Iterative Learning Control And Application In Heat Steam Temperature Control System In Power Plant

As the thermal objects of plants have nonlinear, parameter uncertainty, time-delay and inertance characteristics, it is not adaptable to the control system of modern large power units for the normal control system based on PID. In this paper, the application of iterative learning control (ILC) theory is investigated, which mainly deals with controlling the dynamics in steady state optimizing control of industrial processes and the dynamics when the reprtitive disturbances in the controlled systems. Various ILC algorithms are used in the industrial process control of linear and nonlinear systems, besides prove their convergence and simulate. The ILC design strategy was applied in a main temperature control system in a power plant. Finally carried on the simulation of the computer, the result showed that this control strategy has very good control quality and has wide application prospect.