<p>The use of known model information in the active disturbance rejection controller design reduces the magnitude of the “total disturbance” and consequently improves the control performance. In this paper, based on Takagi–Sugeno (T-S) fuzzy modeling, a new method is proposed to incorporate the known nonlinear dynamics of the plant into a linear active disturbance rejection controller (LADRC). In addition, to evaluate the effectiveness of the proposed method, simulations of a cart inverted pendulum are performed. First, a highly nonlinear plant, the pendulum angle control system, is simulated. Simulation results show that the estimation burden of the extended state observer is reduced and the control performance is improved in the proposed method than in the conventional model-assisted LADRC that can incorporate only linear model information. Next, the cascade control scheme based on the proposed method and PD controller for the pendulum angle stabilization and position tracking is proposed and constructed accordingly, and simulated in comparison with the case of using two PID controllers. The simulation results show that the proposed cascade control scheme has good disturbance rejection, transient response and robustness at the same time.</p>