This paper presents an algorithm to develop a mission-based optimal joint space control for a Stewart manipulator. The proposed algorithm consists of two optimization phases. The first phase seeks an inverse kinematic model and controller for the closed loop control of a Stewart manipulator using a feedback value. The second phase optimally tunes the controller called amplitude phase control (apc) in order to meet special mission requirements. Iteration algorithm is used in this phase as the optimization method. The proposed amplitude phase control optimal joint space control shows the capability to reduce the error in tracking the sin signals.