Power Quality Improvement using a New DPC Switching Table for a Three-Phase SAPF

This research focuses on the analysis and design of robust direct power control (DPC) for a shunt active power filter (SAPF). The study proposes a novel switching table design based on an analysis of the impact of inverter switching vectors on the derivatives of instantaneous reactive and active powers. The goal is to reduce the number of commutations by eliminating null vectors while maintaining the desired DC-bus voltage using a PI regulator-based anti windup technique. Additionally, a robust PLL structure-based band pass multivariate filter (BPMVF) is utilized to enhance the network voltage. The research demonstrates the effectiveness of the suggested power control through extensive simulation results, showing high performance in both transient and steady-state conditions. The proposed approach offers the advantages of sinusoidal network current, and unitary power factor, and eliminates the need for current regulators and coordinate transformations or PWM generators. Further research directions could explore the practical implementation and real-world performance of this technique in power systems

Robust Voltage Vector-Controlled Three-Phase SAPF-based BPMVF and SVM for Power Quality Improvement

The multiplication of nonlinear loads leads to significant degradation of the energy quality, thus the interconnection network is subject to being polluted by the generation of harmonic components and reactive power, which causes a weakening efficiency, especially for the power factor. In three-phase systems, they can cause imbalances by causing excessive currents at the neutral. This research treats the operation of robust voltage-oriented control (VOC) for a shunt active power filter (SAPF). The main benefit of this technique is to guarantee a decoupled control of the active and reactive input currents, as well as the input reference voltage. To sustain the DC voltage, a robust PI-structure-based antiwindup is inserted to ensure active power control. Besides, a robust phase-locked loop (PLL)-based bandpass multivariable filter (BPMVF) is used to improve the network voltage quality. Furthermore, a space vector modulation (SVM) is designed to replace the conventional one. A sinusoidal network current and unitary power factor are achieved with fewer harmonics. The harmonics have been reduced from 27.98% to 1.55% which respects the IEEE 519-1992 standard. Expanded simulation results obtained from the transient and steady-state have demonstrated the high performance of the suggested control scheme

Design, optimization and Real Time implementation of a new Embedded Chien Search Block for Reed-Solomon (RS) and Bose-Chaudhuri-Hocquenghem (BCH) codes on FPGA Board

The development of error correcting codes has been a major concern for communications systems. Therefore, RS and BCH (Reed-Solomon and Bose, Ray-Chaudhuri and Hocquenghem) are effective methods to improve the quality of digital transmission. In this paper a new algorithm of Chien Search block for embedded systems is proposed. This algorithm is based on a factorization of error locator polynomial. i.e, we can minimize an important number of logic gates and hardware resources using the FPGA card. Consequently, it reduces the power consumption with a percentage which can reach 40 % compared to the basic RS and BCH decoder. The proposed system is designed, simulated using the hardware description language (HDL) and Quartus development software. Also, the performance of the designed embedded Chien search block for decoder RS\BCH (255, 239) has been successfully verified by implementation on FPGA board

A Robust Embedded Non-Linear Acoustic Noise Cancellation (ANC) Using Artificial Neural Network (ANN) for Improving the Quality of Voice Communications

Embedded Acoustic Noise Cancellation (ANC) has enjoyed remarkable success in the telecommunication field, and it becomes an essential component in various communications applications, such as digital transmission. So, it is an efficient method used to enhance the quality of communications against noise phenomena which is a problem in communication systems. This paper contributes towards a new non-linear embedded ANC based Artificial Neural Network (ANN) in digital signal processing and backpropagation (BP) of the gradient algorithm. This system is usually required for non-linear adaptive processing digital signals. The neuronal ANC estimates the noise path and subtracting noise from a received signal by minimizing a cost function. It is the mean square error. Thus, also the filter weights are adaptively updated. In this work, we designed and simulated our intelligent embedded ANC model with the help of MATLAB\Simulink software. The proposed system was designed by using embedded functions in Simulink. In addition, all simulation results are performed and verified using Signal Noise to Ratio (SNR) and Mean Square Error (MSE), number of iteration, neuronal architecture, criteria and it has been compared in various scenarios.  Finally, a study and analysis on convergence of neuronal ANC based backpropagation of the gradient algorithm demonstrate that our proposed system can effectively improve the quality of voice communications against the undesired noise. It also provides faster convergence during the back propagation of the gradient. Furthermore, the best values of SNR and MSE show the effectiveness of the proposed model