ALGORITHMS FOR MAKING CONTROL SYSTEMS BASED ON NEURAL NETWORK TECHNOLOGY TO AUTOMATE DYNAMIC PLANTS
Jasur SevinovTashkent state technical university. Adress: Uzbekistan, Tashkent city, University street 2. E-mail: [email protected],Abdishukurov Maqsudovich ShavkatTashkent state technical university. Adress: Uzbekistan, Tashkent city, University street 2. E-mail: [email protected]
Himičeskaâ tehnologiâ. Kontrolʹ i upravlenie/Chemical Technology. Control and Managementjournal2025en
ABI
Abstract
This paper examines the stages of multilayer neural network technology for the control and identification of dynamic systems. It is seen many ways to use multilayer neural networks in control systems. Neural controllers are based on several models and algorithms. Examples of such algorithms include the predictive model-based control algorithm, the Narma-L2 control algorithm, and the benchmark model-based control algorithm. These controllers illustrate various general ways to use multilayer neural networks in control systems. Common, standard linear control architectures have been proposed for many neural controllers.
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