Fuzzy Neuro Observer-Based Control For Nonlinear Descriptor Systems In The Sense Of Practical And Finite-Time Stability

This paper focuses on fuzzy neural control based on observers for a class of nonlinear descriptor systems, which is expressed by Takagi-Sugeno fuzzy model. Several bounded sufficient conditions for nonlinear descriptor systems are derived and represented with linear matrix inequalities. Following proposed theorems of the sufficient conditions for error systems between dynamic systems and their observers, practical ultimate boundedness and finite-time boundedness can be obtained alternatively. And partially based on parallel distribution compensation and non-parallel distribution compensation, fuzzy neural adaptive controllers are devised to guarantee both practical stability and finitetime stability of such studied systems. A numerical example applied to inverted pendulum model is given to confirm the effectiveness of our approach.