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Full-Text Articles in Engineering
Performance Modeling And Optimization For A Fog-Based Iot Platform, Shensheng Tang
Performance Modeling And Optimization For A Fog-Based Iot Platform, Shensheng Tang
Electrical and Computer Engineering Faculty Publications
A fog-based IoT platform model involving three layers, i.e., IoT devices, fog nodes, and the cloud, was proposed using an open Jackson network with feedback. The system performance was analyzed for individual subsystems, and the overall system was based on different input parameters. Interesting performance metrics were derived from analytical results. A resource optimization problem was developed and solved to determine the optimal service rates at individual fog nodes under some constraint conditions. Numerical evaluations for the performance and the optimization problem are provided for further understanding of the analysis. The modeling and analysis, as well as the optimization design …
Recent Advances Of Wind-Solar Hybrid Renewable Energy Systems For Power Generation: A Review, Pranoy Roy, Jiangbiao He, Tiefu Zhao, Yash Veer Singh
Recent Advances Of Wind-Solar Hybrid Renewable Energy Systems For Power Generation: A Review, Pranoy Roy, Jiangbiao He, Tiefu Zhao, Yash Veer Singh
Electrical and Computer Engineering Faculty Publications
A hybrid renewable energy source (HRES) consists of two or more renewable energy sources, such as wind turbines and photovoltaic systems, utilized together to provide increased system efficiency and improved stability in energy supply to a certain degree. The objective of this study is to present a comprehensive review of wind-solar HRES from the perspectives of power architectures, mathematical modeling, power electronic converter topologies, and design optimization algorithms. Since the uncertainty of HRES can be reduced further by including an energy storage system, this paper presents several hybrid energy storage system coupling technologies, highlighting their major advantages and disadvantages. Various …
Cost Minimization Of Battery-Supercapacitor Hybrid Energy Storage For Hourly Dispatching Wind-Solar Hybrid Power System, Pranoy Roy, Jiangbiao He, Yuan Liao
Cost Minimization Of Battery-Supercapacitor Hybrid Energy Storage For Hourly Dispatching Wind-Solar Hybrid Power System, Pranoy Roy, Jiangbiao He, Yuan Liao
Electrical and Computer Engineering Faculty Publications
This study demonstrates a dispatching scheme of wind-solar hybrid power system (WSHPS) for a one-hour dispatching period for an entire day utilizing battery and supercapacitor hybrid energy storage subsystem (HESS). A frequency management approach is deployed to extend the longevity of the batteries through extensively utilizing the high energy density property of batteries and the high power density property of supercapacitors in the HESS framework. A low-pass filter (LPF) is employed to decouple the power between a battery and a supercapacitor (SC). The cost optimization of the HESS is computed based on the time constant of the LPF through extensive …
Design Optimization Of Coreless Axial-Flux Pm Machines With Litz Wire And Pcb Stator Windings, Murat G. Kesgin, Peng Han, Narges Taran, Damien Lawhorn, Donovin Lewis, Dan M. Ionel
Design Optimization Of Coreless Axial-Flux Pm Machines With Litz Wire And Pcb Stator Windings, Murat G. Kesgin, Peng Han, Narges Taran, Damien Lawhorn, Donovin Lewis, Dan M. Ionel
Electrical and Computer Engineering Faculty Publications
Coreless axial-flux permanent-magnet (AFPM) machines may be attractive options for high-speed and high-power-density applications due to the elimination of core losses. In order to make full use of the advantages offered by these machines and avoid excessive eddy current losses in windings, advanced technologies for winding conductors need to be employed to suppress the eddy effect, such as the Litz wire and printed circuit board (PCB). In this paper, the best practices for designing Litz wire/PCB windings are discussed and a brief survey of state of the art PCB winding technology is provided. Three coreless AFPM machines are mainly considered. …
Chaotic Phase-Coded Waveforms With Space-Time Complementary Coding For Mimo Radar Applications, Sheng Hong, Fuhui Zhou, Yantao Dong, Zhixin Zhao, Yuhao Wang, Maosong Yan
Chaotic Phase-Coded Waveforms With Space-Time Complementary Coding For Mimo Radar Applications, Sheng Hong, Fuhui Zhou, Yantao Dong, Zhixin Zhao, Yuhao Wang, Maosong Yan
Electrical and Computer Engineering Faculty Publications
A framework for designing orthogonal chaotic phase-coded waveforms with space-time complementary coding (STCC) is proposed for multiple-input multiple-output (MIMO) radar applications. The phase-coded waveform set to be transmitted is generated with an arbitrary family size and an arbitrary code length by using chaotic sequences. Due to the properties of chaos, this chaotic waveform set has many advantages in performance, such as anti-interference and low probability of intercept. However, it cannot be directly exploited due to the high range sidelobes, mutual interferences, and Doppler intolerance. In order to widely implement it in practice, we optimize the chaotic phase-coded waveform set from …
Biogeography-Based Optimization, Daniel J. Simon
Biogeography-Based Optimization, Daniel J. Simon
Electrical and Computer Engineering Faculty Publications
Biogeography is the study of the geographical distribution of biological organisms. Mathematical equations that govern the distribution of organisms were first discovered and developed during the 1960s. The mindset of the engineer is that we can learn from nature. This motivates the application of biogeography to optimization problems. Just as the mathematics of biological genetics inspired the development of genetic algorithms (GAs), and the mathematics of biological neurons inspired the development of artificial neural networks, this paper considers the mathematics of biogeography as the basis for the development of a new field: biogeography-based optimization (BBO). We discuss natural biogeography and …
H-Infinity Estimation For Fuzzy Membership Function Optimization, Daniel J. Simon
H-Infinity Estimation For Fuzzy Membership Function Optimization, Daniel J. Simon
Electrical and Computer Engineering Faculty Publications
