Disturbances and uncertainties, ubiquitous in real‐world systems, complicate model‐based control design. A key challenge is developing a precise control strategy that takes all disturbances into account. The automatic dry‐type clutch is a nonlinear, uncertain, and continuous system, where influencing factors are regarded as total disturbances. An active disturbance rejection control (ADRC) framework with an adaptive extended state observer (AESO) is proposed. The AESO's key strength is its adaptability, adjusting gains over time to minimize state estimation errors and noise impacts. This optimizes disturbance estimation, enhancing closed‐loop system performance. Furthermore, we prove the stability of the AESO through the Lyapunov method and, based on this, set the controller parameters as a Hurwitz matrix to ensure the stability of the closed‐loop system. Experimental data from clutch control demonstrates the efficacy of this controller. It ensures clutch position accuracy with a mean value of 13.5255 mm and a root mean square error of 28.7368 mm. Notably, the AESO's observation errors are minimal, averaging at 0.4365 mm with a root mean square error of 0.7068 mm, even under conditions of uncertain dynamics and measurement noise. This performance surpasses traditional ADRC methods relying on linear extended state observers (ESO) and PI control, thereby advancing the practical applicability of ADRC. Finally, through simulations comparing with fuzzy ESO and nonlinear ESO, the results show that the proposed AESO can achieve the same effect as them.