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Title: Cell-state-space-based fuzzy logic controller automatic design and optimization for high-order systems.
Creator: Song, Feijun., Florida Atlantic University, Smith, Samuel M., College of Engineering and Computer Science, Department of Ocean and Mechanical Engineering
Abstract/Description: Recent advances in computer engineering make the computational approaches to controller design for high order systems practical. In this dissertation, a series of computational methods based on cell state space for the design and optimization of Takagi-Sugeno (TS) type Fuzzy Logic Controllers (FLCs) are presented. The approaches proposed in this research can be classified into two categories: feed forward design and feedback design. An Optimal Control Table (OCT) based on cell state space is...
Show moreRecent advances in computer engineering make the computational approaches to controller design for high order systems practical. In this dissertation, a series of computational methods based on cell state space for the design and optimization of Takagi-Sugeno (TS) type Fuzzy Logic Controllers (FLCs) are presented. The approaches proposed in this research can be classified into two categories: feed forward design and feedback design. An Optimal Control Table (OCT) based on cell state space is used in all the feed forward design approaches. An FLC can be trained by Least Mean Square (LMS) algorithm with an OCT serving as the training set. For high order systems, due to physical memory limit, the cell resolution is generally low. A specially modified k-d tree representation of cell space is proposed to save the memory while keeping the cell resolution as high as possible. The control command for a point that is not a cell center is approximated by interpolating an OCT. All these commands can be used as training data to train an FLC. An iterative feedback design approach named Incremental Best Estimate Directed Search (IBEDS) is proposed to further optimize a training set. It is a kind of globally directed random search method. The general philosophy is that since the best possible performance of an FLC largely depends on the quality of the training set, if the training set is optimized, an FLC trained by the set would also be optimized. Based on IBEDS, two other feedback FLC design algorithms are also proposed. In one algorithm, subtractive clustering method is used to extract the structure of an FLC from an OCT. The coefficients of the FLC obtained are then optimized with IBEDS. The other algorithm applies IBEDS to three system models and finds the training set that has the worst performance for all the models. This training set is further optimized to improve robustness of a trained FLC.
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Date Issued: 1999
PURL: http://purl.flvc.org/fcla/dt/12608
Subject Headings: Fuzzy logic, Automatic control, Fuzzy systems
Format: Document (PDF)

Title: Implementation of a fuzzy logic controller for laser tracking system.
Creator: Wu, Xiaomin., Florida Atlantic University, Zhuang, Hanqi, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
Abstract/Description: With the strikingly fast development of industrial applications and research projects, control systems have become more and more complex than ever. Intelligent control techniques, featuring their being more robust and their availability when system mathematical models are unknown, have proven to be one of the most attractive and highlighted areas in the automatic control arena. This thesis concentrates first on the design of a laser tracking system. A standard design procedure of Fuzzy Logic...
Show moreWith the strikingly fast development of industrial applications and research projects, control systems have become more and more complex than ever. Intelligent control techniques, featuring their being more robust and their availability when system mathematical models are unknown, have proven to be one of the most attractive and highlighted areas in the automatic control arena. This thesis concentrates first on the design of a laser tracking system. A standard design procedure of Fuzzy Logic Controllers (FLCs) is followed, which is then realized in a PC-based environment in the design. An essential issue in this thesis study is the auto tuning of the Fuzzy Logic Controller. An efficient tuning method, mu-law functions, which can adjust both the shape and scaling gain of fuzzy controller's decision table is adopted. Also a search process called Downhill Simplex Search is chosen. Combining these two methods, a Simplex-mu-law auto-tuning algorithm that fits our application is applied to tune the FLC for the laser tracking system. Another issue covered in this research is to modify the Fuzzy Logic Controller structure by changing the distribution of the membership functions. Based on the analysis of the real time error histogram of the system, a novel method is proposed in the thesis for the modification of the membership functions To assess the effectiveness of the methods proposed in this thesis, a prototype laser tracking system is constructed at the FAU Robotics Center. The control strategy proposed in this thesis is tested extensively by simulations and experimentations on the prototype system.
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Date Issued: 1999
PURL: http://purl.flvc.org/fcla/dt/15717
Subject Headings: Fuzzy logic, Automatic control, Fuzzy systems
Format: Document (PDF)

Title: Application of fuzzy logic for the solution of inverse kinematics and hierarchical controls of robotic manipulators.
Creator: Howard, David William., Florida Atlantic University, Zilouchian, Ali
Abstract/Description: In this thesis work, hierarchical control techniques will be used for controlling a robotic manipulator. The hierarchical control will be implemented with fuzzy logic to improve the robustness and reduce the run time computational requirements. Hierarchical control will consist on solving the inverse kinematic equations using fuzzy logic to direct each individual joint. A commercial Micro-robot with three degrees of freedom will be used to evaluate this methodology. A decentralized fuzzy...
Show moreIn this thesis work, hierarchical control techniques will be used for controlling a robotic manipulator. The hierarchical control will be implemented with fuzzy logic to improve the robustness and reduce the run time computational requirements. Hierarchical control will consist on solving the inverse kinematic equations using fuzzy logic to direct each individual joint. A commercial Micro-robot with three degrees of freedom will be used to evaluate this methodology. A decentralized fuzzy controller will be used for each joint, with a Fuzzy Associative Memories (FAM) performing the inverse kinematic mapping in a supervisory mode. The FAM determines the inverse kinematic mapping which maps the desired Cartesian coordinates to the individual joint angles. The individual fuzzy controller for each joint will generate the required control signal to a DC motor to move the associated link to the new position. The proposed hierarchical fuzzy controller will be compared to a conventional PD controller.
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Date Issued: 1997
PURL: http://purl.flvc.org/fcla/dt/15407
Subject Headings: Robotics, Fuzzy logic, Robots--Kinematics
Format: Document (PDF)

