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Fuzzy Logic - Any Control Thesis Idea Created by: ..

Improving network performance in terms of efficiency, fairness in the bandwidth, and system stability has been a research issue for decades. Current Internet traffic control maintains sophistication in end TCPs but simplicity in routers. In each router, incoming packets queue up in a buffer for transmission until the buffer is full, and then the packets are dropped. This router queue management strategy is referred to as Drop Tail. End TCPs eventually detect packet losses and slow down their sending rates to ease congestion in the network. This way, the aggregate sending rate converges to the network capacity. In the past, Drop Tail has been adopted in most routers in the Internet due to its simplicity of implementation and practicability with light traffic loads. However Drop Tail, with heavy-loaded traffic, causes not only high loss rate and low network throughput, but also long packet delay and lengthy congestion conditions. To address these problems, active queue management (AQM) has been proposed with the idea of proactively and selectively dropping packets before an output buffer is full. The essence of AQM is to drop packets in such a way that the congestion avoidance strategy of TCP works most effectively. Significant efforts in developing AQM have been made since random early detection (RED), the first prominent AQM other than Drop Tail, was introduced in 1993. Although various AQMs also tend to improve fairness in bandwidth among flows, the vulnerability of short-lived flows persists due to the conservative nature of TCP. It has been revealed that short-lived flows take up traffic with a relatively small percentage of bytes but in a large number of flows. From the user’s point of view, there is an expectation of timely delivery of short-lived flows. Our approach is to apply artificial intelligence technologies, particularly fuzzy logic (FL), to address these two issues: an effective AQM scheme, and preferential treatment for short-lived flows. Inspired by the success of FL in the robust control of nonlinear complex systems, our hypothesis is that the Internet is one of the most complex systems and FL can be applied to it. First of all, state of the art AQM schemes outperform Drop Tail, but their performance is not consistent under different network scenarios. Research reveals that this inconsistency is due to the selection of congestion indicators. Most existing AQM schemes are reliant on queue length, input rate, and extreme events occurring in the routers, such as a full queue and an empty queue. This drawback might be overcome by introducing an indicator which takes account of not only input traffic but also queue occupancy for early congestion notification. The congestion indicator chosen in this research is traffic load factor. Traffic load factor is in fact dimensionless and thus independent of link capacity, and also it is easy to use in more complex networks where different traffic classes coexist. The traffic load indicator is a descriptive measure of the complex communication network, and is well suited for use in FL control theory. Based on the traffic load indicator, AQM using FL – or FLAQM – is explored and two FLAQM algorithms are proposed. Secondly, a mice and elephants (ME) strategy is proposed for addressing the problem of the vulnerability of short-lived flows. The idea behind ME is to treat short-lived flows preferably over bulk flows. ME’s operational location is chosen at user premise gateways, where surplus processing resources are available compared to other places. By giving absolute priority to short-lived flows, both short and long-lived flows can benefit. One problem with ME is starvation of elephants or long-lived flows. This issue is addressed by dynamically adjusting the threshold distinguishing between mice and elephants with the guarantee that minimum capacity is maintained for elephants. The method used to dynamically adjust the threshold is to apply FL. FLAQM is deployed to control the elephant queue with consideration of capacity usage of mice packets. In addition, flow states in a ME router are periodically updated to maintain the data storage. The application of the traffic load factor for early congestion notification and the ME strategy have been evaluated via extensive experimental simulations with a range of traffic load conditions. The results show that the proposed two FLAQM algorithms outperform some well-known AQM schemes in all the investigated network circumstances in terms of both user-centric measures and network-centric measures. The ME strategy, with the use of FLAQM to control long-lived flow queues, improves not only the performance of short-lived flows but also the overall performance of the network without disadvantaging long-lived flows.

