Machine learning techniques, including Gaussian processes (GPs), are expected to play a significant role in meeting speed, accuracy, and functionality requirements future data-intensive mechatronic systems. This paper aims reveal the potential of GPs for motion control applications. Successful applications feedforward control, identification noncausal feedforward, position-dependent snap nonlin...