Neural-net-based control of dynamical systems: A case study

Multilayer perceptrons trained with the generalized delta rule or backpropagation procedure have been extensively applied in areas such as phoneme and image recognition and synthesis. Recently, many authors have reported interesting results on the application of these structures to the modeling and control of dynamical systems. In this article, we analyze the use of neural nets in a Model Reference adaptive Controller (MRAC) scheme for hydroturbine control. Several simulation results are provided, showing the feasibility of this approach and the factors involved in its design.