Title: Automatic design of nonlinear controllers with optimal global performance using best estimate-directed search and continued propagation cell mapping.
Creator: Rizk, Charbel George., Florida Atlantic University, Smith, Samuel M., College of Engineering and Computer Science, Department of Ocean and Mechanical Engineering
Abstract/Description: The problem at hand is developing a controller design methodology that is generally applicable to autonomous systems with fairly accurate models. The controller design process has two parts: synthesis and analysis. Over the years, many synthesis and analysis methods have been proposed. An optimal method for all applications has not yet been found. Recent advances in computer technology have made computational methods more attractive and practical. The proposed method is an iterative...
Show moreThe problem at hand is developing a controller design methodology that is generally applicable to autonomous systems with fairly accurate models. The controller design process has two parts: synthesis and analysis. Over the years, many synthesis and analysis methods have been proposed. An optimal method for all applications has not yet been found. Recent advances in computer technology have made computational methods more attractive and practical. The proposed method is an iterative computational method that automatically generates non-linear controllers with specified global performance. This dissertation describes this method which consists of using an analysis tool, continued propagation cell mapping (CPCM), as feedback to the synthesis tool, best estimate directed search (BEDS). Optimality in the design can be achieved with respect to time, energy, and/or robustness depending on the performance measure used. BEDS is based on a novel search concept: globally directing a random search. BEDS has the best of two approaches: gradient (or directed) search and random search. It possesses the convergence speed of a gradient search and the convergence robustness of a random search. The coefficients of the best controller at the time direct the search process until either a better controller is found or the search is terminated. CPCM is a modification of simple cell mapping (SCM). CPCM maintains the simplicity of SCM but provides accuracy near that of a point map (PM). CPCM evaluates the controller's complete and global performance efficiently and with easily tunable accuracy. This CPCM evaluation guarantees monotonic progress in the synthesis process. The method is successfully applied to the design of a TSK-type fuzzy logic (FL) controller and a Sliding Mode-type controller for the uncertain non-linear system of an inverted pendulum on a cart for large pole angles (+/-86 degrees). The resulting controller's performance compares favorably to other established methods designed with dynamic programing (DP) and genetic algorithms (GA). When CPCM is used as feedback to BEDS, the resulting design method quickly and automatically generates non-linear controllers with good global performance and without much a priori information about the desired control actions.
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Date Issued: 1997
PURL: http://purl.flvc.org/fcla/dt/12523
Subject Headings: Nonlinear control theory, Cellular mappings, Fuzzy logic
Format: Document (PDF)

Title: Implementation of a fuzzy-logic-based trust model.
Creator: Zhao, Yuanhui., Florida Atlantic University, Zhuang, Hanqi, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
Abstract/Description: In the last 10 years, due to the rapid developments in computers and Internet, the Electronic Commerce has advanced significantly. More and more companies have shifted their businesses activities to the Internet. However, the popular use of ecommerce has also raised serious security problems. Therefore developing security schemes has become a key issue both in the academic as well as industrial research. Since the Internet is open to the public, the associated security issue is challenging. A...
Show moreIn the last 10 years, due to the rapid developments in computers and Internet, the Electronic Commerce has advanced significantly. More and more companies have shifted their businesses activities to the Internet. However, the popular use of ecommerce has also raised serious security problems. Therefore developing security schemes has become a key issue both in the academic as well as industrial research. Since the Internet is open to the public, the associated security issue is challenging. A good security strategy should not only protect the vendors' interest, but also enhance the mutual trust between vendors and customers. As a result, the people will feel more confident in conducting e-commerce. This thesis is dedicated to develop a fuzzy-logic based trust model. In general, the ecommerce transactions need costly verification and authentication process. In some cases, it is not cost effective to verify and authenticate each transaction, especially for transactions involving only small amount of money and for customers having an excellent transaction history. In view of this, in this research a model that distinguishes potentially safe transactions from unsafe transactions is developed. Only those potentially unsafe transactions need to be verified and authenticated. The model takes a number of fuzzy variables as inputs. However, this poses problems in constructing the trust table since the number of fuzzy rules will increase exponentially as the number of fuzzy variables increase. To make the problem more trackable, the variables are divided into several groups, two for each table. Each table will produce a decision on trust. The final decision is made based on the "intersection" of all these outputs. Simulation studies have been conducted to validate the effectiveness of the proposed trust model. Therefore simulations, however, need to be tested in a real business environment using real data. Relevant limitations on the proposed model are hence discussed and future research direction is indicated.
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Date Issued: 2001
PURL: http://purl.flvc.org/fcla/dt/12812
Subject Headings: Fuzzy logic, Electronic commerce--Security measures
Format: Document (PDF)

