Identification of nonlinear time varying systems based on recurrent neural networks;

As it is well known,it is difficult to identify a nonlinear time varying system using traditional identification approaches,especially under unknown nonlinear function.

The performance of the algorithm is evaluated on the identification of some typical time-varying nonlinear system including the three degrees of freedom structural system with nonlinear time-varying stiffness.

A new method to estimate unknown noise statistics Q and R of nonlinear time-varying system;

Improved RLS algorithm for nonlinear time-varying system identification based on feed forward neural networks

A model switching algorithm based on multi-model adaptive control is presented to solve the problem of poor transient response in the adaptive control of nonlinear time-varying system.

First order approximation of partial exponential stability of nonlinear time-varying systems;

This paper presents stability analysis for general nonlinear time-varying systems.

A new identification method based on feed forward networks is presented for nonlinear time varying systems.

The problem of robust output tracking control for a class of affine nonlinear time varying systems with mismatched uncertainties is considered.

Output tracking for a class of affine nonlinear time varying systems based on state observers is considered.