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Full-Text Articles in Engineering
School Logo Cleveland State University Logo Title Evolutionary Optimization For Safe Navigation Of An Autonomous Robot In Cluttered Dynamic Unknown Environments, Arash Roshanineshat
School Logo Cleveland State University Logo Title Evolutionary Optimization For Safe Navigation Of An Autonomous Robot In Cluttered Dynamic Unknown Environments, Arash Roshanineshat
ETD Archive
We present a path planning approach based on probabilistic methods for a robot to navigate in a cluttered, dynamic, unknown environment. There are dynamic obstacles moving around and static obstacles located in the map. The robot does not have any prior information about them but should be able to navigate through the map beginning from a known starting point and safely ending at a known target point. The only information the robot has is the location of the starting point and the target point and it uses sensory information to collect information about its surroundings. Our method is compared to …
Evolutionary Optimization For Safe Navigation Of An Autonomous Robot In Cluttered Dynamic Unknown Environments, Arash Roshanineshat
Evolutionary Optimization For Safe Navigation Of An Autonomous Robot In Cluttered Dynamic Unknown Environments, Arash Roshanineshat
ETD Archive
We present a path planning approach based on probabilistic methods for a robot to navigate in a cluttered, dynamic, unknown environment. There are dynamic obstacles moving around and static obstacles located in the map. The robot does not have any prior information about them but should be able to navigate through the map beginning from a known starting point and safely ending at a known target point. The only information the robot has is the location of the starting point and the target point and it uses sensory information to collect information about its surroundings. Our method is compared to …
Oppositional Biogeography-Based Optimization, Mehmet Ergezer
Oppositional Biogeography-Based Optimization, Mehmet Ergezer
ETD Archive
This dissertation outlines a novel variation of biogeography-based optimization (BBO), which is an evolutionary algorithm (EA) developed for global optimization. The new algorithm employs opposition-based learning (OBL) alongside BBO migration to create oppositional BBO (OB BO). Additionally, a new opposition method named quasi-reflection is introduced. Quasireflection is based on opposite numbers theory and we mathematically prove that it has the highest expected probability of being closer to the problem solution among all OBL methods that we explore. Performance of quasi-opposition is validated by mathematical analysis for a single-dimensional problem and by simulations for higher dimensions. Experiments are performed on benchmark …
A Three-Dimensional Inverse Finite Element Analysis Of The Heel Pad, Snehal Chokhandre, Jason P. Halloran, Antonie J. Van Den Bogert, Ahmet Erdemir
A Three-Dimensional Inverse Finite Element Analysis Of The Heel Pad, Snehal Chokhandre, Jason P. Halloran, Antonie J. Van Den Bogert, Ahmet Erdemir
Mechanical Engineering Faculty Publications
Quantification of plantar tissue behavior of the heel pad is essential in developing computational models for predictive analysis of preventive treatment options such as footwear for patients with diabetes. Simulation based studies in the past have generally adopted heel pad properties from the literature, in return using heel-specific geometry with material properties of a different heel. In exceptional cases, patient-specific material characterization was performed with simplified two-dimensional models, without further evaluation of a heel-specific response under different loading conditions. The aim of this study was to conduct an inverse finite element analysis of the heel in order to calculate heel-specific …
Model Identification, Updating, And Validation Of An Active Magnetic Bearing High-Speed Machining Spindle For Precision Machining Operation, Adam C. Wroblewski
Model Identification, Updating, And Validation Of An Active Magnetic Bearing High-Speed Machining Spindle For Precision Machining Operation, Adam C. Wroblewski
ETD Archive
High-Speed Machining (HSM) spindles equipped with Active Magnetic Bearings (AMBs) are envisioned to be capable of autonomous self-identification and performance self-optimization for stable high-speed and high quality machining operation. High-speed machining requires carefully selected parameters for reliable and optimal machining performance. For this reason, the accuracy of the spindle model in terms of physical and dynamic properties is essential to substantiate confidence in its predictive aptitude for subsequent analyses.This dissertation addresses system identification, open-loop model development and updating, and closed-loop model validation. System identification was performed in situ utilizing the existing AMB hardware. A simplified, nominal open-loop rotor model was …
Optimization Of Basic And Reactive Dye Uptakes In Binary Dye Solution Using Statistical Experimental Methodology, Siew-Teng Ong, Weng-Nam Lee, Pei-Sin Keng, Siew-Ling Lee, Yung-Tse Hung
Optimization Of Basic And Reactive Dye Uptakes In Binary Dye Solution Using Statistical Experimental Methodology, Siew-Teng Ong, Weng-Nam Lee, Pei-Sin Keng, Siew-Ling Lee, Yung-Tse Hung
Civil and Environmental Engineering Faculty Publications
In the present study, the optimum adsorption conditions for the uptake of methylene blue (MB) and reactive orange 16 (RO16) in binary dye solution by ethylenediamine tetraacidic acid (EDTA) modified rice hulls was studied. By using the Plackett-Burman design, the significant variables in affecting the MB and RO16 uptake in binary dye solution were identified as pH and contact time. The combined effects of interaction between the variables were determined using response surface methodology (RSM). The model predicted that at optimum conditions: pH 6.77 and contact time of 205.58 min, the MB uptake greater than 95% could be obtained. As …
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 …