Calibration, characterization, and linear quadratic Gaussian estimation of sensor feedback signals for a novel ocean wave energy linear test bed Public Deposited

http://ir.library.oregonstate.edu/concern/graduate_thesis_or_dissertations/wd375z65g

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  • Continual growth of the world's energy consumption and the demand for long-term clean renewable energy resources has led to the development of ocean-based wave energy technologies. Emerging technologies are advancing potential solutions to the complex problem of energy generation in the harsh and corrosive ocean environment. To develop these technologies, new tools are needed for simulation and analysis of the ocean's interactions with newly designed wave energy generating devices. OSU's Ocean Wave Energy Linear Test Bed is one such tool that is capable of testing and providing baseline simulations of ocean wave interactions with point absorber ocean wave energy generating devices. To provide accurate ocean wave simulation with the Linear Test Bed, a closed-loop force control scheme must be developed. To date, this force control scheme has been unsuccessful because of ambient Gaussian noise present in the machine's feedback signal lines. A Linear Quadratic Gaussian Estimator was constructed to solve this noise issue by providing estimates of the Linear Test Bed's feedback signals and system states. The Kalman filter is constructed from a mathematical model of the Linear Test Bed physical movements and through statistical analysis of the Gaussian noise present in the feedback signal lines. The concern of sensor accuracy is also addressed by a calibration check of the machine's force measuring load cells and through development of a simple methodology of calibrating the load cells. The major results of this thesis show that Kalman filtration of the Linear Test Bed's feedback signals will provide relatively noise-free estimates that do not suffer phase delay issues common to the low-pass filter, while Kalman estimations of feedback signals reduce noise as measured by signal variance. The load cell sensors and signal lines experience drift over time, and therefore must be calibrated to more accurately reflect the state of an ocean energy generating device under test. Development of this machine's advanced control systems will allow quicker and more accurate testing of ocean-based energy generating devices, that can help solve the world's growing energy needs.
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