화학공학소재연구정보센터
IEEE Transactions on Automatic Control, Vol.44, No.1, 102-108, 1999
Robustifying nonlinear systems using high-order neural network controllers
A robustifying control methodology for affine in the control nonlinear dynamical systems is developed in this paper. A correction control signal is added to a nominal controller (designed to guarantee a desired performance for the corresponding nominal system), to render the actual system uniformly ultimately hounded The control signal is smooth and does not require the a priori knowledge of an upper bound on the modeling error and/or optimal weight values. Simulations performed on a simple nonlinear system illustrate the approach.