Устойчивость нечетких импульсных систем Такаги–Сугено: метод линейных матричных неравенств

The Lyapunov stability of impulsive Takagi-Sugeno fuzzy systems is considered. The sufficient conditions of stability for impulsive fuzzy systems are derived on the basis of Lyapunov’s direct method. They can be easily expressed as a system of linear matrix inequalities

Stability and stabilization of delayed T-S fuzzy systems: A delay partitioning approach

This paper proposes a new approach, namely, the delay partitioning approach, to solving the problems of stability analysis and stabilization for continuous time-delay Takagi-Sugeno fuzzy systems. Based on the idea of delay fractioning, a new method is proposed for the delay-dependent stability analysis of fuzzy time-delay systems. Due to the instrumental idea of delay partitioning, the proposed stability condition is much less conservative than most of the existing results. The conservatism reduction becomes more obvious with the partitioning getting thinner. Based on this, the problem of stabilization via the so-called parallel distributed compensation scheme is also solved. Both the stability and stabilization results are further extended to time-delay fuzzy systems with time-varying parameter uncertainties. All the results are formulated in the form of linear matrix inequalities (LMIs), which can be readily solved via standard numerical software. The advantage of the results proposed in this paper lies in their reduced conservatism, as shown via detailed illustrative examples. The idea of delay partitioning is well demonstrated to be efficient for conservatism reduction and could be extended to solving other problems related to fuzzy delay systems. © 2009 IEEE.published_or_final_versio

Finite-Time Stability Analysis and Control for a Class of Stochastic Singular Biological Economic Systems Based on T-S Fuzzy Model

This paper studies the problem of finite-time stability and control for a class of stochastic singular biological economic systems. It shows that such systems exhibit the distinct dynamic behavior when the economic profit is a variable rather than a constant. Firstly, the stochastic singular biological economic systems are established as fuzzy models based on T-S fuzzy control approach. These models are described by stochastic singular T-S fuzzy systems. Then, novel sufficient conditions of finite-time stability are obtained for the stochastic singular biological economic systems, and the state feedback controller is designed so that the population (state of the systems) can be driven to the bounded range by the management of the open resource. Finally, by using Matlab software, numerical examples are given to illustrate the effectiveness of the obtained results

An adaptive fuzzy observer-based approach for chaotic synchronization

AbstractThis paper presents an adaptive fuzzy observer design to synchronize chaotic systems. The chaotic system is expressed in the form of Takagi–Sugeno fuzzy model (T–S fuzzy system), which considers the effect of model mismatches. Based on this model, an adaptive fuzzy observer is developed to deal with the synchronization of nonidentical chaotic systems. In contrast to the framework of parallel distributed compensation for T–S fuzzy system, the proposed method does not rely on the existence of common matrix P which is imposed in stability conditions. The computer simulation examines the performance of two well-known chaotic systems, Lorenz system and Chua circuit. The results show that the proposed approach cannot only attain synchronization but also is robust to parameter perturbations in the drive system