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Direct drives with linear motors are attracting the attention of both industry and academia thanks to their advantages in terms of higher precision, higher acceleration/deceleration, and reduced dimensions. This paper presents a comparison between industrial PID controllers and state-of-art non-linear control strategies for accurate position tracking on a linear permanent magnet synchronous motor. Namely, the comparison considers an advanced sliding mode approach with scheduling laws related to the state trajectory in the phase plane, and an approximation-based adaptive scheme that relies on a neural network to cancel the non-linearites of the system so as to have almost linear residual dynamics. The feasibility of the control strategies is validated by an extensive experimental analysis. The schemes are both theoretically stable and guarantee accurate positioning, which are, in terms of average absolute position error, two times better than standard PID.