Thesis (Ph. D.)--University of Rhode Island, 2005. / Typescript. Includes bibliographical references (v. 2: leaves 582-593).

It is preferable that control and bearing condition monitoring are integrated, as the condition of the system should influence control actions. As wind turbines mainly work in remote areas, it becomes necessary to develop a wireless platform for the control system. A fuzzy system with self-tuning mechanism was developed. The input speed error and speed change were selected to control the shaft speed, while the kurtosis and peak-to-peak values were used as another set of inputs to monitor the bearing conditions. To enhance effectiveness, wait-and-see (WAS) logic was used as the pre-processing step for the raw vibration signal. The system was implemented on the LabVIEW platform. Experiments have shown that the system can effectively adjust motor rotating speed in response to bearing conditions. For future studies, more advanced fault detection methods can be integrated with proper tuning mechanisms to enrich the performance and function of the controller.

Genetic algorithms are commonly used to solve combinatorial optimizationproblems. The implementation evolves using genetic operators (crossover, mutation,selection, etc.). Anyway, genetic algorithms like some other methods have parameters(population size, probabilities of crossover and mutation) which need to be tune orchosen.In this paper, our project is based on an existing hybrid genetic algorithmworking on the multiprocessor scheduling problem. We propose a hybrid Fuzzy-Genetic Algorithm (FLGA) approach to solve the multiprocessor scheduling problem.The algorithm consists in adding a fuzzy logic controller to control and tunedynamically different parameters (probabilities of crossover and mutation), in anattempt to improve the algorithm performance. For this purpose, we will design afuzzy logic controller based on fuzzy rules to control the probabilities of crossoverand mutation. Compared with the Standard Genetic Algorithm (SGA), the resultsclearly demonstrate that the FLGA method performs significantly better.

The Crew Exploration Vehicle (CEV) necessitates higher levels of automation than previous NASA vehicles due to program requirements for automation, including Automated Rendezvous and Docking (AR&D). Studies of spacecraft development often point to the locus of decision-making authority between humans and computers (i.e. automation) as a prime driver for cost, safety, and mission success. Therefore, a critical component in the CEV development is the determination of the correct level of automation. To identify the appropriate levels of automation and autonomy to design into a human space flight vehicle, NASA has created the Function-specific Level of Autonomy and Automation Tool (FLOAAT). This research develops a methodology for prototyping increased levels of automation for spacecraft rendezvous functions. This methodology was used to evaluate the accuracy of the FLOAAT-specified levels of automation, via prototyping. Two spacecraft rendezvous planning tasks were selected and then prototyped in Matlab using Fuzzy Logic (FL) techniques and existing Shuttle rendezvous trajectory algorithms. The prototyped functions are the determination of the maximum allowable Timeof- IGnition (TIG) slip for a rendezvous phasing burn and the evaluation of vehicle position relative to Transition initiation (Ti) position constraints. The methodology for prototyping rendezvous functions at higher levels of automation is judged to be a promising technique. The results of the prototype indicate that the FLOAAT recommended level of automation is reasonably accurate and that FL can be effectively used to model human decision-making used in spacecraft rendezvous. FL has many desirable attributes for modeling human decision-making, which makes it an excellent candidate for additional spaceflight automation applications. These conclusions are described in detail as well as recommendations for future improvements to the FLOAAT method and prototyped rendezvous functions.

Thesis (M. Phil.)--University of Hong Kong, 2001. / Includes bibliographical references (leaves 166-182).

Thesis (Ph. D.)--West Virginia University, 2002. / Title from document title page. Document formatted into pages; contains xiii, 192 p. : ill. (some col.). Includes abstract. Includes bibliographical references (p. 160-169).

Thesis (M.S.)--California State University, Chico. / Includes abstract. "Located in the Chico Digital Repository." Includes bibliographical references (p. 93-94).

Thesis (Ph. D.)--University of Washington, 2003. / Vita. Includes bibliographical references (leaves 79-83).