The global electrical energy consumption is rising and their is steady increase of the demand on power generation. So in addition to conventional power generation units, a large no. of renewable energy units are being integrated into the power system. A wind electrical generation system is the most cost competitive of all the environmentally clean and safe renewable energy sources in the world. The recent evolution of power semiconductors and variable frequency drive technology has aided the acceptance of variable speed generation systems. Fuzzy logic is a powerful and versatile tool for representing imprecise, ambiguous and vague information. It helps us model difficult, even intractable problems. Advantages of fuzzy control are that it is parameter insensitive, provides fast convergence and accepts noise noisy and inaccurate signals. The fuzzy algorithms are universal and can be applied retroactively in any system. In this thesis a squirrel cage induction generator feeds power to a double sided pulse width modulated converter system which feeds power to an autonomous load or grid. The generation system has three no.s of fuzzy logic control with vector control in its inner loop.
* The first fuzzy controller tracks the generator speed with the wind velocity to extract maximum power.
* The second fuzzy controller programs the machine flux for light load efficiency improvement.
* The third fuzzy controller gives robust speed control against wind gust and turbine oscillatory torque.
The fuzzy logic based control of the system helps to optimize efficiency and enhance performance. The system gives excellent performance and can easily be translated to a larger size in the field.

The fuzzy algorithm will output an early warning of any patient‟s abnormality status.

Fuzzy logic is based on IF THEN.

(2007) Fuzzy logic based control of variable speed cage wind generation system. MTech thesis.

Improving network performance in terms of efficiency, fairness in the bandwidth, and system stability has been a research issue for decades. Current Internet traffic control maintains sophistication in end TCPs but simplicity in routers. In each router, incoming packets queue up in a buffer for transmission until the buffer is full, and then the packets are dropped. This router queue management strategy is referred to as Drop Tail. End TCPs eventually detect packet losses and slow down their sending rates to ease congestion in the network. This way, the aggregate sending rate converges to the network capacity. In the past, Drop Tail has been adopted in most routers in the Internet due to its simplicity of implementation and practicability with light traffic loads. However Drop Tail, with heavy-loaded traffic, causes not only high loss rate and low network throughput, but also long packet delay and lengthy congestion conditions. To address these problems, active queue management (AQM) has been proposed with the idea of proactively and selectively dropping packets before an output buffer is full. The essence of AQM is to drop packets in such a way that the congestion avoidance strategy of TCP works most effectively. Significant efforts in developing AQM have been made since random early detection (RED), the first prominent AQM other than Drop Tail, was introduced in 1993. Although various AQMs also tend to improve fairness in bandwidth among flows, the vulnerability of short-lived flows persists due to the conservative nature of TCP. It has been revealed that short-lived flows take up traffic with a relatively small percentage of bytes but in a large number of flows. From the user’s point of view, there is an expectation of timely delivery of short-lived flows. Our approach is to apply artificial intelligence technologies, particularly fuzzy logic (FL), to address these two issues: an effective AQM scheme, and preferential treatment for short-lived flows. Inspired by the success of FL in the robust control of nonlinear complex systems, our hypothesis is that the Internet is one of the most complex systems and FL can be applied to it. First of all, state of the art AQM schemes outperform Drop Tail, but their performance is not consistent under different network scenarios. Research reveals that this inconsistency is due to the selection of congestion indicators. Most existing AQM schemes are reliant on queue length, input rate, and extreme events occurring in the routers, such as a full queue and an empty queue. This drawback might be overcome by introducing an indicator which takes account of not only input traffic but also queue occupancy for early congestion notification. The congestion indicator chosen in this research is traffic load factor. Traffic load factor is in fact dimensionless and thus independent of link capacity, and also it is easy to use in more complex networks where different traffic classes coexist. The traffic load indicator is a descriptive measure of the complex communication network, and is well suited for use in FL control theory. Based on the traffic load indicator, AQM using FL – or FLAQM – is explored and two FLAQM algorithms are proposed. Secondly, a mice and elephants (ME) strategy is proposed for addressing the problem of the vulnerability of short-lived flows. The idea behind ME is to treat short-lived flows preferably over bulk flows. ME’s operational location is chosen at user premise gateways, where surplus processing resources are available compared to other places. By giving absolute priority to short-lived flows, both short and long-lived flows can benefit. One problem with ME is starvation of elephants or long-lived flows. This issue is addressed by dynamically adjusting the threshold distinguishing between mice and elephants with the guarantee that minimum capacity is maintained for elephants. The method used to dynamically adjust the threshold is to apply FL. FLAQM is deployed to control the elephant queue with consideration of capacity usage of mice packets. In addition, flow states in a ME router are periodically updated to maintain the data storage. The application of the traffic load factor for early congestion notification and the ME strategy have been evaluated via extensive experimental simulations with a range of traffic load conditions. The results show that the proposed two FLAQM algorithms outperform some well-known AQM schemes in all the investigated network circumstances in terms of both user-centric measures and network-centric measures. The ME strategy, with the use of FLAQM to control long-lived flow queues, improves not only the performance of short-lived flows but also the overall performance of the network without disadvantaging long-lived flows.

