The parametric convergence performance improvement in the direct adaptive multi-sinusoidal disturbance compensation problem

Abstract

The paper presents an approach to the parametric convergence performance improvement applied to the direct adaptive multi-sinusoidal disturbance compensation problem. The proposed method improves the performance of the existing solutions and ensures the transient monotonicity. The Dynamic Regressor Extension and Mixing (DREM) procedure followed by the discrete gradient estimator is applied for disturbance parameters estimation. The paper proves the applicability of Kreisselmeier’s scheme as an extension of the algorithm in procedure dynamic regressor extension. A numerical simulation is presented to illustrate the improvement of the transient processes of estimating the parameters of an unmeasured perturbation using the DREM procedure. The work can be used in solving practical problems in the fields of processing and evaluating harmonic and multi-harmonic signals, e.g., to suppress vibrations in electromechanical systems.

Keywords

• dynamic regressor extension and mixing
• kreisselmeier’s scheme
• persistent excitation condition
• discrete systems
• convergence
• parameters identification
• disturbance
• disturbance compensation