Design and implementation of a modified fourier analysis harmonic current computation technique for power active filters using DSPs

The design and implementation of a harmonic current computation technique based on a modified Fourier analysis, suitable for active power filters incorporating DSPs is presented. The proposed technique is suitable for the monitoring and control of load current harmonics for real-time applications. The derivation of the basic equations based on the proposed technique and the system implementation using the Analogue Devices SHARC processor are presented. The steady state and dynamic performance of the system are evaluated for a range of loading conditions

A computationally efficient frequency-domain filtered-X LMS algorithm for virtual microphone

The computational complexity of the virtual FXLMS algorithm is higher than that of the conventional FXLMS algorithm. The additional complexity comes from computation of three secondary path transfer functions (as opposed to one) and a transfer function between the physical and the virtual microphones. The order of these transfer functions may be very high in practical situations where the acoustic damping is low. The high computational complexity of the virtual FXLMS algorithm imposes issues like high power consumption, making it difficult to implement the algorithm in battery operated ANC devices such as active headsets. In addition, the operating sampling frequency of the algorithm is limited and this in turn restricts its operation to relatively low frequency applications. In this paper, a new virtual FXLMS algorithm is derived by implementing all of the secondary path transfer functions in the frequency domain. The algorithm is simulated using measured transfer functions in a duct with low acoustic damping. Implementation schemes are proposed for the new frequency-domain virtual FXLMS algorithm, citing its advantages for use as an efficient real-time active noise control algorithm. © 2013 Elsevier Ltd.Debi Prasad Das, Danielle J. Moreau, Ben S.Cazzolat

Reference signal generator for active power filters using MGP-FIR filter designed by evolutionary programming

This paper describes a high-performance reference signal generator for active power filters extracting the fundamental signal component from distorted current signals. In order to achieve high-quality output as well as computationally effective algorithm, the generator employs an adaptive and predictive MGP-FIR (Multiplicative General Parameter) bandpass filter designed by evolutionary programming. Detailed procedures of MGP-FIR filtering and evolutionary optimization are first discussed; theoretical conclusions are verified by illustrative simulation results.reviewe

Active vibration control systems in the frequency and sub-band domain.

Active noise and vibration control has been the subject of intense study in the last two decades due to the increased speed in digital signal processors and the technological development and manufacture of smart materials. This dissertation analyzes an active control system using adaptive digital signal processing techniques and applies it to the vibration reduction of hard disk drives (HDD). Specifically, this work focuses on the implementation of the adaptive algorithm in the frequency and sub-band domains for performance improvement.In this dissertation, selective adaptation in the frequency domain is proposed to alleviate the constructive interference associated with a feedback active control system. A new sub-band adaptive filter architecture without a signal path delay is proposed, and the associated adaptive algorithm is derived. This delayless sub-band algorithm can be applied to the active control systems to improve the convergence rate and trade-off the performance from the various sub-bands. The resulting side effect of the error path delay of the analysis filter bank is analyzed, and two compensation methods are proposed to increase the performance. The frequency domain method and the sub-band decomposition technique are then combined to improve the overall performance. The single-channel active control system is extended to the multiple-channel active control system to reduce the vibration of complex mechanical structure. The optimal performances of three variants of the feedback control system have been derived in terms of the correlation coefficients of the primary disturbances and the impulse responses of the secondary paths. Real time and simulation results are performed to verify the efficiency of the proposed algorithms and techniques

Performance Enhancement in Active Power Filter (APF) by FPGA Implementation

The generated electrical power in present days is not able to meet its end-user requirement as power demand is gradually increasing and expected to be increasing more in future days. In the power quality management, the parameters/factors like harmonic currents (HC) and reactive power (RP) yields the major issues in the power distribution units causing transformer heating, line losses, and machine vibration. To overcome these issues, several control mechanisms have been presented and implemented in recent past. The control algorithm based on synchronous reference frame (SRF) offers a better response by dividing the HC and RP. But the SRF based control algorithm requires better synchronization among the utility voltage and input current. To achieve this, the existing researches have used digital signal processing (DSP) and microcontroller, but these systems fail to provide better performance as they face issues like limited sampling time, less accuracy, and high computational complexity. Thus, to enhance the performance of active power filter (APF), we present an FPGA based approach. Also, to validate the performance of the proposed approach, we have used Xilinx 14.7 and Modelsim (6.3f) simulator and compared with other previous work. From the results analysis, it is found that the approach has good performance

