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Temperature control has been implemented in friction stir processing and has demonstrated the ability to give improved process control. In order to have optimal control of the process, the parameters of the system to be controlled must be accurately identified. The system parameters change with tool geometry and materials, workpiece materials, and temperature. This thesis presents the use of the relay feedback test to determine the system parameters. The relay feedback test is easy to use and promotes system stability during its use. The results from the relay feedback test can be used to determine controller gains for a PID controller. The use of this method, as well as the quality of the resulting control is demonstrated in this paper.

This thesis presents the formulation and solution of a new problem in systems and control theory, called the Network Realization Problem. Its relationship to other problems, such as State Realization and Structural Identifiability, is shown. The motivation for this work is the desire to completely quantify the conditions for transitioning between different mathematical representations of linear time-invariant systems. The solution to this problem is useful for theorists because it lays a foundation for quantifying the information cost of identifying a system's complete network structure from the transfer function.

[pt] A identificação de sistemas é focalizada sob o ponto de vista da aproximação estocástica. Um sistema sem memória e invariante no tempo, com função completamente desconhecida é identificado por intermédio de uma estimação, que minimiza o critério do erro médio quadrático, tomando como base um conjunto de funções pré- selecionadas e linearmente independentes. A identificação do sistema é obtida através de uma algoritmo recursivo de aproximação estocástica, que converge para o valor real dessa estimativa, com probabilidade 1 e no sentido da média quadrática. Um estudo da aceleração desse algoritmo é efetuado, comprovando a existência de uma seqüência capaz de otimizá-lo. É demonstrada a aplicação desse algoritmo para identificação de um sistema linear e invariante no tempo, entretanto a aceleração da convergência não é mais uma conseqüência do caso anterior. Ainda é apresentada uma tentativa de contornar o problema de acessibilidade dos estados, requerida pelo algoritmo de aproximação estocástica, utilizando simultaneamente à identificação dos parâmetros do sistema, os algoritmos do filtro de Kalman, para estimação dos estados / [en] The stochastic approximation approach is used for systems identification. A memoryless time-invariant system with functional form completely unknow is identified by means of an estimate based on a preselected and linearly independent set of function which minimizes the mean-square-error criterion. The system identification is obtained using a stochastic approximation recursive algorithm, which convergs to a real value of this estimate, with probability 1 and in the mean square sense. The acceleration study of this algorithm is developd by proving the existence of an optimal sequence. The application of this algorithm for a linear timevariant system identification is proved, nevertheless the convergence acceletation is not anymore a consequence of the last case. Next is presented a tentative to by-pass the problem of states accessibility, required for the stochastic approximation, using simultaneously parameters systems identification with the Kalman-filter algorithms for states estimation.

[pt] No presente trabalho faz-se inicialmente um apanhado das principais técnicas usadas na Identificação de Processos Físicos, cuja finalidade é servir de subsidio bibliográfico para outros trabalhos futuros (Cap. I, II e III). É dado ênfase aos problemas existentes na identificação de sistemas não estacionários tendo em vista a sua importância um projeto de Sistemas de Controle Auto – Adaptativos. Foi desenvolvido um método de identificação, usando a Técnica do Modelo Adaptativo (Cap. IV). Fez-se a simulação analógica do modelo adaptativo, no computador ANALAC 110 (comp. Analógico a corrente alternada) tendo em vista as facilidades permitidas pelos comandos gel, e CI dos seus integradores. Verificou-se a validade da simulação no ANALAC, testando-se a convergência do método em vários exemplos, cujos resultados são conhecidos. Os resultados são apresentados no Anexo 1. Posteriormente, estudou-se a possibilidade de tratar este mesmo problema em computador digital (IBM-1130) (Cap. IV e 3). No anexo II são apresentados os fluxogramas e programas FORTRAN, relativos a técnica digital. / [en] The subject of this paper is to give a summary of the more important techniques used in Identification of Physical Process, the purpose being that of serving as a bibliografical reference to future works (chap´s I, II and III). Special attention is given to problems of Identification in time varying systems, with the object the designing Auto-Adaptive Control Systems. Methods of Identification were developed using Adaptative Model Technique (Chap IV). Analog simulation of the adaptative model was performed on the ANALAC (Alternating Current Analog Computer) utilising the GEL and CI Integrator Modules. The simulation results were verified by testing the convergence of various examples, whose solutions are well know. The results are given in the Anex 1. In addition the feasibility of solving this same problem on a digital computer (IBM 1130) was considered (chap IV. 3). In the Anex 2, FORTRAN programs of the digital technics are presented.

