Control of perturbed systems using neural networks

Stability conditions for a perturbed plant control by a conventional robust controller and a neurocontroller are presented. The neural net-based direct inverse controller is proposed to aid the robust controller to further suppress the output error resulting from the unmodeled residuals. A procedure for determining the permissible network's output under which the overall closed-loop system will be robustly stable is provided.