Chaos Synchronization Based on Unknown Input Proportional Multiple-Integral Fuzzy Observer

Chaos Synchronization Based on Unknown Input Proportional Multiple-Integral Fuzzy Observer

and Applied Analysis 3 2. Unknown Input TS Fuzzy Model Structure The TS fuzzy model subject to unknown input is considered as follow:

Design of proportional-integral observer for unknown input descriptor systems

This note presents simple methods to design fulland reducedorder proportional integral observer for unknown inputs (UI) descriptor systems. Sufficient conditions for the existence of the observer are given and proven. The observer is solvable by any pole placement algorithm, it achieves a posteriori robustness state and UI estimation versus to time varying parameters and bounded nonlinear UI. A...

Sensor fault and unknown input estimation based on proportional integral observer applied to LPV descriptor systems

Observer-Based Synchronization for a Class of Unknown Chaos Systems with Adaptive Fuzzy-Neural Network

This investigation applies the adaptive fuzzy-neural observer (AFNO) to synchronize a class of unknown chaotic systems via scalar transmitting signal only. The proposed method can be used in synchronization if nonlinear chaotic systems can be transformed into the canonical form of Lur'e system type by the differential geometric method. In this approach, the adaptive fuzzy-neural network (FNN) i...

Unknown input multiple observer based approach. Application to secure communications

This paper presents multiple observer design for nonlinear chaotic systems with unknown inputs in multiple model approach. The considered unknown inputs influences the states and the outputs of the system. The main objective is to estimate the state variables as well as the unknown inputs of this system. For that, we propose the synthesis of a multiple observer based on the elimination of these...