Title: Optimization and inductive models for continuous estimation of hydrologic variables.
Creator: Brown, Ricardo Eric., College of Engineering and Computer Science, Department of Civil, Environmental and Geomatics Engineering
Abstract/Description: This thesis develops methodologies for continuous estimation of hydrological variables which infill missing daily rainfall data and the forecast of weekly streamflows from a watershed. Several mathematical programming formulations were developed and used to estimate missing historical rainfall data. Functional relationships were created between radar precipitation and known rain gauge data then are used to estimate the missing data. Streamflow predictions models require highly non-linear...
Show moreThis thesis develops methodologies for continuous estimation of hydrological variables which infill missing daily rainfall data and the forecast of weekly streamflows from a watershed. Several mathematical programming formulations were developed and used to estimate missing historical rainfall data. Functional relationships were created between radar precipitation and known rain gauge data then are used to estimate the missing data. Streamflow predictions models require highly non-linear mathematical models to capture the complex physical characteristics of a watershed. An artificial neural network model was developed for streamflow prediction. There are no set methods of creating a neural network and the selection of architecture and inputs to a neural network affects the performance. This thesis addresses this issue with automated input and network architecture selection through optimization. MATLABª scripts are developed and used to test many combinations and select a model through optimization.
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Date Issued: 2012
PURL: http://purl.flvc.org/FAU/3342036
Subject Headings: Hydorlogic models, Mathematics, Fuzzy logic, Spatial analysis (Statistics), Stream measurements
Format: Document (PDF)

Title: Design and implementation of a control system for a laser-tracking measurement system.
Creator: Bai, Ying., Florida Atlantic University, Roth, Zvi S., Zhuang, Hanqi, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
Abstract/Description: To assess and evaluate the performance of robots and machine tools dynamically, it is desirable to have a precision measuring device that performs dynamic measurement of end-effector positions of such robots and machine tools. Among possible measurement techniques, Laser Tracking Systems (LTSs) exlnbit the capability of high accuracy, large workspace, high sampling rate, and automatic target-tracking,. and thus are well-suited for robot calibration both kinematically and dynamically. In this...
Show moreTo assess and evaluate the performance of robots and machine tools dynamically, it is desirable to have a precision measuring device that performs dynamic measurement of end-effector positions of such robots and machine tools. Among possible measurement techniques, Laser Tracking Systems (LTSs) exlnbit the capability of high accuracy, large workspace, high sampling rate, and automatic target-tracking,. and thus are well-suited for robot calibration both kinematically and dynamically. In this dissertation, the design and implementation of a control system for a homemade laser tracking measurement systems is addressed and calibration of a robot using the laser tracking system is demonstrated Design and development of a control system for a LTS is a challenging task. It involves a deep understanding of laser interferometry,. controls, mechanics and optics,. both in theoretical perspective and in implementation aspect. One of the most important requirements for a successful design and implementation of a control system for the LTS is proper installation and alignment of the laser and optical system,. or laser transducer system. The precision of measurement using the LTS depends highly on the accuracy of the laser transducer system, as well as the accuracy of the installation and alignment of the optical system. Hence, in reference to the experimental alignment method presented in this dissertation, major error sources affecting the system measurement accuracy are identified and analyzed. A manual compensation method is developed to eliminate the effects of these error sources effectively in the measurement system. Considerations on proper design and installation of laser and optical components are indicated in this dissertation. As a part of the conventional control system design, a dynamic system model of the LTS is required. In this study, a detailed derivation and analysis of the dynamic model of the motor gimbal system using Lagrange-Euler equations of motion is developed for both ideal and complete gimbal systems. Based on this system model,. a conventional controller is designed. Fuzzy Logic Controllers (FLC) are designed in order to suppress noise or disturbances that exist in the motor driver subsystem. By using the relevant control strategies. noise and disturbances present in the electrical control channels are shown to reduce significantly. To improve the system performance further, a spectrum analysis of the error sources and disturbances existing in the system is conducted. Major noise sources are effectively suppressed by using a two-stage fuzzy logic control strategy. A comparison study on the performances of different control strategies is given in this dissertation, in reference to the following: An ideal system model, a system with a long time delay, a system with various noise sources and a system model with uncertainties. Both simulation and experimental results are furnished to illustrate the advantages of the FLC in respect of its transient response, steady-state response, and tracking performance. Furthermore, noise reduction in the laser tracking system is demonstrated. Another important issue concerning a successful application of the LTS in the calibration of a robot is the estimation of system accuracy. Hence, a detailed analysis of system accuracy of the LTS is presented in this worL This analysis is also verified by experimental methods by means of tracking a Coordinate Measuring Machine available in the FAU Robotics Center. Using the developed LTS, a PUMA robot in the FAU Robotics Center is calibrated. The results obtained are confirmative with the data available in the literature. In summary, the proposed methodology towards the design and implementation of a control system for LTSs has been shown to be successful by performing experimental tracking and calibration studies at the FAU Robotics Center.
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Date Issued: 2000
PURL: http://purl.flvc.org/fcla/dt/12622
Subject Headings: Robots--Calibration, Robots--Control systems, Fuzzy logic
Format: Document (PDF)

