Aloys Mvuma

Complex adaptive notch filter for detection of real sinusoid

This paper presents a new realization of adaptive notch filter based on a cascade of complex first-order notch filters. Unbiased frequency estimation of a real sinusoid has been achieved by thinning the notch bandwidth. It has been shown that the simple closed form of mean square error (MSE) for frequency estimation is given by using the results for first-order complex notch filter and its robustness to the frequency of input sinusoid has been shown. Computer simulation results are presented to validate the analysis.

Tracking properties of complex adaptive notch filter for detection of multiple real sinusoids

This paper presents a new realization of adaptive notch filter based on a cascade of adaptive IIR notch filters using complex coefficient first-order notch filters. The input is multiple real linear chirp signals embedded in a white Gaussian noise. Closed-form expression for frequency tracking mean square error (MSE) is given. Optimum step size parameter and notch bandwidth coefficient that minimize the tracking MSE are also derived. Computer simulation results are presented to validate the analysis.

Complex coefficient adaptive IIR notch filter tracking characteristics

This paper investigates tracking characteristics of a complex-coefficient adaptive infinite-impulse response (IIR) notch filter with a gradient-based algorithm. Two cases are investigated, i.e., linear chirp and randomly-varying frequency input complex signals buried in a complex zero-mean white Gaussian noise. First-order real-coefficient difference equations with respect to steady-state instantaneous frequency tracking error are derived. Closed-form expressions for frequency tracking mean square error (MSE) are derived from the difference equations. In addition, closed-form expressions for optimum notch bandwidth coefficient and step size constant are presented. Computer simulations are included to validate the analyses.

Frequency estimation of three-phase power systems using complex adaptive notch filters

This paper presents a new technique for adaptive estimation of the frequency of unbalanced three-phase power systems using complex coefficient first-order notch filters. The input complex sinusoid is given by a sum of sequences with positive and negative frequencies. Analytical expressions of mean square error due to an oscillating error introduced by the sequence with negative frequency and input noise have been derived. Closed form expression for frequency tracking error has been also derived. Computer simulation results are presented to validate the analysis.

Distributed Demand-side management with load uncertainty

In this paper, we consider load control in a multiple residence setup where energy consumption scheduling (ECS) devices in smart meters are employed for Demand-side management (DSM). Several residential end-users share the same energy source and each residential user has non adjustable loads, adjustable loads and a storage device. The ECS devices interact automatically by running an iterative distributed algorithm to find the optimal energy consumption schedule for each end-user, in order to reduce the total energy cost as well as the peak-to-average-ratio (PAR) in load demand in the system. Simulation results are provided to evaluate the performance of the proposed game theoretic based distributed DSM technique.

Complex adaptive notch filters for frequency estimation of three-phase power systems

This paper presents a new technique for adaptive estimation of the frequency of unbalanced three-phase power systems using complex coefficient first-order notch filters. The input complex sinusoid is given by a sum of sequences with positive and negative frequencies. The analytical expression of a estimation error oscillation introduced by the sequence with negative frequency has been derived. Closed form expression for frequency tracking error has been also derived for a complex linear chirp signal. Computer simulation results are presented to validate the analysis.

Autonomous demand-side optimization with load uncertainty

Demand-side management (DSM) will play an important role in balancing the energy distribution and demand in future smart grids. Indeed DSM is one of the important functions in a smart grid that allows customers to make informed decisions regarding their energy consumption, and help the energy providers reduce the peak load demand and reshape the load profile [1]-[4]. Achieving effective DSM is crucial to the success of the smart grid. The success of DSM programs mainly depends on how big a portion of the total energy load is controllable. Efficient DSM, promote immediate change of consumption by shifting or reducing load through incentives or pricing mechanisms [3]. In this article, we consider load control in a multiple residence setup, where energy consumption scheduler (ECS) devices in smart meters are employed for DSM. Several residential endusers share the same energy source and each residential user has non-adjustable loads, adjustable loads and a storage device. Residential users utilize ECS deployed inside their smart meters for the adjustable loads as well as charging and discharging of their storage devices. The smart meters with ECS functions interact automatically by running a centralized algorithm to find the optimal energy consumption schedule for each user in order to reduce the total energy cost as well as the peak-to-average-ratio (PAR) in load demands. The objective is to minimize the energy cost in the system as well as PAR. Simulation results demonstrate that our proposed scheme significantly reduces the PAR and the total cost of electricity.

A continuous-time adaptive notch filter: Transient and tracking analyses

This paper presents a state-space approach for implementation of a continuous-time adaptive notch filter with a gradient-based algorithm for a single sinusoid frequency estimation. Transient analysis of the proposed algorithm is carried out under the assumption of slow adaptation. Tracking characteristics are also investigated for linear chirp and sinusoidally-varying input signal frequency. Closed-form expressions for frequency tracking error for both cases are derived. Finally, simulation results are presented to verify the validity of the proposed algorithm and derived expressions.

Frequency and amplitude estimation of noncircular sinusoid using complex adaptive notch filters

In this paper, a technique for estimating frequency and amplitude of noncircular complex sinusoid has been presented. A cascade scheme of first-order complex notch filters has been introduced where complex sequence with negative frequency is rejected in the first section and sequence with positive frequency is removed in the second section. Closed-form expressions for bias and mean square error (MSE) for frequency estimation have been presented. By using band-pass outputs of first-order notch filters, amplitudes of sinusoidal sequences with positive and negative frequencies have been also estimated. Computer simulations show the effectiveness of the proposed analyses.

QPSK DS-CDMA System over Rayleigh Channel with a Randomly-Varying Frequency Narrow-Band Interference: Frequency Tracking Analysis

This paper analyses frequency tracking characteristics of a complex-coefficient adaptive infinite-impulse response (IIR) notch filter used for suppression of narrow-band interference (NBI) with a randomly-varying frequency in a quadriphase shift keying (QPSK) modulated direct-sequence code-division multiple-access (DS-CDMA) communication system. The QPSK DS-CDMA signals are transmitted over a frequency non-selective Rayleigh fading channel. The analysis is based on a first-order real-coefficient difference equation with respect to steady-state instantaneous frequency tracking error from which a closed-form expression that relates frequency tracking mean square error (MSE) with number of DS-CDMA active users and NBI power is obtained. Closed-form expressions for optimum notch bandwidth coefficient and step size constant that minimize the frequency tracking MSE are also derived. Computer simulations are included to substantiate the accuracy of the analyses.