Application of adaptive Grey predictor based algorithm to boiler drum level control

To improve the boiler drum level control system of a power plant, the three challenging issues encountered include (1) effect of “false water level”, (2) controller parameter mismatches due to variant working conditions and (3) signal noise caused by uncertainties of drum level. In this paper, based on analyses of the drum level signal, an adaptive derivative action is presented to monitor steam flow, and thus, the effect of “false water level” is weakened. The uncertainties of parameter mismatches and noise are predicted by developing a Grey predictor based algorithm (GPBA). In order to resolve the three problems and further control performance, an adaptive technique is combined with the GPBA to develop an adaptive Grey predictor based method. Finally, concrete simulations give that the proposed method has obvious superiority over conventional methods.