Internal model control of nonlinear systems through the inversion of recurrent neural networks
C. Kambhampati, R. Craddock, M. Tham, Kevin Warwick · 2002
Recurrent neural networks can be used for both the identification and control of nonlinear systems. This paper takes a previously derived set of theoretical results about recurrent neural networks and applies them to the task of providing internal model control for a nonlinear plant. Using the theoretical results, we show how an inverse controller can be produced from a neural network model of the plant, without the need to train an additional network to perform the inverse control.