To deal with the difficulty of input disturbance system in achieving adaptive control, a design method for the Fully Online Sequential Extreme Learning Machine (FOS-ELM) controller with Proportion-Integral-Derivative (PID) compensation was proposed. Firstly, a dynamic linear model of the system was established, then the FOS-ELM algorithm was used to design the controller and learn its parameters. Secondly, by calculating the output error of the system and combining with the system control error, the PID parameters of the system compensation were designed. Finally, the FOS-ELM controller parameters for PID compensation were adjusted online and used for system control. The experiment was carried out on engine Air Fuel Ratio (AFR) control system. The results show that the proposed method can achieve the adaptive control, reduce the disturbance caused by system disturbance input, and obviously improve the effective control rate of the system at the same time. When the positive and negative interference coefficients are 0.2, the effective control rate is increased from less than 53% to over 93%. In addtion, the proposed method is easy to implement and has strong robustness and practical value.