This paper deals with a signal-based robust adaptive approximation technique for a proportional derivative (PD) regulator which is applied to an electromagnetic valve actuator control for camless internal combustion engines. PD regulators generate very high spikes in the presence of unavoidable noise. These spikes cause high power dissipation and poor dynamic performance with a lack of precision. The presented method allows the reduction of the noise and not robust nonlinear uncertainties effects by using minimum variance analysis. The technique with which the PD regulator is approximated does not depend on the model of the controlled system. Hence, the technique is quite general and can be applied to any type of system. In addition, this paper describes a feasible real-time self-tuning of an approximated discrete PD regulator using a backward Euler technique. The main contribution of the paper is the presentation of an approximated PD controller using a minimum variance control strategy together with a weighted least squares method to adapt the parameters of this approximated controller. This control law realises a robust control technique with respect to the noise and nonlinear uncertainties. Moreover, a comparison with the approximate PD controller proposed in MATLAB by Mathworks is provided. The presented technique ensures a good dynamic performance, including low dissipation as well as accurate positioning and soft landing control.