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.