Rafael Cardoso

Kalman Filter-Based Control System for Power Quality Conditioning Devices

A new control scheme based on the Kalman filter and the linear quadratic regulator (LQR) is proposed to improve the performance of power quality conditioning devices. Grid perturbations such as load variations, frequency deviation, voltage distortion, line impedance, unbalance, and measurement noise are taken into account. A new model of the plant is developed that allows the use of the LQR controller with a better performance. This new controller structure is feasible thanks to an algorithm based on the Kalman filter (KF), which estimates the state space variables at the point of common coupling, used in the proposed control system. This algorithm is also responsible for generating the references for the controller. The proposed control system was implemented using a digital signal controller. Extensive tests and experimental results are presented in order to verify the performance of the proposal.

Estruturas de sincronismo monofásica e trifásica baseadas no filtro de Kalman

This paper proposes single-phase and three-phase synchronization methods based on the optimum filtering theory. The Kalman filter is used for the generation of the synchronization signals. The proposed methods incorporate, explicitly, in the problem formulation the presence of harmonics, voltage unbalance, measurement noise, transients and frequency deviation. These perturbations degrade the performance of many synchronization structures presented in literature. The formulation presented here makes the synchronization signals be less sensitive to these perturbations. It is also shown that the proposed methods can be helpfull to provide information about amplitude, instantaneous phase and frequency of the grid voltages, that can be usefull for purposes of power quality analysis. Furthermore, the Kalman filter provides a way to obtain a good compromise between transient response and measurement noise rejection for the synchronization signals. Experimental results using a DSP TMS320F2812 are presented to show the performance of the proposed schemes.

An energy based LQR tuning approach applied for Uninterruptible Power Supplies

This paper proposes a tuning method for a linear quadratic regulator (LQR) and its application to Uninterruptible Power Supplies (UPS). A performance index is established based on the desired behavior of system variables, such as maximum values permitted on the states and control law saturation. The tuning method is based on the Q and R weighting matrices, which relate the energy of the state variables involved on the process. From this index it is possible to find an optimal point to reach the required performance. The design procedure is exemplified with an output voltage control of an Uninterruptible Power Supply and dynamic results are presented.

In Vivo Pattern Classification of Ingestive Behavior in Ruminants Using FBG Sensors and Machine Learning.

Pattern classification of ingestive behavior in grazing animals has extreme importance in studies related to animal nutrition, growth and health. In this paper, a system to classify chewing patterns of ruminants in in vivo experiments is developed. The proposal is based on data collected by optical fiber Bragg grating sensors (FBG) that are processed by machine learning techniques. The FBG sensors measure the biomechanical strain during jaw movements, and a decision tree is responsible for the classification of the associated chewing pattern. In this study, patterns associated with food intake of dietary supplement, hay and ryegrass were considered. Additionally, two other important events for ingestive behavior were monitored: rumination and idleness. Experimental results show that the proposed approach for pattern classification is capable of differentiating the five patterns involved in the chewing process with an overall accuracy of 94%.

Grid Synchronization and Voltage Analysis Based on the Kalman Filter

This chapter deals with the problem of grid synchronization in the presence of several perturbations such as harmonics, voltage unbalance, measurement noise, transients and frequency deviation. The development of two synchronization structures is presented, one for single-phase systems and the other for three-phase systems. These schemes are based on the Kalman filter and all the aforementioned perturbations are incorporated, explicitly, in the problem formulation. A voltage analyser is also developed based on the three-phase synchronization structure.

In-vivo determination of chewing patterns using FBG and artificial neural networks

This paper reports the process of pattern classification of the chewing process of ruminants. We propose a simplified signal processing scheme for optical fiber Bragg grating (FBG) sensors based on machine learning techniques. The FBG sensors measure the biomechanical forces during jaw movements and an artificial neural network is responsible for the classification of the associated chewing pattern. In this study, three patterns associated to dietary supplement, hay and ryegrass were considered. Aditionally, two other important events for ingestive behavior studies were monitored, rumination and idle period. Experimental results show that the proposed approach for pattern classification has been capable of differentiating the materials involved in the chewing process with a small classification error.

Comparative analysis between FFT and Kalman filter approaches for harmonic components detection

This paper presents a numerical comparison between the FFT and the Kalman filter applied for harmonic components detection in different situation of the grid operation. Some pitfalls of the FFT are showed and the results are compared with the Kalman filter approach. It is considered signals with step changes in amplitude, frequency and phase. An analysis of these results is made demonstrating the better behavior of the Kalman filter approach in comparison to the FFT.

Robust Adaptive Controller Combined With a Linear Quadratic Regulator Based on Kalman Filtering

This work presents a control algorithm which incorporates a Reference Model Robust Adaptive Controller (RMRAC) and a Linear Quadratic Regulator based on Kalman Filtering (LQRKF) to obtain a high performance and robust control system. The adaptive portion of the controller deals with system uncertainties, while the optimum scheme, aided by a Kalman Filter, is designed to deal with harmonically related system disturbances. A proof of stability is presented in addition to a numerical example of the combined RMRAC - LQRKF controller to show the effectiveness of this new control approach.

Dynamic behavior of the PV Grid-connected inverter based on L and LCL filter with active damping control

PV Grid-connected inverters must fulfill the standards specifications of current harmonics injected to the grid. In order to satisfy these grid requirements, passive filters are connected between the inverter and the grid. This paper compares the response characteristic of the traditional inductive (L) filter with the inductive-capacitive-inductive (LCL) filter. It is shown that the increasing the inductance L leads to a good ripple current suppression around the inverter switch frequency. The LCL filter provides better harmonic attenuation and reduces the filter size. The main drawback is the LCL filter impedance, which is characterized by a typical resonance peak, which has to be damped to avoid instability. Passive or active techniques can be used to damp the LCL resonance. To address this issue, this paper presents a comparison of passive and active damping strategies. Experimental results are given to support the theoretical analysis and to illustrate the performance of grid connected PV inverter system.

Implementation of the IEEE Std 1459-2010 using Kalman filter for fundamental and harmonics detection

This paper presents an approach for the harmonic decomposition of voltage and current. This approach uses the Kalman filter combined with a frequency detection algorithm. It is applied to solving the power computations described in IEEE Std 1459-2010. The implementation of the filter is described and a comparison with the Fast Fourier Transform (FFT) is also provided. The paper also presents the results obtained using a free software developed using the QT framework which implements the power computations in accordance with IEEE Std 1459-2010.