Delayless recursive differentiator with efficient noise attenuation for motion control applications

Acceleration feedback can improve the performance of motion control in servomotor drives. Closed-loop acceleration control is, however, seldom implemented in practical drive systems due to the dissatisfactory performance of most existing acceleration measurement methods. In this paper, the authors introduce a feedback extension scheme for FIR (finite impulse response) polynomial differentiators making it possible to differentiate the velocity signal computationally efficiently while providing considerable noise attenuation. The proposed recursive differentiator does not delay the primary acceleration signal but, instead, the forward prediction step can be adjusted to compensate for various delays in the physical implementation. Predictive properties are obtained by taking advantage of the deterministic nature of polynomial signals. The utilization of the polynomial model, on the other hand, is justified because within narrow time windows, low-degree polynomials can be fitted accurately into the smoothly changing velocity and acceleration signals.