Given a fuzzy logic system, how can we determine the membership functions that will result in the best performance? If we constrain the membership functions to a specific shape (e.g., triangles or trapezoids) then each membership function can be parameterized by a few variables and the membership optimization problem can be reduced to a parameter optimization problem. The parameter optimization problem can then be formulated as a nonlinear filtering problem. In this paper we solve the nonlinear filtering problem using H∞ state estimation theory. However, the membership functions that result from this approach are not (in general) sum normal. …
Data Smoothing And Interpolation Using Eighth-Order Algebraic Splines, Daniel J. Simon
Data Smoothing And Interpolation Using Eighth-Order Algebraic Splines, Daniel J. Simon
Electrical and Computer Engineering Faculty Publications
A new type of algebraic spline is used to derive a filter for smoothing or interpolating discrete data points. The spline is dependent on control parameters that specify the relative importance of data fitting and the derivatives of the spline. A general spline of arbitrary order is first formulated using matrix equations. We then focus on eighth-order splines because of the continuity of their first three derivatives (desirable for motor and robotics applications). The spline's matrix equations are rewritten to give a recursive filter that can be implemented in real time for lengthy data sequences. The filter is lowpass with …
Training Radial Basis Neural Networks With The Extended Kalman Filter, Daniel J. Simon
Training Radial Basis Neural Networks With The Extended Kalman Filter, Daniel J. Simon
Electrical and Computer Engineering Faculty Publications
Radial basis function (RBF) neural networks provide attractive possibilities for solving signal processing and pattern classification problems. Several algorithms have been proposed for choosing the RBF prototypes and training the network. The selection of the RBF prototypes and the network weights can be viewed as a system identification problem. As such, this paper proposes the use of the extended Kalman filter for the learning procedure. After the user chooses how many prototypes to include in the network, the Kalman filter simultaneously solves for the prototype vectors and the weight matrix. A decoupled extended Kalman filter is then proposed in order …
Sum Normal Optimization Of Fuzzy Membership Functions, Daniel J. Simon
Sum Normal Optimization Of Fuzzy Membership Functions, Daniel J. Simon
Electrical and Computer Engineering Faculty Publications
Given a fuzzy logic system, how can we determine the membership functions that will result in the best performance? If we constrain the membership functions to a certain shape (e.g., triangles or trapezoids) then each membership function can be parameterized by a small number of variables and the membership optimization problem can be reduced to a parameter optimization problem. This is the approach that is typically taken, but it results in membership functions that are not (in general) sum normal. That is, the resulting membership function values do not add up to one at each point in the domain. This …
Design And Rule Base Reduction Of A Fuzzy Filter For The Estimation Of Motor Currents, Daniel J. Simon
Design And Rule Base Reduction Of A Fuzzy Filter For The Estimation Of Motor Currents, Daniel J. Simon
Electrical and Computer Engineering Faculty Publications
Fuzzy systems have been used extensively and successfully in control systems over the past few decades, but have been applied much less often to filtering problems. This is somewhat surprising in view of the dual relationship between control and estimation. This paper discusses and demonstrates the application of fuzzy filtering to motor winding current estimation in permanent magnet synchronous motors. Motor winding current estimation is an important problem because in order to implement effective closed-loop control, a good estimation of the current is needed. Motor winding currents are notoriously noisy because of electrical noise in the motor drive. We use …
Applying Neural Networks To Find The Minimum-Cost Coverage Of A Boolean Function, Pong P. Chu
Applying Neural Networks To Find The Minimum-Cost Coverage Of A Boolean Function, Pong P. Chu
Electrical and Computer Engineering Faculty Publications
To find a minimal expression of a boolean function includes a step to select the minimum cost cover from a set of implicants. Since the selection process is an NP-complete problem, to find an optimal solution is impractical for large input data size. Neural network approach is used to solve this problem. We first formalize the problem, and then define an ''energy function'' and map it to a modified Hopfield network, which will automatically search for the minima. Simulation of simple examples shows the proposed neural network can obtain good solutions most of the time.
The Application Of Neural Networks To Optimal Robot Trajectory Planning, Daniel J. Simon
The Application Of Neural Networks To Optimal Robot Trajectory Planning, Daniel J. Simon
Electrical and Computer Engineering Faculty Publications
Interpolation of minimum jerk robot joint trajectories through an arbitrary number of knots is realized using a hardwired neural network. Minimum jerk joint trajectories are desirable for their similarity to human joint movements and their amenability to accurate tracking. The resultant trajectories are numerical rather than analytic functions of time. This application formulates the interpolation problem as a constrained quadratic minimization problem over a continuous joint angle domain and a discrete time domain. Time is discretized according to the robot controller rate. The neuron outputs define the joint angles (one neuron for each discrete value of time) and the Lagrange …
Two-Step Optimal Thermal Generation Scheduling, B Fardanesh, F. Eugenio Villaseca
Two-Step Optimal Thermal Generation Scheduling, B Fardanesh, F. Eugenio Villaseca
Electrical and Computer Engineering Faculty Publications
A new approach to the solution of the optimal thermal generation scheduling problem is presented. The problem is solved in two steps. As a first step, the optimal production schedule for the next day is obtained based on a daily load forecast, reserve capacity requirements, and present status of generating units. The second-step algorithm uses the results of the first step and adjusts the previous schedule to meet new constraints developed during the course of the day. Variable truncation dynamic programming is proposed as a new method to reduce computation effort. To eliminate the need for solving the …