System identification of laboratory fan heater using artificial neural network

Cilj umjetne inteligencije je ostvarenje sustava koji rješava probleme samostalno i inteligentno poput čovjeka. Kao što ideja o avionima potječe od promatranja ptica, tako je razvoj umjetnih neuronskih mreža potakunt spoznajama o građi i načinu funkcioniranja ljudskog mozga. U radu je ukratko objašnjen razvoj neurona i ideja neuronskih mreža te je opisana njihova struktura. Iako su još daleko od potpunog oponašanja funkcija mozga, neuronske mreže uspješno se primjenjuju na mnogim područjima. Prikazana je usporedba dva tipa neuronskih mreža, statičke i dinamičke mreže učene metodom povratnog prostiranja pogreške. Mreže su testirane i uspoređene na problemu identifikacije toplinskog procesa, realiziranog primjenom laboratorijskog modela grijalice zraka.The aim of artificial intelligence is to develop a system that solves problems independently and intelligently like a human. As the idea of a plane comes from observation of birds, so is the development of artificial neural networks enhanced by the knowledge of the structure and the way of functioning of the human brain. The paper briefly explains the development of neurons and ideas of neural networks, and also their structure is described. Although they are far from complete imitating brain functions, neural networks are successfully applied to many systems. Comparison of two types of neural networks, static and dynamic neural network trained with error-back propagation algorithm, is presented. Both networks were tested and compared on process identification problem realized using laboratory air heater testbed