Recently, various forms and purposes of autonomous mobility have been widely developed and commercialized. To control the various iterations of shaped and purposeful mobility, control technology that can adapt to the dynamic characteristics of the mobility and environmental changes is essential. This study presents an adaptive proportional–integral–derivative (PID) controller for longitudinal velocity and yaw rate tracking in autonomous mobility, addressing the aforementioned issue. To design the adaptive PID controller, error dynamics have been designed using error and control input with two coefficients. It is designed that the two coefficients are estimated in real time by recursive least squares with multiple constraints and forgetting factors. The estimated coefficients are used to compute PI gains based on the Lyapunov direct method with constant derivative gain. Multiple constraints, such as value and rate limits, have been incorporated into the RLS algorithm to enhance the control stability. The performance evaluation is conducted through the co-simulation of MATLAB/Simulink and CarMaker under integrated control scenarios, such as longitudinal velocity and yaw rate tracking, for mobility.