This thesis presents the development of an adaptive controller based on mismatched dynamic systems. Through the simulated control of the SAM manipulator, an intelligent assist device, the controller's performance and stability are analyzed. Two dynamic models, a simple model based on a revolute-prismatic manipulator and a complex model based on a three-revolute manipulator, are derived to describe the SAM's motion. Both models correctly describe the kinematic motion of the SAM however the complex model better captures the true manipulator dynamics. The adaptive controller is developed for the simple dynamic model of the SAM manipulator. The controller is then applied to drive a more complex SAM dynamic model. The simulation results show that even though differing dynamic terms exist, the adaptive controller is able to adjust the unknown parameters to significantly improve performance when compared to a non-adaptive computed torque controller. A step change in the payload mass is also tracked and properly identified by the adaptive controller.