Anti-disturbance synchronization of fuzzy genetic regulatory networks with reaction-diffusion.

This paper intends to focus on the anti-disturbance synchronization issue for genetic regulatory networks subject to reaction-diffusion terms based on the Takagi-Sugeno fuzzy model. In view of the fact that disturbances are widespread in actual control engineering, the stability of the aforementioned systems would be affected, therefore, ensuring the stability of closed-loop genetic regulatory networks is the main goal of this paper. The unknown disturbances are supposed to be generated by an exogenous system, which can be estimated by developing disturbance observers. Furthermore, integrating the disturbance observers with fuzzy rule-based conventional control laws, a new anti-disturbance control strategy is proposed to reject the disturbances and guarantee the desired dynamic performances. Then, by constructing a proper Lyapunov function and using advanced decoupling techniques, some sufficient conditions in the form of linear matrix inequalities, to guarantee the asymptotic stability of the error system, are obtained. Finally, an illustrated example is presented to demonstrate the effectiveness and superiority of the proposed method. [ABSTRACT FROM AUTHOR]