The proposed system has proven that it outperforms the MEWS system in many cases, and hence an indication of the usefulness of this fuzzy-based approach.

Fuzzy Logic Control Implementation On Pic Microcontroller

While it may be a little fuzzy to convert 75 mph averages to 12 mph averages (I find my clown car trips average at 35-40, tops), another thing that’s missing is that there is rarely a 1:1 replacement of car miles traveled with bike miles.

Genetic Fuzzy PID Controller

Nutrient biogeochemistry in coastal waters. Development of anti-cancer and anti-infective agents. The discovery of what is going wrong, both in the central nervous system and the rest of the body, is key to understanding the disease and can lead us towards the following research ideals:. In other words, we aim to optimise all aspects in the development cycle such as needs analysis, concept development, evaluation and validation, commercialisation and product take back at its end of life. Andrea Lecturer Above The Bar Medicinal inorganic and pharmaceutical solid state chemistry. Environment, Marine and Energy Environment Health Santocanale, Prof Corrado Professor Cancer Biology and therapeutics- Cell Cycle an DNA replication Uncontrolled entry into S-phase is one of the hallmarks of cancer, while defects in the replication machinery and in the proper maintenance of the epigenetic information. She is the founder member of the World Literature Network Sorcha welcomes PhD proposals in any of the above research areas. Which origins can be identified of the ongoing need for various types of flexibility? Applied Social Sciences and Public Policy Business and Manufacturing Competitiveness Cairns,. Biomedical Science and Engineering phd thesis in fuzzy logic Medical Devices Connected Health McGarry, Dr Patrick Lecturer Bar/College Lecturer Multiscale cell and tissue mechanics. We study the molecular mechanisms underlying these stress responses to gain better understanding of human diseases, such as cancer and neurodegeneration. Biomedical Science and Engineering Health Independent Living McDonagh, Dr Brian Lecturer Below The Bar Redox signalling in response to endogenous ROS generation in a variety of cell and translational models particularly in skeletal muscle during exercise and ageing but also including glucoma, myopathy, chronic heart.

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Matlab Thesis; Fuzzy Logic Matlab; ..


Introduction to Fuzzy Logic Projects

The thesis represents improved algorithm, which manages the number of active heaters for heating and maintaining temperature in the beer brewing process, based on fuzzy logic. The goals of the new algorithm are lower time and energy consumption in addition to lesser end temperature deviation from the desired temperature. Steps necessary for the algorithm development are divided into several chapters. First is an environment presentation. It holds a description of kettle and its elements important for heating and maintaining the temperature. There is also a description of the whole beer brewing process and the existing algorithm of which results need to be improved. The tools used for the development are also presented in this chapter. The second chapter is intended for determining the properties of the environment. Here we have the acquisition of environment data regarding the temperatures and active heater information in various probable scenarios as well as the result interpretation. Algorithm development description consists of a short fuzzy logic presentation which is followed by an extensive presentation of fuzzy variables and associated fuzzy sets. The rules that act as a base for the fuzzy logic operation and the defuzzyfication method selection are also presented. Next is the new versus old algorithm result comparison. It consists of duration comparison and a comparison of end temperature deviation from the desired temperature within heating and maintaining temperature. The energy consumption comparison of both algorithms is also presented. Conclusion consists of algorithm development final findings and suggestions for possible further work in this area.

Fuzzy logic can be stated as a mathematical ..

The system consists of a wireless mobile vital signs data acquisition unit and a fuzzy-logic–based-software algorithm to monitors and assess patients‟ conditions on 24/7 bases.

Fuzzy Logic And Grey Science -- ScienceDaily

(2005) Fuzzy logic based robust control of queue management and optimal treatment of traffic over TCP/IP networks. [Thesis (PhD/Research)]

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