IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
Robust peak-to-peak filtering for Markov jump systems
Signal Processing
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics - Special issue on human computing
H∞ fuzzy filtering of nonlinear systems with intermittent measurements
IEEE Transactions on Fuzzy Systems
IEEE Transactions on Fuzzy Systems
An ILC-based adaptive control for general stochastic systems with strictly decreasing entropy
IEEE Transactions on Neural Networks
Delay dependent stability results for fuzzy BAM neural networks with Markovian jumping parameters
Expert Systems with Applications: An International Journal
Filtering-based robust fault detection of fuzzy jump systems
Fuzzy Sets and Systems
| Hi-index | 0.00 |
This paper is concerned with the robust-stabilization problem of uncertain Markovian jump nonlinear systems (MJNSs) without mode observations via a fuzzy-control approach. The Takagi and Sugeno (T-S) fuzzy model is employed to represent a nonlinear system with norm-bounded parameter uncertainties and Markovian jump parameters. The aim is to design a mode-independent fuzzy controller such that the closed-loop Markovian jump fuzzy system (MJFS) is robustly stochastically stable. Based on a stochastic Lyapunov function, a robust-stabilization condition using a mode-independent fuzzy controller is derived for the uncertain MJFS in terms of linear matrix inequalities (LMIs). A new improved LMI formulation is used to alleviate the interrelation between the stochastic Lyapunov matrix and the system matrices containing controller variables in the derivation process. Finally, a simulation example is presented to illustrate the effectiveness of the proposed design method.