To suppress friction fluctuations during the operation of a pipeline inspection gauge (PIG) and to avoid speed deviations, which may lead to poor detection accuracy and jamming, an adaptive backstepping controller with improved unscented Kalman filter (UKF) was proposed in this paper. Firstly, the friction model was derived, and based on this, the nonlinear dynamic model of PIG was established. Then, an adaptive backstepping controller was designed to estimate the dynamic parameters of the system and stabilize the operating velocity of the PIG by controlling the friction, and adaptive noise based UKF was applied to obtain more accurate feedback estimated signals to deal with the time-varying disturbances in the environment. An active control PIG prototype and a pipeline experimental platform was built, and experiments were conducted under various conditions. Under all conditions, compared to the uncontrolled system, the proposed control strategy can reduce the fluctuation range of friction values by more than 59%, reduce the velocity fluctuation range by more than 88%, and maintain the velocity control error within 4%. Compared to the other controllers, the proposed controller demonstrated better performance in terms of control precision and robustness, verifying the effectiveness and reliability of the proposed controller.