Topic
Alpha beta filter
About: Alpha beta filter is a research topic. Over the lifetime, 5653 publications have been published within this topic receiving 128415 citations.
Papers published on a yearly basis
Papers
More filters
TL;DR: In this article, an improved variable hysteresis-band current control in natural frame for a three-phase unity power rectifier is presented, which is based on three decoupled sliding-mode controllers combined with three independent Kalman filters.
Abstract: This paper presents an improved variable hysteresis-band current-control in natural frame for a three-phase unity power rectifier. The proposed control algorithm is based on three decoupled sliding-mode controllers combined with three independent Kalman filters. The use of Kalman filters instead of a nonadaptive state observer improves the quality of the estimated signals in presence of noise, increasing the immunity of the control loop in noisy environments. To reduce drastically the computational load in the Kalman algorithm, a reduced bilinear model is derived which allows to use a Kalman filter algorithm instead of an extended Kalman filter. A fast output-voltage control is also presented which avoids output-voltage variations when a sudden change in the load or a voltage sag appears. Moreover, a fixed switching frequency algorithm is proposed which uses a variable hysteresis-band in combination with a switching decision algorithm, ensuring a switching spectrum concentrated around the desired switching frequency. The overall control proposal has been fully integrated into a digital signal processor. Selected experimental results are introduced to validate the theoretical contributions of this paper.
70 citations
TL;DR: In this article, a new decentralized computational structure is developed for optimal state estimation in large scale linear interconnected dynamical systems, which uses a hierarchical structure to perform successive orthogoilalizations on the measurement subspaces of each sub-system in order to provide the optimal estimate.
Abstract: In this paper a new decentralized computational structure is developed for Optimal state estimation in large scale linear interconnected dynamical systems. The new filter uses a hierarchical structure to perform successive orthogoilalizations on the measurement subspaces of each sub-system in order to provide the optimal estimate. This ensures substantial savings in computation time. In addition, since only low-order subsystem equations are manipulated at each stage, numerical inaccuracies are reduced, and the filter remains stable for even high-order systems. This is illustrated on a multimachine example of a system comprising eleven interconnected machines.
70 citations
TL;DR: An adaptive observer form is derived which can be utilized in designing the reduced order state observer and results are given to exhibit the effectiveness of proposed synthesis approaches in dealing with the practical systems.
70 citations
TL;DR: The problem of simultaneously estimating the state and the fault of linear stochastic discrete-time varying systems with unknown inputs is studied and the Optimal three-stage Kalman Filter (OThSKF) is proposed.
Abstract: The paper studies the problem of simultaneously estimating the state and the fault of linear stochastic discrete-time varying systems with unknown inputs. The fault and the unknown inputs affect both the state and the output. However, if the dynamical evolution models of the fault and the unknown inputs are available the filtering problem will be solved by the Optimal three-stage Kalman Filter (OThSKF). The OThSKF is obtained after decoupling the covariance matrices of the Augmented state Kalman Filter (ASKF) using a three-stage U–V transformation. Nevertheless, if the fault and the unknown inputs models are not perfectly known the Robust three-stage Kalman Filter (RThSKF) will be applied to give an unbiased minimum-variance estimation. Finally, a numerical example is given in order to illustrate the proposed filters.
70 citations
TL;DR: In this article, a linear functional state observer for time-delay systems is introduced, which converges to any number of linear functionals when some conditions are met, with any prescribed stability margin.
Abstract: A new linear functional state observer for time-delay systems is introduced in this paper It is shown that the observer converges, with any prescribed stability margin, to any number of linear functionals when some conditions are met The design procedure is simple and can be easily implemented Numerical examples are given to illustrate the properties of the new observer and its advantages over existing observer design techniques in the literature
69 citations