In end-stage kidney disease, kidneys no longer sufficiently perform their intended functions, for example, filtering blood of excess fluid and waste products. Without transplantation or chronic dialysis, this condition results in mortality. Dialysis is the process of artificially replacing some of the kidney’s functionality by passing blood from a patient through an external semi-permeable membrane to remove toxins and excess fluid. The rate of ultrafiltration – the rate of fluid removal from blood – is controlled by the hemodialysis machine per prescription by a nephrologist. While essential for survival, hemodialysis is fraught with clinical challenges. Too high a fluid removal rate could result in hypotensive events where the patient blood pressure drops significantly which is associated with adverse symptoms such as exhaustion, fainting, nausea, and cramps, leading to decreased patient quality of life. Too low a fluid removal rate, in contrast, could leave the patient fluid overloaded often leading to hypertension, which is associated with adverse clinical outcomes. Previous work in our lab demonstrated via simulations that it is possible to design an individualized, model-based ultrafiltration profile with the aim of minimizing hypotensive events during dialysis. The underlying model using in the design of the individualized ultrafiltration profile is a simplified, linearized, continuous-time model derived from a nonlinear model of the patient’s fluid dynamics system. The parameters of the linearized model are estimated from actual patient’s temporal hematocrit response to ultrafiltration. However, the parameter identification approach used in the above work was validated using limited clinical data and often failed to achieve accurate estimation. Against this backdrop, this thesis had three goals: (1) obtain a new, larger set of clinical data, (2) improve the linearized model to account for missing physiological aspects of fluid dynamics, and (3) develop and validate a new approach for identification of model parameters for use in the design of individualized ultrafiltration profiles. The first goal was accomplished by retrofitting an entire in-center, hemodialysis clinic in Holyoke, MA, with online hematocrit sensors (CliC devices), Wi-Fi boards, and a laptop with a radio receiver. Treatment data was wirelessly uploaded to a laptop and redacted files and manual treatment charts were made available for our research per approved study IRB. The second goal was accomplished by examining the nonlinear system of equations governing the relevant dynamics and simplifying the model to an identifiable case. Considerations of refill not accounted for fully in previous works were integrated into the Cardimino 7 linearized model, adding terms but making it generally more accurate to the underlying dynamics. The third goal was accomplished by developing an algorithm to identify major system parameters, using steady-state behavior to effectively reduce the number of parameters to identify. The system was subsequently simulated over an established range for all remaining parameters, compared to collected data, with the lowest RMS error case being taken as the set of identified parameters. While intra-patient identified individual model parameters were associated with a high degree of variability, the system’s steady-state gain and time constants exhibited more consistent estimations, though the time constants still had high variability overall. Parameter sensitivity analysis shows high sensitivity to small changes in individual model parameters. The addition of refill dynamics in the model constituted a significant improvement in the identifiability of the measured dynamics, with up to 70% of data sets resulting in successful estimates. Unmodelled dynamics, resulting from unmeasured input variables, resulted in about 30% of measured data sets unidentifiable. The updated model and associated parameter identification developed in this thesis can be readily integrated with the model-based design of individualized UFR profile.

Accurate ship-motion prediction is important because it is directly related to the design, control, and economic operation of ships. Many methods are available for studying and predicting ship motions, including time-domain, strip-theory, and system-identification-based predictions. Time-domain and strip-theory predictions suffer from several physical and computational limitations. In this work, we use system-identification techniques to predict ship motions. We establish an identification methodology that can handle general finite-degree-of-freedom (FDOF) models of ship motions. To establish this methodology, we derive the correct form of the equations of motion. This form contains all relevant linear and nonlinear terms. Moreover, it explicitly specifies the dependence of the linear and nonlinear parameters on the forward speed. The energy-formulation approach is utilized to obtain full nonlinear ship-motion equations. The advantages of using this formulation are that self-sustained motions are not allowed and the dependence of the parameters on the forward speed is derived explicitly. The data required for the identification techniques are generated using the Large Amplitude Motions Program (LAMP) developed by the Science Applications International Corporation (SAIC). The ship studied in this work is a Series 60 ship, which is a military cargo ship. LAMP data for different sea states and forward speeds are used to identify and predict the ship motions. For linear parametric identification, we use the Eigensystem Realization Algorithm (ERA) to determine the coefficients in the linearly coupled equations and the effects of the forward speed on these coefficients. For linear nonparametric identification, we present a new analysis technique, namely, the circular-hyperbolic decomposition (CHD), which avoids the leakage effects associated with the discrete Fourier transform (DFT). The CHD is then utilized to determine transfer functions and response amplitude operators (RAOs). For nonlinear parametric identification, we present a methodology that is a combination of perturbation techniques and higher-order spectral moments. We apply this methodology to identify the nonlinear parameters that cause parametric roll resonance. The level of accuracy of the models and the parameter estimates are determined by validations of the predicted ship motions with the LAMP data. / Ph. D.

