This paper describes a comparative investigation of friction- compensating control strategies designed to improve low-velocity position tracking performance for servomechanisms. Several control methods are considered including adaptive control and estimation-based control. Additionally, the various controller designs incorporate different friction models ranging from classical friction and Stribeck friction to the less popular Dahl friction model. This investigation of friction models is motivated by the fact that there is little consensus in the literature on how best to model friction for dynamic friction compensation. The control strategies are compared in an extensive test program involving position tracking experiments on a direct- drive de motor. This effort addresses the current lack of comparative experimental results on friction compensation. The results show that the adaptive and estimation-based controllers outperform more traditional linear controllers. The experiments also yield insight into the appropriateness of the different friction models under the tested operating conditions. In particular, the Dahl model is observed to provide a reliable representation of friction behavior near zero velocity.