Dissertations / Theses on the topic 'Dynamic system identification'
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Wester, Stefan. "Dynamic system identification of a strainfield." Thesis, KTH, Reglerteknik, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-105153.
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To be able to monitor forces acting on objects is important for a lot of dierent applications. In this case the object is a big steel disc and the forces to be monitored are those acting on the rim of the disc. This is done with strain gauges that register changes in the internal strain eld. This is then run through a system model that outputs the equivalent force for that strain eld. The system model is created through a static system identication consisting of a series of test pushes on the rim of the disc. This method of system identication has a series of problem mainly that it is time consuming. The thesis presents a proof-of-concept of a dynamic system identication method. Instead of pressure applied while stationary the pressure is applied by rotating the disc against another smaller steel disc and performing the system identication on this continuous data. An algorithm to use the data is tested in simulation and the results are analyzed and proven successful. Then a experiment is performed, recording data and running the algorithm. The dynamic system identication is shown to give almost equal results to the static one. The dierence can be accounted for as problems with the force measuring or that the dynamic system identication is actually more accurate than the static one. The algorithm is concluded to work and give an advantage over the old algorithm in form of the time it takes to perform it. It has a possibility to be more accurate and also to be able to identify forces in more directions than straight into the disc.
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Deng, Chuang. "System identification in dynamic positron emission tomography /." View abstract or full-text, 2008. http://library.ust.hk/cgi/db/thesis.pl?ECED%202008%20DENG.
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Singhavilai, Thamvarit. "Identification of electric power system dynamic equivalent." Thesis, University of Strathclyde, 2011. http://oleg.lib.strath.ac.uk:80/R/?func=dbin-jump-full&object_id=15647.
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Peng, Tian. "Structural system identification by dynamic observability technique." Doctoral thesis, Universitat Politècnica de Catalunya, 2021. http://hdl.handle.net/10803/672173.
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Structure system identification (SSI) can be classified as static and dynamic depending on the type of excitation. SSI by Observability Method (OM) using static tests was proposed and analyzed to address the observability of the estimated parameters. This mathematical approach has been used in other fields such as hydraulics, electrical, and power networks or transportation. Usually, the structural behavior of engineering structures can be identified according to dynamic characteristics such as mode shapes, natural frequencies, and damping ratios. However, the analysis of SSI by dynamic Observability Method using dynamic information is lacking.
This Ph.D. thesis developed the dynamic Observability Method using masses, modal frequencies, modal deflections based on the static OM to obtain the geometrical and mechanical parameters of the structure. This thesis mainly contains three aspects of work.
Firstly, in chapter 3, the development, for the first time, of constrained observability techniques (COM) for parametric estimation of structures using dynamic information such as frequencies and mode-shapes was proposed. New algorithms are introduced based on the dynamic eigenvalue equation. Two step by step examples are used to illustrate the functioning of these. Parametric expressions for the observed variables are successfully obtained,which will allow the study of the sensitivity of each of the variables in the problem and the error distribution, which is an advantage with respect to non-parametric SSI techniques. A large structure is used to validate this new application, whose structural properties can be obtained satisfactorily in either the whole or local analysis, and the results show that the required measurement set is smaller than the required for a static analysis. Chapters 4 and 5 are the applications of COM to fill the shortcomings of current research, such as the optimal SHM+SSI strategy and uncertainty quantification.
Secondly, in chapter 4, the role of the SHM strategy and the SSI analysis based on the Constrained Observability Method (COM), which aims at reducing the estimation error, is discussed. A machine learning decision tool to help building the best-combined strategy of SHM and SSI that can result in the most accurate estimations of the structural properties is proposed, and the combination of COM and decision tree algorithm is used for the first time. The machine learning algorithm is based on the theory of Decision Trees. Decision trees are firstly presented to investigate the influence of the variables (layout of bridge, span length, measurement set, and weight factor in the objective function of the COM) involved in the SHM+SSI process on the error estimation in a general structure. The verification of the method with a real bridge with different levels of damage shows that the method is robust even for a high damage level, showing the SHM+SSI strategy that yields the most accurate estimation.