Recent Technological Advances in Spatial Active Noise Control Systems

This article provides a broad overview of the recent advances in the field of active noise control techniques to reduce unwanted noise over a certain spatial region of interest. Thanks to commercial and technological advances in local active noise control systems extending the size of the quiet zone seems to be a crucial step to developing the next generation of active control systems for a more personalized and quieter audio product. In this review article, the advances over the past decade the in design and development of spatial active noise control techniques to enlarge the controlled sound zone is reviewed. The focus is specifically on the adaptive control techniques and the methods proposed in the frequency domain to control the sound field. The study has paid specific attention to the most important performance measures in designing a spatial active noise control system such as convergence rate, stability and robustness of the algorithm, the size of the quiet zone and how it can be enlarged by configuring the loudspeaker and microphone array geometries. Finally, the authors will discuss the current and future challenges that should be overcome to improve the effectiveness of the recently proposed methods to expand the silence zone

Active Noise Control in The New Century: The Role and Prospect of Signal Processing

Since Paul Leug's 1933 patent application for a system for the active control of sound, the field of active noise control (ANC) has not flourished until the advent of digital signal processors forty years ago. Early theoretical advancements in digital signal processing and processors laid the groundwork for the phenomenal growth of the field, particularly over the past quarter-century. The widespread commercial success of ANC in aircraft cabins, automobile cabins, and headsets demonstrates the immeasurable public health and economic benefits of ANC. This article continues where Elliott and Nelson's 1993 Signal Processing Magazine article and Elliott's 1997 50th anniversary commentary~\cite{kahrs1997past} on ANC left off, tracing the technical developments and applications in ANC spurred by the seminal texts of Nelson and Elliott (1991), Kuo and Morgan (1996), Hansen and Snyder (1996), and Elliott (2001) since the turn of the century. This article focuses on technical developments pertaining to real-world implementations, such as improving algorithmic convergence, reducing system latency, and extending control to non-stationary and/or broadband noise, as well as the commercial transition challenges from analog to digital ANC systems. Finally, open issues and the future of ANC in the era of artificial intelligence are discussed.Comment: Inter-Noise 202

Advancements of MultiRate Signal processing for Wireless Communication Networks: Current State Of the Art

With the hasty growth of internet contact and voice and information centric communications, many contact technologies have been urbanized to meet the stringent insist of high speed information transmission and viaduct the wide bandwidth gap among ever-increasing high-data-rate core system and bandwidth-hungry end-user complex. To make efficient consumption of the limited bandwidth of obtainable access routes and cope with the difficult channel environment, several standards have been projected for a variety of broadband access scheme over different access situation (twisted pairs, coaxial cables, optical fibers, and unchanging or mobile wireless admittance). These access situations may create dissimilar channel impairments and utter unique sets of signal dispensation algorithms and techniques to combat precise impairments. In the intended and implementation sphere of those systems, many research issues arise. In this paper we present advancements of multi-rate indication processing methodologies that are aggravated by this design trend. The thesis covers the contemporary confirmation of the current literature on intrusion suppression using multi-rate indication in wireless communiquE9; networks

A Review on Application of Artificial Intelligence Techniques in Microgrids

A microgrid can be formed by the integration of different components such as loads, renewable/conventional units, and energy storage systems in a local area. Microgrids with the advantages of being flexible, environmentally friendly, and self-sufficient can improve the power system performance metrics such as resiliency and reliability. However, design and implementation of microgrids are always faced with different challenges considering the uncertainties associated with loads and renewable energy resources (RERs), sudden load variations, energy management of several energy resources, etc. Therefore, it is required to employ such rapid and accurate methods, as artificial intelligence (AI) techniques, to address these challenges and improve the MG's efficiency, stability, security, and reliability. Utilization of AI helps to develop systems as intelligent as humans to learn, decide, and solve problems. This paper presents a review on different applications of AI-based techniques in microgrids such as energy management, load and generation forecasting, protection, power electronics control, and cyber security. Different AI tasks such as regression and classification in microgrids are discussed using methods including machine learning, artificial neural networks, fuzzy logic, support vector machines, etc. The advantages, limitation, and future trends of AI applications in microgrids are discussed.©2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.fi=vertaisarvioitu|en=peerReviewed