A study of the nonlinear vibrations of metallic cantilever beams and plates subjected to transverse harmonic excitations is presented. Both experimental and theoretical results are presented. The primary focus is however on the transfer of energy between widely spaced modes via modulation. This phenomenon is studied both in the presence and absence of a one-to-one internal resonance. Reduced-order models using Galerkin discretization are also developed to predict experimentally observed motions. A good qualitative agreement is obtained between the experimental and numerical results. Experimentally the energy transfer between widely spaced modes is found to be a function of the closeness of the modulation frequency to the natural frequency of the first mode. The modulation frequency, which depends on various parameters like the amplitude and frequency of excitation, damping factors, etc., has to be near the natural frequency of the low-frequency mode for significant transfer of energy from the directly excited high-frequency mode to the low-frequency mode. An experimental parametric identification technique is developed for estimating the linear and nonlinear damping coefficients and effective nonlinearity of a metallic cantilever beam. This method is applicable to any single-degree-of-freedom nonlinear system with weak cubic geometric and inertia nonlinearities. In addition, two methods, based on the elimination theory of polynomials, are proposed for determining both the critical forcing amplitude as well as the jump frequencies in the case of single-degree-of-freedom nonlinear systems. An experimental study of the response of a rectangular, aluminum cantilever plate to transverse harmonic excitations is also conducted. Various nonlinear dynamic phenomena, like two-to-one and three-to-one internal resonances, external combination resonance, energy transfer between widely spaced modes via modulation, period-doubled motions, and chaos, are demonstrated using a single plate. It is again shown that the closeness of the modulation frequency to the natural frequency of the first mode dictates the energy transfer between widely spaced modes. / Ph. D.

A method for developing transient, predictive models of gas turbine engine performance using system identification techniques in conjunction with test cell data has been successfully demonstrated. Test cell data were obtained for both transient and steady-state operation from two F402-RR-406A USMC AV-8B engines at the Naval Aviation Depot (NADEP), Cherry Point, North Carolina. One engine was run to gather a single set of steady-state data consisting of 24 subsets of five seconds of data. The other engine was run to obtain two sets of transient data, recorded at three different rates of engine acceleration for each set. The acceleration rates of 3, 25, and 100 degrees of throttle per second were preset in the test cell controls. These rates correspond to the angular velocity of the fuel throttle during an acceleration. Each of these six transient test runs consisted of 25 seconds of data. Data were captured at a rate of five Hertz over the engine operating range from idle (26% Low Pressure spool speed) to full military power (105% LP spool speed) for all cases. A BASIC code developed at the NADEP required significant modification before it could be used to reduce the data. The modified code generated engine operating points consisting of mass flow rate, total pressure ratio, spool speed, and rate of acceleration for the inner fan, outer fan, and high pressure compressor. Finally, a multivariate regression technique using the SAS language was developed in cooperation with the Virginia Tech Statistical Consulting Center. This technique was used to generate a closed-form model of each component capable of predicting operating points at spool speeds and acceleration rates intermediate to those measured. / Master of Science

Hydrogen-powered engines have been gaining increasing interest due to the global concerns of the effects of hydrocarbon combustion on climate change. Gas turbines are suitable for operation on hydrogen fuel. This thesis reports the results of investigations of the special requirements of the fuel controller for a hydrogen gas turbine. In this investigation, a digital fuel controller for a hydrogen-fueled modified Pratt and Whitney PT6A-20 turboprop engine was successfully designed and implemented. Included in the design are safety measures to protect the operating personnel and the engine. A redundant fuel control is part of the final design to provide a second method of managing the engine should there be a malfunction in any part of the primary controller. Parallel to this study, an investigation of the existing hydrogen combustor design was performed to analyze the upper stability limits that were restricting the operability of the engine. The upstream propagation of the flame into the premixer, more commonly known as a flashback, routinely occurred at 150 shaft horsepower during engine testing. The procedures for protecting the engine from a flashback were automated within the fuel controller, significantly reducing the response time from the previous (manual) method. Additionally, protection measures were added to ensure the inter-turbine temperature of the engine did not exceed published limits. Automatic engine starting and shutdown procedures were also added to the control logic, minimizing the effort needed by the operator. The tested performance of the engine with each of the control functions demonstrated the capability of the controller. Methods to generate an engine-specific fuel control map were also studied. The control map would not only takes into account the operability limits of the engine, but also the stability limits of the premixing devices. Such a map is integral in the complete design of the engine fuel controller. / Master of Science