Thesis (M. S.)--Economics, Georgia Institute of Technology, 2006. / Wille J. Belton, Jr., Committee Chair ; Patrick McCarthy, Committee Member ; Usha Nair-Reichert, Committee Member. Includes bibliographical references.

Thesis (M.S.)--West Virginia University, 2005. / Title from document title page. Document formatted into pages; contains vi, 126 p. : ill. (some col.). Includes abstract. Includes bibliographical references (p. 67-70).

Thesis (Ph. D.)--Ohio State University, 2007. / Title from first page of PDF file. Includes bibliographical references (p. 193-194).

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O trabalho apresenta o desenvolvimento de um sistema inteligente, baseado em lógica fuzzy, o qual controla a velocidade de uma esteira ergométrica com a finalidade de minimizar os riscos da atividade cardíaca do usuário, permitindo ainda maximizar os benefícios que a atividade física pode proporcionar ao usuário deste equipamento. O controlador inteligente desenvolvido foi baseado na técnica de controle fuzzy, possuindo por isso um software simplificado. Além disto o hardware desenvolvido foi baseado em circuitos eletrônicos simples e de baixo custo, o que permite sua instalação nos mais diversos tipos de esteiras existentes no mercado. A contribuição técnico cientifica do equipamento desenvolvido é um controlador adaptativo que é gerado de acordo com o perfil do usuário, isto é, para um conjunto de características tais como: idade, condicionamento físico, índice de massa corporal e zona de treinamento desejada. O sistema constrói automaticamente um controlador fuzzy capaz de manter a atividade cardíaca do usuário dentro da faixa de segurança indicada pelos médicos e / ou fisioterapeutas, de acordo com as características fornecidas. O equipamento desenvolvido, hardware e software, são descritos detalhadamente e os resultados dos testes realizados com diversos usuários são comparados a valores simulados por um software dedicado a controle industrial, apresentando uma discrepância inferior a 10%. O sistema também apresentou resultados de maneira a garantir a integridade física de quem fez uso do equipamento, não tendo, em momento algum, ultrapassado o valor de freqüência cardíaca máxima permitida para o usuário. E ainda, manteve a freqüência cardíaca numa faixa entre 60 a 85% da freqüência cardíaca máxima, constatando a eficiência do controlador. / The aim of this work is to develop an intelligent system to speed control of a treadmill. The intelligent control system minimizes the risks of the user’s cardiac activity, allowing the maximization of the benefits that the physical activity can grant the user of this equipment. The developed intelligent controller is based on fuzzy control techniques, and has a simplified software. Besides, the developed hardware is based on cheaper and simpler electronic circuits, which allows its installation on driver kinds of treadmills existing in the market. The main characteristic of the developed equipment and that a controller adaptable is generated in agreement with the user`s profile, that is, for a group of such characteristics lite age, physical conditioning, index of corporal mass and training area recommended. The system builds a controller fuzzy automatically inside capable of maintaining the user`s heart activity of suitable safety´s strip for the doctors and / or physiotherapists, in agreement with the supplied characteristics. The developed equipment, its hardware and software, is described in full detail and the results of the tests accomplished with several users are compared to simulated values by a software dedicated to industrial control, presenting an inferior discrepancy of 10%. The system also presents way results that guarantee the physical integrity of who made use of the equipment, it doesn't tend, at any time, outdated the value of maximum heart frequency allowed for the user. It is still, maintained the heart frequency in a strip among 60 to 85% of the maximum heart frequency, verifying the controller's efficiency.

Thesis (MTech (Electrical Engineering))--Peninsula Technikon, 2002 / In this thesis fuzzy control is analyzed and applied to two complex processes. A process is deemed to be complex if it possesses characteristics that make it non-linear. Examples of such characteristics are backlash, hysteresis, saturation and dead zones, which are common in industrial processes. These characteristics do not allow for the easy implementation of controllers and often there would be a requirement to employ some non-linear form of control. Often with complex processes linearization techniques would be employed to enable the application of linear controllers. However, these controllers will only operate over a limited range and will have degradation in performance when subjected to unpredictable changes in parameters. Fuzzy controllers can handle nonlinear characteristics in complex processes very well and also provides some transparency between the human machine interface. Fuzzy control is based upon the fuzzy methodology that was introduced by Lotfi Zadeh (Zadeh, 1965) in his seminal paper on fuzzy sets. The first practical application (Mamdani and Assilian, 1975) paved the way for fuzzy control and although this alternate paradigm of control came up against much criticism it managed to capture the interest of many researchers. Although research into fuzzy control saw a slump in the late 70's and early 80's it rapidly progressed in the 90's with literally thousands of research papers being published. In this study this alternate paradigm of control is investigated and applied to two processes. An initial study was done on the fundamental concepts of fuzzy logic and how this methodology can be applied to develop a controller that is fuzzy logic based. A plethora of information exist on fuzzy theory however only the fundamental concepts are dealt with here. This is sufficient for the realization of a rudimentary controller. A detailed investigation was also done on the development of the rules of the knowledge base of the controller with the emphasis on the development of a fuzzy controller that has characteristics akin to a proportional-integral (PI) controller.