Title: Obstacle avoidance for AUVs.
Creator: Gan, (Linda) Huilin., Florida Atlantic University, Ganesan, Krishnamurthy
Abstract/Description: This thesis describes a general three-dimensional Obstacle Avoidance approach for the Autonomous Underwater Vehicle (AUV) using a forward-looking high-frequency active sonar system. This approach takes into account obstacle distance and AUV speed to determine the vehicle's heading, depth and speed. Fuzzy logic has been used to avoid the abrupt turn of the AUV in the presence of obstacles so that the vehicle can maneuver smoothly in the underwater environment. This approach has been...
Show moreThis thesis describes a general three-dimensional Obstacle Avoidance approach for the Autonomous Underwater Vehicle (AUV) using a forward-looking high-frequency active sonar system. This approach takes into account obstacle distance and AUV speed to determine the vehicle's heading, depth and speed. Fuzzy logic has been used to avoid the abrupt turn of the AUV in the presence of obstacles so that the vehicle can maneuver smoothly in the underwater environment. This approach has been implemented as an important part of the overall AUV software system. Using this approach, multiple objects could be differentiated automatically by the program through analyzing the sonar returns. The current vehicle state and the path of navigation of the AUV are self-adjusted depending on the location of the obstacles that are detected. A minimum safety distance is always maintained between the AUV and any object. Extensive testing of the program has been performed using several simulated AUV on-board systems undergoing different types of missions.
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Date Issued: 1997
PURL: http://purl.flvc.org/fcla/dt/15451
Subject Headings: Submersibles--Automatic control, Fuzzy logic, Neural networks (Computer science)
Format: Document (PDF)

Title: Design and tuning of fuzzy control surface with Bezier functions.
Creator: Wongsoontorn, Songwut., Florida Atlantic University, Zhuang, Hanqi, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
Abstract/Description: Design and Tuning a fuzzy logic controller (FLCs) are usually done in two stages. In the first stage, the structure of a FLC is determined based on physical characteristics of the system. In the second stage, the parameters of the FLC are selected to optimize the performance of the system. The task of tuning FLCs can be performed by a number of methods such as adjusting control gains, changing membership functions, modifying control rules and varying control surfaces. A method for the design...
Show moreDesign and Tuning a fuzzy logic controller (FLCs) are usually done in two stages. In the first stage, the structure of a FLC is determined based on physical characteristics of the system. In the second stage, the parameters of the FLC are selected to optimize the performance of the system. The task of tuning FLCs can be performed by a number of methods such as adjusting control gains, changing membership functions, modifying control rules and varying control surfaces. A method for the design and tuning of FLCs through modifying their control surfaces is presented in this dissertation. The method can be summarized as follows. First, fuzzy control surfaces are modeled with Bezier functions. Shapes of the control surface are then adjusted through varying Bezier parameters. A Genetic Algorithm (GA) is used to search for the optimal set of parameters based on the control performance criteria. Then, tuned control surfaces are sampled to create rule-based FLCs. To further improve the system performance, continuity constraints of the curves are imposed. Under the continuity constraints with the same number of tunable parameters, one can obtain more flexible curves that have the potential to improve the overall system performance. An important issue is to develop a new method to self-tune a fuzzy PD controller. The method is based on two building blocks: (I) Bezier functions used to model the control surfaces of the fuzzy PD controller; and, shapes of control surfaces are then adjusted by varying Bezier parameters. (II) The next step involves using a gradient-based optimization algorithm with which the input scaling factors and Bezier parameters are on-line tuned until the controller drives the output of the process as close as possible to the reference position. To protect vendors and consumers from being victimized, various trust models have been used in e-commerce practices. However, a strict verification and authentication process may pose unnecessary heavy cost to the vendor. As an application of the control strategy proposed, this dissertation presents a solution to the reduction of costs of a vendor. With two fuzzy variables (price, credit-history), a trust-surface can be tuned to achieve an optimal solution in terms of profit margin of the vendor. With this new approach, more realistic trust decisions can be reached.
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Date Issued: 2005
PURL: http://purl.flvc.org/fcla/dt/12172
Subject Headings: Fuzzy systems, Nonlinear control theory, Process control--Data processing, Fuzzy logic, Intelligent control systems
Format: Document (PDF)

Title: Fuzzy logic techniques for software reliability engineering.
Creator: Xu, Zhiwei., Florida Atlantic University, Khoshgoftaar, Taghi M., College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
Abstract/Description: Modern people are becoming more and more dependent on computers in their daily lives. Most industries, from automobile, avionics, oil, and telecommunications to banking, stocks, and pharmaceuticals, require computers to function. As the tasks required become more complex, the complexity of computer software and hardware has increased dramatically. As a consequence, the possibility of failure increases. As the requirements for and dependence on computers increases, the possibility of crises...
Show moreModern people are becoming more and more dependent on computers in their daily lives. Most industries, from automobile, avionics, oil, and telecommunications to banking, stocks, and pharmaceuticals, require computers to function. As the tasks required become more complex, the complexity of computer software and hardware has increased dramatically. As a consequence, the possibility of failure increases. As the requirements for and dependence on computers increases, the possibility of crises caused by computer failures also increases. High reliability is an important attribute for almost any software system. Consequently, software developers are seeking ways to forecast and improve quality before release. Since many quality factors cannot be measured until after the software becomes operational, software quality models are developed to predict quality factors based on measurements collected earlier in the life cycle. Due to incomplete information in the early life cycle of software development, software quality models with fuzzy characteristics usually perform better because fuzzy concepts deal with phenomenon that is vague in nature. This study focuses on the usage of fuzzy logic in software reliability engineering. Discussing will include the fuzzy expert systems and the application of fuzzy expert systems in early risk assessment; introducing the interval prediction using fuzzy regression modeling; demonstrating fuzzy rule extraction for fuzzy classification and its usage in software quality models; demonstrating the fuzzy identification, including extraction of both rules and membership functions from fuzzy data and applying the technique to software project cost estimations. The following methodologies were considered: nonparametric discriminant analysis, Z-test and paired t-test, neural networks, fuzzy linear regression, fuzzy nonlinear regression, fuzzy classification with maximum matched method, fuzzy identification with fuzzy clustering, and fuzzy projection. Commercial software systems and the COCOMO database are used throughout this dissertation to demonstrate the usefulness of concepts and to validate new ideas.
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Date Issued: 2001
PURL: http://purl.flvc.org/fcla/dt/11948
Subject Headings: Software engineering, Fuzzy logic, Computer software--Quality control, Fuzzy systems
Format: Document (PDF)

