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Aerospace Engineering Projects Thesis On Control Parameters for the Ranger 8-DOF Tele-operated Space Manipulator

September 29, 2011 Leave a comment
Title: Categorizing Admittance Control Parameters for the Ranger 8-DOF Tele-operated Space Manipulator
Abstract: Position-based admittance control of a robotic manipulator is a strategy that allows the manipulator to achieve compliance without sacrificing positional accuracy or modifying the underlying position controller. Desired manipulator stiffness and damping can be specified so that the tool tip behaves as a spring-dashpot system. This work characterizes the range of parameters that allows stable task execution in contact with an environment of varying stiffness for the Ranger dexterous manipulator. A classical stability analysis and simulation of the controller is conducted to predict its response in contact. The manipulator’s behavior is then observed during a series of simple tasks involving contact in one and two degrees of freedom. Suitable gains are chosen such that interaction forces at the tool tip are kept low. A compliant peg-in-hole insertion task is successfully accomplished. The work also outlines the implementation of an algorithm that removes unwanted gravity forces measured at the tool tip.

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Keywords: Engineering, Aerospace, Impedance, Admittance, Control, Robotic Manipulator
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Aerospace Engineering Project On APPLICATION OF REDUCED ORDER MODELING TECHNIQUES

September 29, 2011 Leave a comment
Title: APPLICATION OF REDUCED ORDER MODELING TECHNIQUES TO PROBLEMS IN HEATCONDUCTION, ISOELECTRIC FOCUSING AND DIFFERENTIAL ALGEBRAIC EQUATIONS 

Abstract: This thesis focuses on applying and augmenting `Reduced Order Modeling’ (ROM) techniques to large scale problems. ROM refers to the set of mathematical techniques that are used to reduce the computational expense of conventional modeling techniques, like finite element and finite difference methods, while minimizing the loss of accuracy that typically accompanies such a reduction. The first problem that we address pertains to the prediction of the level of heat dissipation in electronic and MEMS devices. With the ever decreasing feature sizes in electronic devices, and the accompanied rise in Joule heating, the electronics industry has, since the 1990s, identified a clear need for computationally cheap heat transfer modeling techniques that can be incorporated along with the electronic design process. We demonstrate how one can create reduced order models for simulating heat conduction in individual components that constitute an idealized electronic device. The reduced order models are created using Krylov Subspace Techniques (KST). We introduce a novel `plug and play’ approach, based on the small gain theorem in control theory, to interconnect these component reduced order models (according to the device architecture) to reliably and cheaply replicate whole device behavior.
                                                         The final aim is to have this technique available commercially as a computationally cheap and reliable option that enables a designer to optimize for heat dissipation among competing VLSI architectures. Another place where model reduction is crucial to better design is Isoelectric Focusing (IEF) – the second problem in this thesis – which is a popular technique that is used to separate minute amounts of proteins from the other constituents that are present in a typical biological tissue sample. Fundamental questions about how to design IEF experiments still remain because of the high dimensional and highly nonlinear nature of the differential equations that describe the IEF process as well as the uncertainty in the parameters of the differential equations. There is a clear need to design better experiments for IEF without the current overhead of expensive chemicals and labor. We show how with a simpler modeling of the underlying chemistry, we can still achieve the accuracy that has been achieved in existing literature for modeling small ranges of pH (hydrogen ion concentration) in IEF, but with far less computational time. We investigate a further reduction of time by modeling the IEF problem using the Proper Orthogonal Decomposition (POD) technique and show why POD may not be sufficient due to the underlying constraints. The final problem that we address in this thesis addresses a certain class of dynamics with high stiffness – in particular, differential algebraic equations. With the help of simple examples, we show how the traditional POD procedure will fail to model certain high stiffness problems due to a particular behavior of the vector field which we will denote as twist. We further show how a novel augmentation to the traditional POD algorithm can model-reduce problems with twist in a computationally cheap manner without any additional data requirements.Keywords: Engineering, Aerospace Mathematics, Chemistry, Biochemistry, Differential Algebraic Equations, Heat dissipation electronic devices, Isoelectric Focusing, Krylov Subspace Theory, Proper Orthogonal Decomposition, Reduced Order modeling.

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Aerospace Engineering Project Report On APPLICATION OF REDUCED ORDER MODELING TECHNIQUES…

September 13, 2011 Leave a comment
APPLICATION OF REDUCED ORDER MODELING TECHNIQUES TO PROBLEMS IN HEATCONDUCTION, ISOELECTRIC FOCUSING AND DIFFERENTIAL ALGEBRAIC EQUATIONS

Abstract: This thesis focuses on applying and augmenting `Reduced Order Modeling’ (ROM) techniques to large scale problems. ROM refers to the set of mathematical techniques that are used to reduce the computational expense of conventional modeling techniques, like finite element and finite difference methods, while minimizing the loss of accuracy that typically accompanies such a reduction. The first problem that we address pertains to the prediction of the level of heat dissipation in electronic and MEMS devices. With the ever decreasing feature sizes in electronic devices, and the accompanied rise in Joule heating, the electronics industry has, since the 1990s, identified a clear need for computationally cheap heat transfer modeling techniques that can be incorporated along with the electronic design process. We demonstrate how one can create reduced order models for simulating heat conduction in individual components that constitute an idealized electronic device. The reduced order models are created using Krylov Subspace Techniques (KST). We introduce a novel `plug and play’ approach, based on the small gain theorem in control theory, to interconnect these component reduced order models (according to the device architecture) to reliably and cheaply replicate whole device behavior.

The final aim is to have this technique available commercially as a computationally cheap and reliable option that enables a designer to optimize for heat dissipation among competing VLSI architectures. Another place where model reduction is crucial to better design is Isoelectric Focusing (IEF) – the second problem in this thesis – which is a popular technique that is used to separate minute amounts of proteins from the other constituents that are present in a typical biological tissue sample. Fundamental questions about how to design IEF experiments still remain because of the high dimensional and highly nonlinear nature of the differential equations that describe the IEF process as well as the uncertainty in the parameters of the differential equations. There is a clear need to design better experiments for IEF without the current overhead of expensive chemicals and labor. We show how with a simpler modeling of the underlying chemistry, we can still achieve the accuracy that has been achieved in existing literature for modeling small ranges of pH (hydrogen ion concentration) in IEF, but with far less computational time. We investigate a further reduction of time by modeling the IEF problem using the Proper Orthogonal Decomposition (POD) technique and show why POD may not be sufficient due to the underlying constraints.

The final problem that we address in this thesis addresses a certain class of dynamics with high stiffness – in particular, differential algebraic equations. With the help of simple examples, we show how the traditional POD procedure will fail to model certain high stiffness problems due to a particular behavior of the vector field which we will denote as twist. We further show how a novel augmentation to the traditional POD algorithm can model-reduce problems with twist in a computationally cheap manner without any additional data requirements.

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Keywords: Engineering, Aerospace, Mathematics, Chemistry, Biochemistry, Differential Algebraic Equations, Heat dissipation electronic devices, Isoelectric Focusing, Krylov Subspace Theory, Proper Orthogonal Decomposition, Reduced Order modeling.

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