteria it has been analysed and found that the IMC controller has better settling time, rise time, peak time and peak overshoot compared to conventional PID controller.
Fuzzy PID Control With Grey Prediction and Its Application in Temperature Control System
Incorporating the grey prediction, fuzzy control and the conventional PID control, a design method of the grey prediction fuzzy PID control algorithm is presented. This control algorithm can be divided into three steps: to build the fuzzy tuning rules by simulation and analysis and obtain the parameters of PID controller by reasoning, to determine the control effect through the PID control law directly, and then to put the grey prediction into online uses. The prediction results replace the measure of the controlled object. The simulation results show that the superheated steam temperature control system using this algorithm has better performances than that of fuzzy PID control system.