Title: Geographic Routing Reliability Enhancement in Urban Vehicular Ad Hoc Networks.
Creator: Alzamzami, Ohoud, Mahgoub, Imad, Florida Atlantic University, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
Abstract/Description: Vehicular Ad hoc Networks (VANETs) have the potential to enable various kinds of applications aiming at improving road safety and transportation efficiency. These applications require uni-cast routing, which remains a significant challenge due to VANETs characteristics. Given VANET dynamic topology, geographic routing protocols are considered the most suitable for such network due to their scalability and low overhead. However, the optimal selection of next-hop nodes in geographic routing is...
Show moreVehicular Ad hoc Networks (VANETs) have the potential to enable various kinds of applications aiming at improving road safety and transportation efficiency. These applications require uni-cast routing, which remains a significant challenge due to VANETs characteristics. Given VANET dynamic topology, geographic routing protocols are considered the most suitable for such network due to their scalability and low overhead. However, the optimal selection of next-hop nodes in geographic routing is a challenging problem where the routing performance is highly affected by the variable link quality and bandwidth availability. In this dissertation, a number of enhancements to improve geographic routing reliability in VANETs are proposed. To minimize packet losses, the direction and link quality of next-hop nodes using the Expected Transmission Count (ETX) are considered to select links with low loss ratios. To consider the available bandwidth, a cross-layer enchantment of geographic routing, which can select more reliable links and quickly react to varying nodes load and channel conditions, is proposed. We present a novel model of the dynamic behavior of a wireless link. It considers the loss ratio on a link, in addition to transmission and queuing delays, and it takes into account the physical interference e ect on the link. Then, a novel geographic routing protocol based on fuzzy logic systems, which help in coordinating di erent contradicting metrics, is proposed. Multiple metrics related to vehicles' position, direction, link quality and achievable throughput are combined using fuzzy rules in order to select the more reliable next-hop nodes for packet forwarding. Finally, we propose a novel link utility aware geographic routing protocol, which extends the local view of the network topology using two-hop neighbor information. We present our model of link utility, which measures the usefulness of a two-hop neighbor link by considering its minimum residual bandwidth and packet loss rate. The proposed protocol can react appropriately to increased network tra c and to frequent topology dis-connectivity in VANETs. To evaluate the performance of the proposed protocols, extensive simulation experiments are performed using network and urban mobility simulation tools. Results confirm the advantages of the proposed schemes in increased traffic loads and network density.
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Date Issued: 2018
PURL: http://purl.flvc.org/fau/fd/FA00013037
Subject Headings: Vehicular ad hoc networks (Computer networks), Traffic safety, Routing protocols (Computer network protocols), Fuzzy logic
Format: Document (PDF)

Title: A novel NN paradigm for the prediction of hematocrit value during blood transfusion.
Creator: Thakkar, Jay., College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
Abstract/Description: During the Leukocytapheresis (LCAP) process used to treat patients suffering from acute Ulcerative Colitis, medical practitioners have to continuously monitor the Hematocrit (Ht) level in the blood to ensure it is within the acceptable range. The work done, as a part of this thesis, attempts to create an early warning system that can be used to predict if and when the Ht values will deviate from the acceptable range. To do this we have developed an algorithm based on the Group Method of Data...
Show moreDuring the Leukocytapheresis (LCAP) process used to treat patients suffering from acute Ulcerative Colitis, medical practitioners have to continuously monitor the Hematocrit (Ht) level in the blood to ensure it is within the acceptable range. The work done, as a part of this thesis, attempts to create an early warning system that can be used to predict if and when the Ht values will deviate from the acceptable range. To do this we have developed an algorithm based on the Group Method of Data Handling (GMDH) and compared it to other Neural Network algorithms, in particular the Multi Layer Perceptron (MLP). The standard GMDH algorithm captures the fluctuation very well but there is a time lag that produces larger errors when compared to MLP. To address this drawback we modified the GMDH algorithm to reduce the prediction error and produce more accurate results.
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Date Issued: 2011
PURL: http://purl.flvc.org/FAU/3174078
Subject Headings: Neural networks (Computer science), Scientific applications, GMDH algorithms, Pattern recognition systems, Genetic algorithms, Fuzzy logic
Format: Document (PDF)

