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Academic Commons Search Resultsen-usSimultaneous Iterative Learning and Feedback Control Design
http://academiccommons.columbia.edu/catalog/ac:182998
Chinnan, Anil Philiphttp://dx.doi.org/10.7916/D8NC6000Tue, 10 Feb 2015 00:00:00 +0000Iterative learning controllers aim to produce high precision tracking in operations where the same tracking maneuver is repeated over and over again. Model-based iterative learning control laws are designed from the system Markov parameters which could be inaccurate. Chapter 2 examines several important learning control laws and develops an understanding of how and when inaccuracy in knowledge of the Markov parameters results in instability of the learning process. While an iterative learning controller can compensate for unknown repeating errors and disturbances, it is not suited to handle non-repeating, stochastic errors and disturbances, which can be more effectively handled by a feedback controller. Chapter 3 explores feedback and iterative learning combination controllers, showing how a one-time step behind disturbance estimator and one-repetition behind disturbance estimator can be incorporated together in such a combination. Since learning control applications are finite-time by their very nature, frequency response based design techniques are not best suited for designing the feedback controller in this context. A finite-time feedback controller design approach is more appropriate given the overall aim of zero tracking error for the entire trajectory, even for shorter trajectories where the system response is still in its transient phase and has not yet reached steady state. Chapter 4 presents a combination of finite-time feedback and learning control as a natural solution for such a control objective, showing how a finite-time feedback controller and an iterative learning controller can be simultaneously synthesized during the learning process. Finally, Chapter 5 examines different configurations where a combination of a feedback controller and an iterative learning controller can be implemented. Numerical results are used to illustrate the feedback and iterative controller designs developed in this thesis.Electrical engineering, Mechanical engineering, Roboticsapc2113Electrical EngineeringDissertationsExperimental investigations of the role of proximity approximation in near-field radiative transfer
http://academiccommons.columbia.edu/catalog/ac:189127
Gu, Ninghttp://dx.doi.org/10.7916/D89P311QMon, 16 Sep 2013 00:00:00 +0000The nature of thermal radiative transfer changes significantly as the nominal gap between two objects becomes comparable to or smaller than the characteristic wavelength given by Wien's displacement law. At larger gaps, conventional theory of blackbody radiation is sufficient to describe the radiative transfer; at smaller gaps, however, wave effects such as evanescent wave tunneling, interference and diffraction render the classical theory invalid. The change in radiative transfer between two objects is most dramatic when they can support electromagnetic surface polaritons because of the high local density of states at the interface between the object and vacuum. When two objects of polar dielectric materials are close enough, the enhanced near-field radiation due to surface phonon polariton tunneling can exceed the blackbody limit by several orders of magnitude. This enhanced radiation at nanoscale has potential applications in energy transfer, heat assisted magnetic recording and near-field radiative cooling. In recent years, several experiments measuring the enhanced near-field radiation between a micro-sphere and a plane substrate have been reported. To measure the radiative transfer, the magnitude of which can be less than 10 nW, the sensor of choice is the bi-material micro-cantilever. My thesis has focused on two aspects of near-field radiative transfer between a micro-sphere and a substrate: (1) to enable quantitative comparison between experimental measurement and theoretical/numerical prediction of near-field radiative transfer. (2) to develop a comprehensive thermal model for the experimental measurement procedure. To enable the first task, an improved experimental apparatus to measure the near-field radiation between a micro-sphere and a substrate has been developed. In previous experimental apparatuses, radiative transfer was measured between a micro-sphere and a truncated plane surface. This was necessary because of the optical configuration. Our new apparatus overcomes this drawback with a newly designed optical path. With this new apparatus, the experiments are truly between a micro-sphere and an infinite plane. Measurements for micro-spheres with wide range of radii from 2.5 µ; to 25 µ; have been conducted. The experimental measurements are compared to the numerical prediction using the modified proximity proximation. In contrast to van der Waals force and Casimir force measurements in which the proximity approximation agree better when applied to larger spheres, in radiative heat transfer measurements, the modified proximity approximation agree better for smaller spheres. This surprising finding is explained by the difference in nature of radiative transfer and forces. To go along with the improved apparatus, we have also modified the method of data acquisition, calibration procedures and the thermal model for the experiment. In terms of data collection, we can now eliminate the effects of spurious forces; the second change we have implemented in the experiment is that the substrate is translated at a constant velocity, as opposed to discrete steps. We have developed a thermal model for the new experimental procedure.Mechanical engineering, Electrical engineering, Physicsng2220Electrical Engineering, Mechanical EngineeringDissertationsMulti-Input Multi-Output Repetitive Control Theory And Taylor Series Based Repetitive Control Design
http://academiccommons.columbia.edu/catalog/ac:144391
Xu, Kevinhttp://hdl.handle.net/10022/AC:P:12492Tue, 07 Feb 2012 00:00:00 +0000Repetitive control (RC) systems aim to achieve zero tracking error when tracking a periodic command, or when tracking a constant command in the presence of a periodic disturbance, or both a periodic command and periodic disturbance. This dissertation presents a new approach using Taylor Series Expansion of the inverse system z-transfer function model to design Finite Impulse Response (FIR) repetitive controllers for single-input single-output (SISO) systems, and compares the designs obtained to those generated by optimization in the frequency domain. This approach is very simple, straightforward, and easy to use. It also supplies considerable insight, and gives understanding of the cause of the patterns for zero locations in the optimization based design. The approach forms a different and effective time domain design method, and it can also be used to guide the choice of parameters in performing in the frequency domain optimization design. Next, this dissertation presents the theoretical foundation for frequency based optimization design of repetitive control design for multi-input multi-output (MIMO) systems. A comprehensive stability theory for MIMO repetitive control is developed. A necessary and sufficient condition for asymptotic stability in MIMO RC is derived, and four sufficient conditions are created. One of these is the MIMO version of the approximate monotonic decay condition in SISO RC, and one is a necessary and sufficient condition for stability for all possible disturbance periods. An appropriate optimization criterion for direct MIMO is presented based on minimizing a Frobenius norm summed over frequencies from zero to Nyquist. This design process is very tractable, requiring only solution of a linear algebraic equation. An alternative approach reduces the problem to a set of SISO design problems, one for each input-output pair. The performances of the resulting designs are studied by extensive examples. Both approaches are seen to be able to create RC designs with fast monotonic decay of the tracking error. Finally, this dissertation presents an analysis of using an experiment design sequence for parameter identification based on the theory of iterative learning control (ILC), a sister field to repetitive control. This is suggested as an alternative to the results in optimal experiment design. Modified ILC laws that are intentionally non-robust to model errors are developed, as a way to fine tune the use of ILC for identification purposes. The non-robustness with respect to its ability to improve identification of system parameters when the model error is correct is studied. It is demonstrated that in many cases the approach makes the learning particularly sensitive to relatively small parameter errors in the model, but sensitivity is sometimes limited to parameter errors of a specific sign.Electrical engineering, Mechanical engineering, Aerospace engineeringkx2101Electrical EngineeringDissertations