We present a new adaption rule for the filtered x least mean squares (FxLMS) algorithm and its application as a disturbance compensator for the quarter car. Therefore we combine an adaption rule, which is based on the normalized, leaky-nu FxLMS algorithm, with a novel method for the initialization of the filter coefficients. This leads to fast convergence, which is important in the case of sudden changes in the primary path's delay time. Thereafter, the new algorithm is applied as a disturbance compensator for road irregularities. The goal is to improve driving comfort and safety by exploiting the knowledge of the road surface (i.e. disturbance). Assuming that it is known a certain time in advance, we show the improved performance of the developed algorithm and compare it to the standard FxLMS algorithm and to a static disturbance compensator.      «

We present a new adaption rule for the filtered x least mean squares (FxLMS) algorithm and its application as a disturbance compensator for the quarter car. Therefore we combine an adaption rule, which is based on the normalized, leaky-nu FxLMS algorithm, with a novel method for the initialization of the filter coefficients. This leads to fast convergence, which is important in the case of sudden changes in the primary path's delay time. Thereafter, the new algorithm is applied as a disturbance...     »