Title: Smart Adaptive Beaconing Schemes for VANET.
Creator: Alhameed, Mohammed, Mahgoub, Imad, Florida Atlantic University, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
Abstract/Description: Vehicular Ad hoc Networks (VANET) is a wireless ad-hoc network that includes two types of communications, Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I). In VANET there are two types of messages. The first type is the event-driven messages that are only triggered in case of emergency. The second type is the periodical messages named beacons that are exchanged frequently between vehicles. A beacon message contains basic information about the sending vehicle such as id, location...
Show moreVehicular Ad hoc Networks (VANET) is a wireless ad-hoc network that includes two types of communications, Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I). In VANET there are two types of messages. The first type is the event-driven messages that are only triggered in case of emergency. The second type is the periodical messages named beacons that are exchanged frequently between vehicles. A beacon message contains basic information about the sending vehicle such as id, location and velocity. Beacons are frequently exchanged to increase the cooperative awareness between vehicles. Increasing beacon frequency helps increasing neighborhood awareness and improving information accuracy. However, this causes more congestion in the network, specially when the number of vehicles increases. On the other hand, reducing beacon frequency alleviates network congestion, but results in out-dated information. In this dissertation, we address the aforementioned challenges and propose a number of smart beaconing protocols and evaluate their performance in di↵erent environments and network densities. The four adaptive beaconing protocols are designed to increase the cooperative awareness and information freshness, while alleviating the network congestion. All the proposed protocols take into account the most important aspects, which are critical to beaconing rate adaptation. These aspects include channel status, traffic conditions and link quality. The proposed protocols employ fuzzy logic-based techniques to determine the congestion rank, which is used to adjust beacon frequency. The first protocol considers signal to interference-noise ratio (SINR), number of neighboring nodes and mobility to determine the congestion rank and adjust the beacon rate accordingly. This protocol works well in sparse conditions and highway environments. The second protocol works well in sparse conditions and urban environments. It uses channel busy time (CBT), mobility and packet delivery ratio (PDR) to determine the congestion rank and adjust the beacon rate. The third protocol utilizes CBT, SINR, PDR, number of neighbors and mobility as inputs for the fuzzy logic system to determine the congestion rank and adjust the beacon rate. This protocol works well in dense conditions in both highway and urban environments. Through extensive simulation experiments, we established that certain input parameters are more e↵ective in beacon rate adaptation for certain environments and conditions. Based on this, we propose a high awareness and channel efficient scheme that adapts to di↵erent environments and conditions. First, the protocol estimates the network density using adaptive threshold function. Then, it looks at the spatial distribution of nodes using the quadrat method to determine whether the environment is highway or urban. Based on the density conditions and nodes distribution, the protocol utilizes the appropriate fuzzy input parameters to adapt the beaconing rate. In addition, the protocol optimizes the performance by adapting the transmission power based on network density and nodes distribution. Finally, an investigation of the impact of adaptive beaconing on broadcasting is conducted. The simulation results confirm that our adaptive beaconing scheme can improve performance of the broadcast protocols in terms of reachability and bandwidth consumption when compared to a fixed rate scheme.
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Date Issued: 2018
PURL: http://purl.flvc.org/fau/fd/FA00013112
Subject Headings: Vehicular ad hoc networks (Computer networks), Beacons, Fuzzy logic, Adaptive computing systems
Format: Document (PDF)

Title: Classification of marine sediments using a fuzzy logic impedance inversion model.
Creator: DeBruin, Darryl L., Florida Atlantic University, LeBlanc, Lester R., College of Engineering and Computer Science, Department of Ocean and Mechanical Engineering
Abstract/Description: In this dissertation, a fuzzy logic impedance inversion model is developed to classify marine sediments. Expert knowledge and fuzzy decision making constrain the inversion procedures to the resolving ability of the transmitted. The model is validated by comparing the estimated impedance profile with the measured impedance profile. A coherent surface scattering and incoherent volume scattering model are incorporated into a single geoacoustic scattering model that is applied to acoustic...
Show moreIn this dissertation, a fuzzy logic impedance inversion model is developed to classify marine sediments. Expert knowledge and fuzzy decision making constrain the inversion procedures to the resolving ability of the transmitted. The model is validated by comparing the estimated impedance profile with the measured impedance profile. A coherent surface scattering and incoherent volume scattering model are incorporated into a single geoacoustic scattering model that is applied to acoustic subbottom measurements. The reflected signal is modeled as the convolution of the transmitted processed wavelet and the impulse response of the sea bottom. The impedance of the acoustic return is inverted at the layer interfaces and the volume scattering strength is measured between layer interfaces. The model is applied to acoustic subbottom measurements obtained by an X-STAR subbottom profiler sonar system. The inversion techniques are developed for a 2-10 kHz 20 msec swept FM pulse. A fuzzy logic layer tracking procedure identifies the coherent surface scattering layer interfaces in a subbottom profile image. The peak amplitudes and locations are used as fuzzy inputs in the layer tracking rule base. The rule base determines which peak is assigned to the layer when two peaks compete for assignment or which layer is assigned to the peak when two layers compete for assignment. The fuzzy event detection algorithm estimates the impulse response of the acoustic return by complex least squares fitting parts of the transmitted wavelet with sections of the acoustic return. Reflectors are iteratively identified and removed from the return and the residual return is reprocessed. The detection procedure is constrained by the resolving ability of the matching signals and the peak envelope shape of the acoustic return. A genetic algorithm allows up to five low error reflector estimates to be processed until converging on the correct estimated impulse response (the tree branch whose summed error is minimized). The impedance is correlated with sediment bulk density by empirical relation. Experimental results validate that the fuzzy logic impedance inversion model reliably estimates the impedance of the sea bottom. The estimated impedance profiles of fifty acoustic returns are averaged and compared with measured impedance values.
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Date Issued: 1995
PURL: http://purl.flvc.org/fcla/dt/12415
Subject Headings: Fuzzy logic, Marine sediments, Acoustic impedance, Marine sediments--Acoustic properties
Format: Document (PDF)