Finally, an analysis of uncertainty quantification (UQ) is necessary to assess the effect of uncertainties on the estimated parameters and to provide a way to evaluate these uncertainties. This work is carried out in chapter 5. There are a large number of UQ approaches in science and engineering. It is identified that the proposed dynamic Constrained Observability Method (COM) can make up for some of the shortcomings of existing methods. After that, the COM is used to analyze a real bridge. A result is compared with a method based on a Bayesian approach demonstrating its applicability and correct performance through the analysis of a reinforced concrete beam.La identificación del sistema estructural puede clasificarse como estático y dinámico según el tipo de excitación. Recientemente, se ha propuesto y analizado SSI mediante el Método de Observabilidad (OM) utilizando medidas experimentales de pruebas estáticas para abordar la observabilidad de los parámetros estimados. Este enfoque matemático se ha utilizado en otros campos como la hidráulica, la electricidad y las redes de energía o transporte. Por lo general, el comportamiento de las estructuras de ingeniería se puede identificar de acuerdo con características dinámicas como formas modales, frecuencias naturales y amortiguamiento. Sin embargo, hasta la fecha, no se han propuesto análisis de SSI por el método de observabilidad utilizando información dinámica. Esta tesis desarrolla el Método de Observabilidad Dinámico usando masas, frecuencias propias y modos de vibración para identificar los parámetros mecánicos de los elementos de una estructura. A tal fin, se desarrollan tres líneas de trabajo. En primer lugar, se propone la primera aplicación de técnicas de observabilidad restringida para la estimación paramétrica de estructuras utilizando información dinámica como frecuencias y modos de vibración. Se introducen nuevos algoritmos basados en la ecuación dinámica de valores propios. Se utilizan dos ejemplos paso a paso para ilustrar su l funcionamiento. Se obtienen con éxito expresiones paramétricas para las variables observadas, lo que permite estudiar la sensibilidad de cada una de las variables en el problema y la distribución del error, lo cual es una ventaja respecto a las técnicas SSI no paramétricas. Para la validación de esta nueva aplicación se utiliza una estructura compleja, cuyas propiedades estructurales se pueden obtener satisfactoriamente en el análisis total o local, y los resultados muestran que el conjunto de medidas requerido es menor que en el caso del análisis estático. Los capítulos 4 y 5 son las aplicaciones de COM para subsanar las deficiencias de la investigación actual, como la estrategia óptima de SHM + SSI y la cuantificación de la incertidumbre. En segundo lugar, se discute el papel que juega la estrategia SHM y el análisis SSI basado en el Método de Observabilidad Restringido (COM), con el objetivo reducir el error de estimación. Se propone una herramienta de decisión de aprendizaje automático para ayudar a construir la mejor estrategia combinada de SHM y SSI que puede resultar en estimaciones más precisas de las propiedades estructurales. Para ello, se utiliza la combinación de algoritmo COM dinámico y el método de los árboles de decisión por primera vez. Los árboles de decisión se presentan, en primer lugar, como una herramienta útil para investigar la influencia de las variables (tipología estructural del puente, longitud del vano, conjunto de medidas experimentales y pesos en la función objetivo) involucradas en el proceso SHM + SSI con el objetivo de minimizar el error en la identificación de la estructura. La verificación del método con un puente real con diferentes niveles de daño muestra que el método es robusto incluso para un nivel de daño importante, resultando en la estrategia SHM + SSI que arroja la estimación más precisa. Por último, es necesario un análisis de cuantificación de la incertidumbre (UQ) para evaluar el efecto de las incertidumbres sobre los parámetros estimados y proporcionar una forma de evaluar las incertidumbres en los parámetros identificados. Hay una gran cantidad de enfoques de UQ en ciencia e ingeniería. En primer lugar, se identifica que el Método de Observabilidad Restringido (COM) dinámico propuesto puede compensar algunas de las deficiencias de los métodos existentes. Posteriormente, el COM se utiliza para analizar un puente real. Se compara el resultado con un método existente basado, demostrando su aplicabilidad y correcto desempeño mediante la aplicación a una viga de hormigón armado. Además, se obtiene como resultado que el mejor conjunto de puntos de medición experimental dependerá de la incertidumbre epistémica incorporada en el modelo. Dado que la incertidumbre epistémica se puede eliminar a medida que aumenta el conocimiento de la estructura, la ubicación óptima de los sensores debe lograrse considerando no sólo la precisión de los mismos, sino también los modos de vibración de la estructura.
