A learning control of unused energy power generation

In recent years, the development of new clean energy without dependence on fossil fuel has become urgent. This article proposes a learning control system for power generation using a low-temperature gap which has been designed to maintain the speed of a steam turbine in a real environment. This system includes nonlinearity and the characteristics of changing parameters with age and deterioration, as in the real environment. The evaporator, condenser, and turbine systems have been modeled, and a PID control with the ability to learn, based on a BackPropagation neural network, has been designed.