Controlling Digital Systems via Intelligent Networks

Abstract

: Control is important to improve hardware performance. Most electronic systems are designed according to
 the device and then manufactured as an attached electronic device. However, if conditions change or the factory is
 modernized then the control device must be replaced. This is due to the complexity of the control unit represented by
 the program implementation algorithms, in addition to the time delay caused by digital and analog signal converters
 (ADC - DAC), and in this research it is replaced by deep neural networks It is a thriving field with practical and
 medical applications and is characterized by its ability to learn and train as it is a branch of machine learning and
 artificial intelligence. The results proved that the functioning of the neural networks and their performance are better
 than the control system where the value of the difference between the two is equal to zero.