Title: A connectionist approach to adaptive reasoning: An expert system to predict skid numbers.
Creator: Reddy, Mohan S., Florida Atlantic University, Pandya, Abhijit S., College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
Abstract/Description: This project illustrates the neural network approach to constructing a fuzzy logic decision system. This technique employs an artificial neural network (ANN) to recognize the relationships that exit between the various inputs and outputs. An ANN is constructed based on the variables present in the application. The network is trained and tested. Various training methods are explored, some of which include auxiliary input and output columns. After successful testing, the ANN is exposed to new...
Show moreThis project illustrates the neural network approach to constructing a fuzzy logic decision system. This technique employs an artificial neural network (ANN) to recognize the relationships that exit between the various inputs and outputs. An ANN is constructed based on the variables present in the application. The network is trained and tested. Various training methods are explored, some of which include auxiliary input and output columns. After successful testing, the ANN is exposed to new data and the results are grouped into fuzzy membership sets based membership evaluation rules. This data grouping forms the basis of a new ANN. The network is now trained and tested with the fuzzy membership data. New data is presented to the trained network and the results form the fuzzy implications. This approach is used to compute skid resistance values from G-analyst accelerometer readings on open grid bridge decks.
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Date Issued: 1996
PURL: http://purl.flvc.org/fcla/dt/15239
Subject Headings: Artificial intelligence, Fuzzy logic, Neural networks (Computer science), Pavements--Skid resistance
Format: Document (PDF)

Title: Fuzzy identification of processes on finite training sets with known features.
Creator: Diaz-Robainas, Regino R., Florida Atlantic University, Huang, Ming Z., Zilouchian, Ali, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
Abstract/Description: A methodology is presented to construct an approximate fuzzy-mapping algorithm that maps multiple inputs to single outputs given a finite training set of argument vectors functionally linked to corresponding scalar outputs. Its scope is limited to problems where the features are known in advance, or equivalently, where the expected functional representation is known to depend exclusively on the known selected variables. Programming and simulations to implement the methodology make use of...
Show moreA methodology is presented to construct an approximate fuzzy-mapping algorithm that maps multiple inputs to single outputs given a finite training set of argument vectors functionally linked to corresponding scalar outputs. Its scope is limited to problems where the features are known in advance, or equivalently, where the expected functional representation is known to depend exclusively on the known selected variables. Programming and simulations to implement the methodology make use of Matlab Fuzzy and Neural toolboxes and a PC application of Prolog, and applications range from approximate representations of the direct kinematics of parallel manipulators to fuzzy controllers.
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Date Issued: 1996
PURL: http://purl.flvc.org/fcla/dt/12487
Subject Headings: Fuzzy algorithms, Set theory, Logic, Symbolic and mathematical, Finite groups, Representations of groups
Format: Document (PDF)

Title: Lifeline structures under earthquake excitations.
Creator: Reddy, Kondakrindhi Praveen., Florida Atlantic University, Yong, Yan, College of Engineering and Computer Science, Department of Ocean and Mechanical Engineering
Abstract/Description: An analytical method is proposed for the response analysis of lifeline structures subjected to earthquake excitations. The main feature of the approach is to consider the vibrational motion as a result of the wave motion in a waveguide-like lifeline structure. Based on the theory of wave propagation, scattering matrices are derived to characterize the wave propagation in individual segments and wave reflections and transmissions at supports and boundaries. Response solution is derived in a...
Show moreAn analytical method is proposed for the response analysis of lifeline structures subjected to earthquake excitations. The main feature of the approach is to consider the vibrational motion as a result of the wave motion in a waveguide-like lifeline structure. Based on the theory of wave propagation, scattering matrices are derived to characterize the wave propagation in individual segments and wave reflections and transmissions at supports and boundaries. Response solution is derived in a closed form, suitable for stochastic analysis when the input is an earthquake excitation. A space-time earthquake ground motion model that accounts for both coherent decay and seismic wave propagation is used to specify motions at supports. The proposed technique can be used to obtain lifeline structural response accurately and determine the correlation between any two locations in an effective manner. The computational aspects of its implementation are also discussed. Numerical examples are presented to illustrate the application and efficiency of the proposed analytical scheme.
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Date Issued: 1993
PURL: http://purl.flvc.org/fcla/dt/14898
Subject Headings: Artificial intelligence, Fuzzy logic, Neural networks (Computer science), Pavements--Skid resistance
Format: Document (PDF)

