Engineering Commons^™

Compensation Of Torque Ripple In High Performance Bldc Motor Drives, Ilhwan Kim, Nobuaki Nakazawa, Sungsoo Kim, Chanwon Park, Chansu Yu

Electrical and Computer Engineering Faculty Publications

Brushless DC motor drives (BLDC) are finding expanded use in high performance applications where torque smoothness is essential. The nature of the square-wave current excitation waveforms in BLDC motor drives permits some important system simplifications compared to sinusoidal permanent magnet AC (PMAC) machines. However, it is the simplicity of the BLDC motor drive that is responsible for causing an additional source of ripple torque commonly known as commutation torque to develop. In this paper, a compensation technique for reducing the commutation torque ripple is proposed. With the experimental results, the proposed method demonstrates the effectiveness for a control …

Consideration Of Dispersion And Group Velocity Dispersion In The Determination Of Velocities Of Electromagnetic Propagation, Monish Ranjan Chatterjee, Partha P. Banerjee

Electrical and Computer Engineering Faculty Publications

Electromagnetic (EM) propagation velocities play an important role in the determination of power and energy flow in materials and interfaces. It is well known that group and phase velocities need to be in opposition in order to achieve negative refractive index.

Recently, we have shown that considerable differences may exist in phase, group and signal/energy velocities for normal and anomalous dispersion, especially near dielectric resonances. This paper examines the phase and group velocities in the presence of normal and anomalous dispersion, and group velocity dispersion (GVD), which requires introduction of the second order coefficient in the permittivity and permeability models.

Performance Measures In Acousto-Optic Chaotic Signal Encryption System Subject To Parametric Variations And Additive Noise, Monish Ranjan Chatterjee, Anjan K. Ghosh, Mohammed A. Al-Saedi

Electrical and Computer Engineering Faculty Publications

Signal encryption and recovery using chaotic optical waves has been a subject of active research in the past 10 years. Since an acousto-optic Bragg cell with zeroth- and first-order feedback exhibits chaotic behavior past the threshold for bistability, such a system was recently examined for possible chaotic encryption using a low-amplitude sinusoidal signal applied via the bias input of the sound cell driver.

Subsequent recovery of the message signal was carried out via a heterodyne strategy employing a locally generated chaotic carrier, with threshold parameters matched to the transmitting Bragg cell. The simulation results, though encouraging, were limited to relatively …

Kalman Filtering With State Constraints: A Survey Of Linear And Nonlinear Algorithms, Daniel J. Simon

Electrical and Computer Engineering Faculty Publications

The Kalman filter is the minimum-variance state estimator for linear dynamic systems with Gaussian noise. Even if the noise is non-Gaussian, the Kalman filter is the best linear estimator. For nonlinear systems it is not possible, in general, to derive the optimal state estimator in closed form, but various modifications of the Kalman filter can be used to estimate the state. These modifications include the extended Kalman filter, the unscented Kalman filter, and the particle filter. Although the Kalman filter and its modifications are powerful tools for state estimation, we might have information about a system that the Kalman filter …

Biogeography-Based Optimization With Blended Migration For Constrained Optimization Problems, Haiping Ma, Daniel J. Simon

Electrical and Computer Engineering Faculty Publications

Biogeography-based optimization (BBO) is a new evolutionary algorithm based on the science of biogeography. We propose two extensions to BBO. First, we propose blended migration. Second, we modify BBO to solve constrained optimization problems. The constrained BBO algorithm is compared with solutions based on a genetic algorithm (GA) and particle swarm optimization (PSO). Numerical results indicate that BBO generally performs better than GA and PSO in handling constrained single-objective optimization problems.

Biogeography-Based Optimization Of Neuro-Fuzzy System Parameters For Diagnosis Of Cardiac Disease, Mirela Ovreiu, Daniel J. Simon

Electrical and Computer Engineering Faculty Publications

Cardiomyopathy refers to diseases of the heart muscle that becomes enlarged, thick, or rigid. These changes affect the electrical stability of the myocardial cells, which in turn predisposes the heart to failure or arrhythmias. Cardiomyopathy in its two common forms, dilated and hypertrophic, implies enlargement of the atria; therefore, we investigate its diagnosis through P wave features. In particular, we design a neuro-fuzzy network trained with a new evolutionary algorithm called biogeography-based optimization (BBO). The neuro-fuzzy network recognizes and classifies P wave features for the diagnosis of cardiomyopathy. In addition, we incorporate opposition-based learning in the BBO algorithm for improved …

Analytic Confusion Matrix Bounds For Fault Detection And Isolation Using A Sum-Of-Squared-Residuals Approach, Daniel J. Simon, Donald L. Simon

Electrical and Computer Engineering Faculty Publications

Given a system which can fail in 1 of n different ways, a fault detection and isolation (FDI) algorithm uses sensor data to determine which fault is the most likely to have occurred. The effectiveness of an FDI algorithm can be quantified by a confusion matrix, also called a diagnosis probability matrix, which indicates the probability that each fault is isolated given that each fault has occurred. Confusion matrices are often generated with simulation data, particularly for complex systems. In this paper, we perform FDI using sum-of-squared residuals (SSRs). We assume that the sensor residuals are s-independent and Gaussian, which …

A Realistic Mobility Model For Wireless Networks Of Scale-Free Node Connectivity, Sunho Lim, Chansu Yu, Chita R. Das

Electrical and Computer Engineering Faculty Publications

Recent studies discovered that many of social, natural and biological networks are characterised by scale-free power-law connectivity distribution. We envision that wireless networks are directly deployed over such real-world networks to facilitate communication among participating entities. This paper proposes Clustered Mobility Model (CMM), in which nodes do not move randomly but are attracted more to more populated areas. Unlike most of prior mobility models, CMM is shown to exhibit scale-free connectivity distribution. Extensive simulation study has been conducted to highlight the difference between Random WayPoint (RWP) and CMM by measuring network capacities at the physical, link and network layers.

