Abstract
AbstractBoiler drum system is an important component of a thermal power plant or industrial production, and the water level is a critical parameter of boiler drum control system. Because of non-linear, strong coupling and large disturbance, it is difficult to reach a suitable working state of drum system by using traditional control methods. It is necessary to explore new methods to realize optimal control of drum water level. The back propagation (BP) neural network model of boiler drum system is built in this paper firstly, then the optimal control of the drum system by the dual heuristic dynamic programming (DHP) algorithm is realized, and compared with the heuristic dynamic programming (HDP) algorithm at last. The result shows that the DHP optimization algorithm has good performance in control precision and rejecting process disturbances.Keywordsboiler drum levelBP neural networkdual heuristic dynamic programmingoptimal control
Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
