The influence of the noises uncertainty on the Kalman filter performance is characterized by sensitivity functions. Relationships for computing these functions are derived and used both for synthesizing a Kalman filter with reduced sensitivity (KFRS) and a self-tuning Kalman filter (SKF). The results are illustrated by examples.

This paper proposes a novel particle filtering framework for multi-target tracking by using online learned class-specific and instancespecific cues, called Data-Driven Particle Filtering (DDPF). The learned cues include an online learned geometrical model for excluding detection outliers that violate geometrical constraints, global pose estimators shared by all targets for particle refinement, ...

Based on the modern time series analysis method, for single channel autoregressive moving average (ARMA) signals with colored noise, a self-tuning weighted measurement fusion Kalman filter is presented when the model parameters and noise statistics are unknown. By applying the recursive instrumental variable (RIV) algorithm and the Gevers-Wouters (G-W) iterative algorithm with dead band, the lo...

_ In this paper, a partial update Kalman Filter (PUKF) is presented for the real-time parameter estimation of a DC-DC switch-mode power converter (SMPC). The proposed estimation algorithm is based on a novel combination between the classical Kalman filter and a M-Max partial adaptive filtering technique. The proposed PUKF offers a significant reduction in computational effort compared to the co...

 A step-by-step algorithm for enhancement of periodic signals that are highly corrupted by additive uncorrelated white gausian noise is proposed. In each adaptation step a new parallel second-order section is added to the previous filters. Every section has only one adjustable parameter, i.e., the center frequency of the self-tuning filter. The bandwidth and the convergence factor of each secti...

The filter term of a PID with Filter controller reduces the impact of measurement noise on the derivative action of the controller. This impact is quantified by the controller output travel defined as the total movement of the controller output per unit time. Decreasing controller output travel is important to reduce wear in the final control element. Internal Model Control (IMC) tuning correla...

The principles of the traditional passive filter for suppressing harmonics are qualitatively analyzed in this study. The auto-tuning principles based on TCR are also analyzed. According to the deficiencies of these filters, a passive filter based on variable reactors is presented and the tuning method is investigated principally. This filter utilizes the anti-parallel thyristor controlled react...