Adaptive neural network tracking control with disturbance attenuation for multiple-input nonlinear systems

Prescribed Performance Output Feedback/Observer-Free Robust Adaptive Control of Uncertain Systems Using Neural Networks

A neural network output feedback/observer-free continuous controller for multiple-input-multiple-output uncertain nonlinear systems is designed, which is capable of guaranteeing prescribed performance bounds on the system output, as well as the boundedness of all other closed-loop signals, despite the presence of additive external disturbances and unmodeled dynamics. The assumptions that were made concern the satisfaction of an unboundedness observability property and an output Lagrange stability condition of the unmodeled dynamics subsystem and that the nominal system is output feedback equivalent to a strictly passive one. Simulations on an induction motor system illustrate the approach.