Thesis (Ph. D.)--University of Wisconsin--Madison, 1964. / Vita. Typescript. Abstracted in Dissertations abstracts, v. 26 (1964) no 6, p. 3483-4. eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references.

Thesis (Ph. D.)University of Wisconsin--Wisconsin. / Vita. eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references (leaves 420-441).

Thesis (doctoral)--Université de Neuchâtel, 1991. / Includes bibliographical references (p. 112) and index.

Thesis (Ph. D.)--University of Wisconsin--Madison 1983. / Typescript. Vita. eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references (leaves 180-185).

Thesis (M.S.)--University of Wisconsin--Madison, 1963. / Typescript. eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references (leaves 118-119).

Submitted in compliance with the requirements for the National Masters Diploma in Technology: Electronic Engineering, Technikon Natal, 1994. / This work presents a novel way of controlling the feed rate of raw material from a vibratory pipe feeder system. The system consists of a hopper, feeder pipe, electromechanical vibrator and a loadcell which measures the mass of the complete system. Raw material is gravity fed onto the vibrating pipe whose amplitude of vibration controls the amount of material fed. / M

The objective of this thesis is to investigate decomposition and its applicability to the theory of optimal control. The work begins with a representation of the structure of the optimal control problem in terms of directed graphs. This representation exposes a strong connectedness property leading to fundamental difficulties which are central in limiting the class of control problems to which decomposition can successfully be applied. Computational problems of optimal control are then considered, and decomposition is found to provide a framework within which to analyse numerical methods suitable for parallel processing. A number of such methods are shown and a numerical example is used to illustrate the viability of one of these. In the second part of the thesis, the optimal control law synthesis problem is discussed together with an inverse problem. The latter concerns the requirement of a second-level co-ordinator in a hierarchical structure. A multi-level controller is then suggested for a class of systems. The effect of this controller structure is to provide a performance very close to the optimal while maintaining adequate sub-optimal control in case of a breakdown of the second-level co-ordinator. The structure is justified on the basis of the second variation theory of the calculus of variations. Finally, a new computational technique founded on the geometrical concepts of optimal control theory is introduced. This results in replacing the unstable co-state variables associated with Pontryagin's maximum principle with a set of bounded variables. The facility in the choice of initial iterates makes the method promising. / Applied Science, Faculty of / Electrical and Computer Engineering, Department of / Graduate

Okada's three-phase star-connected circuit with three delta-connected SCRs inserted in the neutral point is analyzed using Take-uchi's ϕ-function method. The three-phase synchronous motor with three delta-connected SCRs inserted in the neutral point of the armature windings is then investigated. By control of the firing of the SCRs, operation at subsynchronous speeds is possible. The analysis of the steady-state operation of the SCR-controlled synchronous motor is experimentally checked. / Applied Science, Faculty of / Electrical and Computer Engineering, Department of / Graduate

No description available.

Models of dynamical systems are important in many disciplines of science, ranging from physics and traditional mechanical and electrical engineering to life sciences, computer science and economics. Engineers, for example, use models for development, analysis and control of complex technical systems. Dynamical models can be derived from physical insights, for example some known laws of nature, (which are models themselves), or, as considered here, by fitting unknown model parameters to measurements from an experiment. The latter approach is what we call system identification. A model is always (at best) an approximation of the true system, and for a model to be useful, we need some characterization of how large the model error is. In this thesis we consider model errors originating from stochastic (random) disturbances that the system was subject to during the experiment. Stochastic model errors, known as variance-errors, are usually analyzed under the assumption of an infinite number of data. In this context the variance-error can be expressed as a (complicated) function of the spectra (and cross-spectra) of the disturbances and the excitation signals, a description of the true system, and the model structure (i.e., the parametrization of the model). The primary contribution of this thesis is an alternative geometric interpretation of this expression. This geometric approach consists in viewing the asymptotic variance as an orthogonal projection on a vector space that to a large extent is defined from the model structure. This approach is useful in several ways. Primarily, it facilitates structural analysis of how, for example, model structure and model order, and possible feedback mechanisms, affect the variance-error. Moreover, simple upper bounds on the variance-error can be obtained, which are independent of the employed model structure. The accuracy of estimated poles and zeros of linear time-invariant systems can also be analyzed using results closely related to the approach described above. One fundamental conclusion is that the accuracy of estimates of unstable poles and zeros is little affected by the model order, while the accuracy deteriorates fast with the model order for stable poles and zeros. The geometric approach has also shown potential in input design, which treats how the excitation signal (input signal) should be chosen to yield informative experiments. For example, we show cases when the input signal can be chosen so that the variance-error does not depend on the model order or the model structure. Perhaps the most important contribution of this thesis, and of the geometric approach, is the analysis method as such. Hopefully the methodology presented in this work will be useful in future research on the accuracy of identified models; in particular non-linear models and models with multiple inputs and outputs, for which there are relatively few results at present. / QC 20100810