Variable convergence rate fuzzy control of chaotic Chua's circuit under impulsive and stochastic disturbances

This paper proposes an intelligent regulation method for dynamically adjusting the convergence rate of nonlinear Chua's circuits subject to impulsive effects and stochastic disturbances, based on a Takagi-Sugeno (T-S) fuzzy model. First, an interval stability criterion for variable convergence rate is established through generalized pole assignment principle, constructing a unified analytical framework that simultaneously incorporates stability margin and dynamic convergence rate indicators. Second, a state feedback fuzzy controller with convergence rate constraints is designed. By constructing a constrained eigenvalue domain, the controller enables active regulation of the system's convergence rate. Furthermore, an intelligent convergence rate regulation algorithm is developed to achieve precise on-demand adjustment for Chua's circuit. Finally, simulation experiments conducted on the original system using the proposed fuzzy controller verify the effectiveness and practical utility of the control strategy.