This paper discusses and analyzes the performances of an Intelligence Pneumatic Actuator (IPA) positioning system using Predictive Functional Controller (PFC) with Kalman filter Design. The uncertainties in the pneumatic system are undesirable. Kalman filter is useful in vast areas due to the prediction assets. The system models are designed based on previous research on the predictive controller and focused on position tracking. The transfer function for the pneumatic actuator is obtained by using system identification (SI) techniques. The initial covariance values of the Kalman filter system are determined according to the plant system. The performances of the proposed system are performed in MATLAB, Simulink and validated with IPA plant. The validation process of the IPA plant is run through real-time experiments using National Instrument (NI) devices. The Result showed the system is stable with Kalman filter is new implementation on both simulations and experiment process.