With large-scale implementation of drones having begun and numerous companies competing to be among the original players in the market, there lies a large potential for novel drone designs to be created and flown. These novel designs are the ones that were largely ignored in the previous century due to the physical constraints of having a crewed cockpit, but uncrewed aerial vehicles, or UAVs, have opened a floodgate of potential design spaces that may be explored which were previously impossible. The hybrid vertical take-off and landing, VTOL, UAV is one aircraft that presents a potential solution to the classic trade-off of the traditional VTOL's range and endurance limitations versus the fixed wing's required infrastructure. An aircraft known as the Flite Test Spear is used to examine fuzzy logic control and is one such hybrid VTOL that uses large control surfaces and throttle control to maneuver itself for take-offs and landings in a tail-sitting orientation before transitioning to forward, fixed-wing flight. Current flight controllers used in operation on hybrid VTOL aircraft rely on a control law state machine where given a pre-identified aircraft state, the controller enters a transitioning maneuver that takes the aircraft from a VTOL to fixed wing flight regime, or vice versa. Each flight regime is operated by a PID controller with different gains and control input realizations. A modification to this principle is first examined by using fuzzy logic PID gain modification for increased response time and reduced overshoot. Reducing overshoot is of particular interest in this case as, on an aircraft such as this, it has the potential for entering undesirable and unrecoverable states, especially during its transition. Secondly, a mixing of the two flight controllers using a fuzzy logic system was implemented to combine the two controllers' outputs and potentially smooth this transition for safer, more efficient flight. The fuzzy logic controlled mixing of the two VTOL and fixed wing controllers was not proven to provide a more desirable response within the scope of the simulation, however, performed equally as well to that of the current state machine response. The gain scheduling fuzzy systems implemented in the controller have shown to decrease overshoot of the aircraft when given commands to different states, but respond slower than their conventional counterparts. Promise in the reduction of the overshoot error and their lightweight construction leads to the conclusion that implementation on a prototype aircraft would be worthwhile for further testing. / Master of Science / Drones play a larger role in our daily lives than they ever have before. With the work being performed by Google Wing to begin last-mile delivery of household consumer goods to the success of companies like Zipline and Swoop Aero in delivering emergency medical supplies to remote locations in low-resource areas, drones are being increasingly deployed, and their use will continue to grow if current trends continue. Like all burgeoning markets, competition is driving innovation to seek new market sectors and pushing the stagnant players out. In order to distinguish themselves, many companies have been creating their own drones for whichever sector of the drone market they wish to compete in. Whether that be consumer good delivery or aerial imagery, these challenges create numerous problems that some drones handle better than others. This has led to a large investment into the research and development of drones that best suit the needs of whatever mission has to be performed. Drones that act similarly to conventional aircraft such as planes or helicopters may serve as the best solution for a variety of problem statements, but because the need for a pilot in the cockpit is no longer necessary, solutions that were previously impossible to implement due to human factors can now be explored fully. With such an explosion in the design space of drones, the control algorithms needed to operate them must follow suit. This paper attempts to explain an alternative to one of the most common controllers in use today known as the PID. A modification to this controller using a technique known as fuzzy logic is made to increase the performance of experimental drone types without the need of an extensive, costly research and development phase that is necessary for crewed aircraft.

Thesis (M.S.)--Florida State University, 2004. / Advisor: Dr. Bing Kwan, Florida State University, College of Engineering, Dept. of Electrical and Computer Engineering. Title and description from dissertation home page (viewed June 16, 2004). Includes bibliographical references.

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