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Resonant electromagnetic actuators have been broadly used as vibration motorsfor mobile devices given their ability of generating relatively fast, strong,and controllable vibration force at a given resonant frequency. Mechanism ofthe actuators that is based on mechanical resonance, however, limits their useto a situation where their resonant frequencies are known and unshifted. Inreality, there are many factors that alter the resonant frequency: for example,manufacturing tolerances, worn mechanical components such as a spring,nonlinearity in association with different input voltage levels. Here, wedescribe a sensorless resonance tracking method that actuates the motor andautomatically detects its unknown damped natural frequency through theestimation of back electromotive force (EMF) and inner mass movements. Wedemonstrate the tracking performance of the proposed method through a series ofexperiments. This approach has the potential to control residual vibrations andthen improve vibrotactile feedback, which can potentially be used forhuman-computer interaction, cognitive and affective neuroscience research.

Sensorless Resonance Tracking of Resonant Electromagnetic Actuator through Back-EMF Estimation for Mobile Devices