Signal Processing On Waveform Data From The Eyesafe Ladar Testbed (Elt), K.D. Neilsen, Scott E. Budge, R.T. Pack

Electrical and Computer Engineering Faculty Publications

The Eyesafe Ladar Test-bed (ELT) is a raster scanning, single-beam, energy-detection ladar with the capability of digitizing and recording the return pulse waveform at 2 GHz in the field for off-line 3D point cloud formation research in the laboratory. The ELT serves as a prime tool in understanding the behavior of ladar waveforms. Signal processing techniques have been applied to the ELT waveform in an effort to exploit the signal with respect to noise reduction, range resolution improvement, and ability to discriminate between two surfaces of similar range. This paper presents a signal processing method used on the ELT waveform. …

Classificiation Of Atrial Fibrillation Prone Patients Using Electrocardiographic Parameters In Neuro-Fuzzy Modeling,, Mirela Ovreiu, Marc Petre, Daniel J. Simon, Daniel Sessler, C Allen Bashour

Electrical and Computer Engineering Faculty Publications

Atrial Fibrillation (AF) is a significant clinical problem and the complications of cardiovascular postoperative AF often lead to longer hospital stays and higher heath care costs. The literature showed that AF may be preceded by changes in electrocardiogram (ECG) characteristics such as premature atrial activity, heart rate variability (HRV), and P-wave morphology. We hypothesize that the limitations of statistics-based attempts to predict AF occurrence may be overcome using a hybrid neuro-fuzzy prediction model that is better capable of uncovering complex, non-linear interactions between ECG parameters. We created a neuro-fuzzy network that was able to classify the patients into the control …

Constrained Kalman Filtering Via Density Function Truncation For Turbofan Engine Health Estimation, Daniel J. Simon, Donald L. Simon

Electrical and Computer Engineering Faculty Publications

Kalman filters are often used to estimate the state variables of a dynamic system. However, in the application of Kalman filters some known signal information is often either ignored or dealt with heuristically. For instance, state variable constraints (which may be based on physical considerations) are often neglected because they do not fit easily into the structure of the Kalman filter. This article develops an analytic method of incorporating state variable inequality constraints in the Kalman filter. The resultant filter truncates the probability density function (PDF) of the Kalman filter estimate at the known constraints and then computes the constrained …

A Majorization Algorithm For Constrained Correlation Matrix Approximation, Daniel J. Simon, Jeff Abell

Electrical and Computer Engineering Faculty Publications

We desire to find a correlation matrix of a given rank that is as close as possible to an input matrix R, subject to the constraint that specified elements in must be zero. Our optimality criterion is the weighted Frobenius norm of the approximation error, and we use a constrained majorization algorithm to solve the problem. Although many correlation matrix approximation approaches have been proposed, this specific problem, with the rank specification and the constraints, has not been studied until now. We discuss solution feasibility, convergence, and computational effort. We also present several examples.

Harvesting Single Ferroelectric Domain Stressed Nanoparticles For Optical And Ferroic Applications, Gary Cook, J. L. Barnes, S. A. Basun, Dean R. Evans, Ron F. Ziolo, Arturo Ponce, Victor Yu. Reshetnyak, Anatoliy Glushchenko, Partha P. Banerjee

Electrical and Computer Engineering Faculty Publications

We describe techniques to selectively harvest single ferroelectric domain nanoparticles of BaTiO3 as small as 9 nm from a plethora of nanoparticles produced by mechanical grinding. High resolution transmission electron microscopy imaging shows the unidomain atomic structure of the nanoparticles and reveals compressive and tensile surface strains which are attributed to the preservation of ferroelectric behavior in these particles.

We demonstrate the positive benefits of using harvested nanoparticles in disparate liquid crystal systems.

Super-Resolution Using Adaptive Wiener Filters, Russell C. Hardie

Electrical and Computer Engineering Faculty Publications

The spatial sampling rate of an imaging system is determined by the spacing of the detectors in the focal plane array (FPA). The spatial frequencies present in the image on the focal plane are band-limited by the optics. This is due to diffraction through a finite aperture. To guarantee that there will be no aliasing during image acquisiton, the Nyquist criterion dictates that the sampling rate must be greater than twice the cut-off frequency of the optics. However, optical designs involve a number of trade-offs and typical imaging systems are designed with some level of aliasing. We will refer to …

Characterization Of Atmospheric Turbulence Effects Over 149 Km Propagation Path Using Multi-Wavelength Laser Beacons, Mikhail Vorontsov, Gary W. Carhart, Venkata S. Rao Gudimetla, Thomas Weyrauch, Eric Stevenson, Svetlana Lachinova, Leonid A. Beresnev, Jony Jiang Liu, Karl Rehder, Jim F. Riker

Electrical and Computer Engineering Faculty Publications

We describe preliminary results of a set of laser beam propagation experiments performed over a long (149 km) near-horizontal propagation path between Mauna Loa (Hawaii Island) and Haleakala (Island of Maui) mountains in February 2010. The distinctive feature of the experimental campaign referred to here as the Coherent Multi-Beam Atmospheric Transceiver (COMBAT) experiments is that the measurements of the atmospheric-turbulence induced laser beam intensity scintillations at the receiver telescope aperture were obtained simultaneously using three laser sources (laser beacons) with different wavelengths (λ1 = 0.53 μm, λ2 = 1.06 μm, and λ3 = 1.55 μm). The presented experimental results on …