首页> 外文会议>2017 International Conference on Inventive Computing and Informatics >On comparison of effectiveness of neural tuner based adaptive control system and observer based controller to solve heating plant control problem
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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

机译:基于神经调谐器的自适应控制系统和基于观测器的控制器解决供热厂控制问题的有效性比较

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摘要

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.
机译:工业供热厂是大功率非线性装置。通过优化或自适应控制系统的应用可以提高其能效。最有效的最佳控制方法之一是使用工厂模型的基于状态观察器的控制器。但是,其功能取决于工厂识别的准确性以及该模型是否保持实际的事实。这项研究的目的是开发一种用于加热炉数学模型的控制器,并将其功能的结果与PI控制器神经调谐器进行比较,后者根本不需要该模型。所得结果表明,只要工厂模型与实际工厂一致,基于观察者的控制器就具有很高的效率,但是当工厂更改其状态时,会得到较差的结果。同时,尽管工厂改变了参数,神经调谐器仍可将瞬变质量保持在所需水平。

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