The friction surfacing process is a derivative of friction welding and retains all the benefits of that welding process - solid phase, forged microstructures and excellent metallurgical bonds. This work is aimed at the development of mathematical and statistical models for the optimisation of the significant process parameters in order to allow rapid development of new applications using standard CNC equipment. Also the possibility of implementing real-time control systems have been investigated and developed. A friction surfacing database has been configured to allow continuos recording and storage of the useful machine outputs. Later, an infrared pyrometer and thermocouples have also been connected to the data acquisition set-up establishing fully automated information flow from the process. A conversion procedure has been developed to ensure that the experimental results are applicable in industrial environments. Response surface map and the method of visual optimisation have been developed. They are an essential part of the methodology for experimental optimisation of the friction surfacing process. The problem of modelling and optimisation has also been approached using accurate statistical methods. Artificial intelligence in the form of neural networks has been used to improve the accuracy of the derived friction surfacing analytical relationships. For the first time dynamic study of the process has been carried out and CARIMA models have been derived using a modified version of the recursive least squares, to ensure high sensitivity and stability of the identification procedure. New conversion technique has been developed, allowing the use of existing models for materials that have not been used for friction surfacing before, reducing significantly the number of experiments. The idea of using indicator parameters has been introduced for the first time in this research. Such parameters are the force, the torque and the interface temperature and they can be measured on-line. It has been shown that variations of these parameters reflect in the quality of the coating characteristics that cannot be measured on-line. Real-time control has also been considered. An algorithm involving fuzzy logic and self-tuning extremum controller has been developed to continuously monitor and compensate in real-time against the variations in the coating characteristics, and respectively in the indicator parameters. The proposed methodology has been used to design a control system that is capable of maintaining optimal process characteristics. The value of this work is also in reducing the lead-time and hence the cost for determining the optimum parameters for a given coating material on a given substrate geometry. This is an important feature when developing new applications for the friction surfacing process. On the basis of this research a range of new commercial applications have emerged including the manufacture of machine knives for the food, pharmaceutical and packaging industries, repair of car engine valve seats, turbine blades, reclamation of shafts, etc.

(Uncorrected OCR) Abstract of thesis entitled Improving the Performance of Lifts Using Artificial Intelligence Techniques submitted by Wong King Sau for the degree of Doctor of Philosophy at the University of Hong Kong in August 2003 An elevator group control system manages multiple elevators to serve hall calls in a building. Most elevator group control systems need to recognize the traffic pattern of the building and then change their control algorithms to improve the efficiency of the elevator system. However, the traffic flow in a building is very difficult to be classified into distinct patterns. Traffic recognition systems can recognize certain traffic patterns, but mixed traffic patterns are difficult to be recognized. The aim of this study was therefore to develop improved duplex elevator group control systems that do not need to recognize the traffic pattern. A fuzzy logic. control unit and genetic algorithms control unit were used. A fuzzy logic control unit integrates with the conventional duplex elevator group control system to improve performance especially in mixed traffic patterns with intermittent heavy traffic demand. This system will send more than one elevator to a floor with heavy demand, . according to the overall passenger traffic conditions in the building. The genetic algorithms control unit divides the building into three zones and assigns an appropriate number of elevators to each zone. The floors covered by each zone are adjusted every five minutes. This control unit optimizes elevator group control by equalizing the number of hall calls in each zone, the total elevator door opening time in each zone, and the number of floors served by each elevator. Both of the control units were tested by a simulator in a computer. The performance of the elevator system is given by indices such as average waiting time, wasted man-hour, and long waiting time percentage. The new performance index "wasted man-hour" indicates the total time spent by passengers in a building waiting for the lift service. Both proposed systems perform better than the conventional duplex control system. (An abstract of 297 words.) ~ Signed _ Wong King Sau / abstract / toc / Mechanical Engineering / Doctoral / Doctor of Philosophy