Magnetically levitated planar motor is a new-generation motion device in modern precision industry, while its advanced motion controller design is still of main concern. In this paper, a learning adaptive robust control (LARC) motion controller is proposed for a magnetically levitated planar motor developed in our laboratory to achieve good tracking performance. The planar motor consists of a Halbach permanent magnetic array as the stator, and a levitated platen containing four groups of three-phase windings as the mover. Based on the Lorentz force law, the mover placed in the magnetic field is subjected to vertical force for levitation and horizonal force for planar motion through dynamics decoupling and current allocation. An LARC control scheme containing adaptive robust control (ARC) term and iterative learning control (ILC) term in a serial structure is then proposed for the magnetically levitated planar motor to achieve high-performance tracking even there exist parametric variations and uncertain disturbances. Comparative experiments between traditional lead, ARC, ILC, and the proposed LARC are carried out on the planar motor to track sinusoidal, point-to-point, and planar circular motions, respectively. The experimental results consistently validate that the proposed LARC control strategy outperforms other controllers much, and possesses not only good transient/steady-state tracking performance but also parametric adaptation ability and uncertain disturbance robustness. The proposed scheme actually provides a practically effective technique for motion control of magnetically levitated planar motors in industrial applications.