A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2005; you can also visit the original URL.
The file type is application/pdf
.
Neural network-based control design: an LMI approach
1998
IEEE Transactions on Neural Networks
In this paper, we address a neural-network-based control design for a discrete-time nonlinear system. Our design approach is to approximate the nonlinear system with a multilayer perceptron of which the activation functions are of the sigmoid type symmetric to the origin. A linear difference inclusion representation is then established for this class of approximating neural networks and is used to design a statefeedback control law for the nonlinear system based on the certainty equivalence
doi:10.1109/72.728392
pmid:18255820
fatcat:xpo4ozhdjvf5rmzykfwwwcflua