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On comparison of effectiveness of neural tuner based adaptive control system and observer based controller to solve heating plant control problem

Industrial heating plants are high power nonlinear units. Their energy efficiency can be improved by optimal or adaptive control systems application. One of the most efficient optimal control methods is state observer based controller using the plant model. However, its functioning is dependent on the plant identification accuracy and the fact whether the model is being kept actual. The aim of this research is to develop the mentioned controller for a heating furnace mathematical model and compare results of its functioning to the PI-controller neural tuner, which does not require the model at all. Obtained results show that the observer based controller is of high efficiency so far as the plant model coincides with the real plant, but worse results are got when the plant changes its state. At the same time, the neural tuner allows to keep the transients quality at the required level despite the fact that the plant changes its parameters.