3 resultados para worst-case analysis

em Digital Commons - Michigan Tech


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This dissertation discusses structural-electrostatic modeling techniques, genetic algorithm based optimization and control design for electrostatic micro devices. First, an alternative modeling technique, the interpolated force model, for electrostatic micro devices is discussed. The method provides improved computational efficiency relative to a benchmark model, as well as improved accuracy for irregular electrode configurations relative to a common approximate model, the parallel plate approximation model. For the configuration most similar to two parallel plates, expected to be the best case scenario for the approximate model, both the parallel plate approximation model and the interpolated force model maintained less than 2.2% error in static deflection compared to the benchmark model. For the configuration expected to be the worst case scenario for the parallel plate approximation model, the interpolated force model maintained less than 2.9% error in static deflection while the parallel plate approximation model is incapable of handling the configuration. Second, genetic algorithm based optimization is shown to improve the design of an electrostatic micro sensor. The design space is enlarged from published design spaces to include the configuration of both sensing and actuation electrodes, material distribution, actuation voltage and other geometric dimensions. For a small population, the design was improved by approximately a factor of 6 over 15 generations to a fitness value of 3.2 fF. For a larger population seeded with the best configurations of the previous optimization, the design was improved by another 7% in 5 generations to a fitness value of 3.0 fF. Third, a learning control algorithm is presented that reduces the closing time of a radiofrequency microelectromechanical systems switch by minimizing bounce while maintaining robustness to fabrication variability. Electrostatic actuation of the plate causes pull-in with high impact velocities, which are difficult to control due to parameter variations from part to part. A single degree-of-freedom model was utilized to design a learning control algorithm that shapes the actuation voltage based on the open/closed state of the switch. Experiments on 3 test switches show that after 5-10 iterations, the learning algorithm lands the switch with an impact velocity not exceeding 0.2 m/s, eliminating bounce.

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Bioenergy and biobased products offer new opportunities for strengthening rural economies, enhancing environmental health, and providing a secure energy future. Realizing these benefits will require the development of many different biobased products and biobased production systems. The biomass feedstocks that will enable such development must be sustainable, widely available across many different regions, and compatible with industry requirements. The purpose of this research is to develop an economic model that will help decision makers identify the optimal size of a forest resource based biofuel production facility. The model must be applicable to decision makers anywhere, though the modeled case analysis will focus on a specific region; the Upper Peninsula (U.P.) of Michigan. This work will illustrate that several factors influence the optimal facility size. Further, this effort will reveal that the location of the facility does affect size. The results of the research show that an optimal facility size can be determined for a given location and are based on variables including forest biomass availability, transportation cost rate, and economy of scale factors. These variables acting alone and interacting together can influence the optimal size and the decision of where to locate the biofuel production facility. Further, adjustments to model variables like biomass resource and storage costs have no effect on facility size, but do affect the unit cost of the biofuel produced.

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As the agricultural non-point source pollution(ANPSP) has become the most significant threat for water environmental deterioration and lake eutrophication in China, more and more scientists and technologists are focusing on the control countermeasure and pollution mechanism of agricultural non-point source pollution. The unreasonable rural production structure and limited scientific management measures are the main reasons for acute ANSPS problems in China. At present, the problem for pollution control is a lack of specific regulations, which affects the government's management efficiency. According to these characteristics and problems, this paper puts forward some corresponding policies. The status of the agricultural non-point source pollution of China is analyzed, and ANSPS prevention and control model is provided based on governance policy, environmental legislation, technical system and subsidy policy. At last, the case analysis of Qiandao Lake is given, and an economic policy is adopted based on its situation.