Title: Intelligent systems using GMDH algorithms.
Creator: Gupta, Mukul., College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
Abstract/Description: Design of intelligent systems that can learn from the environment and adapt to the change in the environment has been pursued by many researchers in this age of information technology. The Group Method of Data Handling (GMDH) algorithm to be implemented is a multilayered neural network. Neural network consists of neurons which use information acquired in training to deduce relationships in order to predict future responses. Most software tool during the simulation of the neural network based...
Show moreDesign of intelligent systems that can learn from the environment and adapt to the change in the environment has been pursued by many researchers in this age of information technology. The Group Method of Data Handling (GMDH) algorithm to be implemented is a multilayered neural network. Neural network consists of neurons which use information acquired in training to deduce relationships in order to predict future responses. Most software tool during the simulation of the neural network based algorithms in a sequential, single processor machine like Pascal, C or C++ takes several hours or even days. But in this thesis, the GMDH algorithm was modified and implemented into a software tool written in Verilog HDL and tested with specific application (XOR) to make the simulation faster. The purpose of the development of this tool is also to keep it general enough so that it can have a wide range of uses, but robust enough that it can give accurate results for all of those uses. Most of the applications of neural networks are basically software simulations of the algorithms only but in this thesis the hardware design is also developed of the algorithm so that it can be easily implemented on hardware using Field Programmable Gate Array (FPGA) type devices. The design is small enough to require a minimum amount of memory, circuit space, and propagation delay.
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Date Issued: 2010
PURL: http://purl.flvc.org/FAU/2976442
Subject Headings: GMDH algorithms, Genetic algorithms, Pattern recognition systems, Expert systems (Computer science), Neural networks (Computer science), Fuzzy logic, Intelligent control systems
Format: Document (PDF)

Title: Development of an intelligent fuzzy obstacle avoidance system using SONAR modeling and simulation.
Creator: Bouxsein, Philip A., Florida Atlantic University, An, Edgar
Abstract/Description: Response time to a threat or incident for coastline security is an area needing improvement. Currently, the U.S. Coast Guard is tasked with monitoring and responding to threats in coastal and port environments using boats or planes, and SCUBA divers. This can significantly hinder the response time to an incident. A solution to this problem is to use autonomous underwater vehicles (AUVs) to continuously monitor a port. The AUV must be able to navigate the environment without colliding into...
Show moreResponse time to a threat or incident for coastline security is an area needing improvement. Currently, the U.S. Coast Guard is tasked with monitoring and responding to threats in coastal and port environments using boats or planes, and SCUBA divers. This can significantly hinder the response time to an incident. A solution to this problem is to use autonomous underwater vehicles (AUVs) to continuously monitor a port. The AUV must be able to navigate the environment without colliding into objects for it to operate effectively. Therefore, an obstacle avoidance system (OAS) is essential to the activity of the AUV. This thesis describes a systematic approach to characterize the OAS performance in terms of environments, obstacles, SONAR configuration and signal processing methods via modeling and simulation. A fuzzy logic based OAS is created using the simulation. Subsequent testing of the OAS demonstrates its effectiveness in unknown environments.
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Date Issued: 2006
PURL: http://purl.flvc.org/fcla/dt/13390
Subject Headings: Fuzzy logic, Submersibles--Automatic control, Neural networks (Computer science), Underwater acoustics--Computer simulation, Sonar--Computer simulation
Format: Document (PDF)

Fuzzy logic (18)	+ -
Neural networks (Computer science) (6)	+ -
Fuzzy systems (4)	+ -
Artificial intelligence (2)	+ -
Automatic control (2)	+ -

GMDH algorithms (2)	+ -
Genetic algorithms (2)	+ -
Intelligent control systems (2)	+ -
Nonlinear control theory (2)	+ -
Pattern recognition systems (2)	+ -
Pavements--Skid resistance (2)	+ -
Submersibles--Automatic control (2)	+ -
Vehicular ad hoc networks (Computer networks) (2)	+ -
Acoustic impedance (1)	+ -
Adaptive computing systems (1)	+ -
Beacons (1)	+ -
Cellular mappings (1)	+ -
Computer software--Quality control (1)	+ -
Electronic commerce--Security measures (1)	+ -
Expert systems (Computer science) (1)	+ -
Finite groups (1)	+ -
Fuzzy algorithms (1)	+ -
Hydorlogic models (1)	+ -
Logic, Symbolic and mathematical (1)	+ -
Marine sediments (1)	+ -
Marine sediments--Acoustic properties (1)	+ -
Mathematics (1)	+ -
Process control--Data processing (1)	+ -
Representations of groups (1)	+ -
Robotics (1)	+ -

College of Engineering and Computer Science (16)	+ -
Florida Atlantic University (16)	+ -
Department of Computer and Electrical Engineering and Computer Science (11)	+ -
Department of Ocean and Mechanical Engineering (4)	+ -
Zhuang, Hanqi (4)	+ -

Mahgoub, Imad (2)	+ -
Smith, Samuel M. (2)	+ -
Zilouchian, Ali (2)	+ -
Alhameed, Mohammed (1)	+ -
Alzamzami, Ohoud (1)	+ -
An, Edgar (1)	+ -
Bai, Ying. (1)	+ -
Bouxsein, Philip A. (1)	+ -
Brown, Ricardo Eric. (1)	+ -
DeBruin, Darryl L. (1)	+ -
Department of Civil, Environmental and Geomatics Engineering (1)	+ -
Diaz-Robainas, Regino R. (1)	+ -
Gan, (Linda) Huilin. (1)	+ -
Ganesan, Krishnamurthy (1)	+ -
Gupta, Mukul. (1)	+ -
Howard, David William. (1)	+ -
Huang, Ming Z. (1)	+ -
Khoshgoftaar, Taghi M. (1)	+ -
LeBlanc, Lester R. (1)	+ -
Pandya, Abhijit S. (1)	+ -
Reddy, Kondakrindhi Praveen. (1)	+ -
Reddy, Mohan S. (1)	+ -
Rizk, Charbel George. (1)	+ -
Roth, Zvi S. (1)	+ -
Song, Feijun. (1)	+ -

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