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Stiles, Peter A. "Improvement of structural dynamic models via system identification." Thesis, Virginia Tech, 1988. http://hdl.handle.net/10919/44086.
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Proper mathematical models of structures are beneficial for designers and
analysts. The accuracy of the results is essential. Therefore, verification and/or
correction of the models is vital. This can be done by utilizing experimental results
or other analytical solutions. There are different methods of generating the accurate
mathematical models. These methods range from completely analytically derived
models, completely experimentally derived models, to a combination of the two.
These model generation procedures are called System Identification. Today a
popular method is to create an analytical model as accurately as possible and then
improve this model using experimental results.
This thesis provides a review of System Identification methods as applied to
vibrating structures. One simple method and three more complex methods, chosen
from current engineering literature, are implemented on the computer. These
methods offer the capability to correct a discrete (for example, finite element based)
model through the use of experimental measurements. The validity of the methods
is checked on a two degree of freedom problem, an eight degree of freedom example
frequently used in the literature, and with experimentally derived vibration results of
a free-free beam.Master of Science
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Ge, Ma. "Structural damage detection and identification using system dynamic parameters." Related electronic resource: Current Research at SU : database of SU dissertations, recent titles available full text, 2005. http://wwwlib.umi.com/cr/syr/main.
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Mao, Lei. "Frequency-based structural damage identification and dynamic system characterisation." Thesis, University of Edinburgh, 2012. http://hdl.handle.net/1842/7945.
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This thesis studies structural dynamic system identification in a frequency-based framework. The basic consideration stems from the fact that frequencies may generally be measured with higher accuracy than other pertinent modal data such as mode shapes; however only a limited number of frequencies may be measured in the conventional context of natural frequencies. Being able to measure extra frequencies is a key to the success of a frequency-based method. The main part of the thesis is therefore organised around the involvement of the so-called artificial boundary condition (ABC) frequencies to augment the frequency dataset for general structural damage identification. In essence, the ABC frequencies correspond to the natural frequencies of the system with additional pin supports, but may be extracted from specially configured incomplete frequency response function matrix of the original structure without the need of physically imposing the additional supports. In the first part of the research, a particular focus is placed on the actual extraction of these ABC frequencies from physical experiments through effective modal testing, data collection, data processing and analysis. The influences of key processes involved in a typical modal experimental procedure, including high-fidelity measurement of the (impact) excitation input, averaging, windowing, and an effective use of post-processing techniques, particularly the Singular Value Decomposition (SVD) technique, are scrutinised in relation to the extraction of the ABC frequencies. With appropriate implementation of testing and data processing procedures, results demonstrate that all one-pin and two-pin ABC frequencies from the first few modes can be extracted with good quality in a laboratory setting, and the accuracy of extracted ABC frequencies is comparable to natural frequencies of corresponding orders. A comprehensive study is then carried out to investigate the sensitivities of ABC frequencies to damages. Two-pin ABC frequency sensitivity is formulated by extending the expression of anti-resonance sensitivity. On this basis, the mode shape contribution is adopted as a criterion for the selection of more sensitive ABC frequencies to be employed in detailed parameter identification or finite element model updating procedures. The soundness of using ABC frequencies in structural parameter identification and the effectiveness of the above ABC frequency selection method are subsequently examined through case studies involving laboratory experiments and the corresponding FE model updating. Furthermore, a preliminary study is carried out to examine the possibility of formulating ABC frequency-based damage indicator, herein with an analogy to the mode shape curvature, for direct damage assessment. As an extended investigation in the general framework of frequency-based dynamic identification, in the last part of the thesis, a complex dynamic system, namely a railway bridge under moving loads & masses, is evaluated with regard to the various frequency characteristics involved. The variation of the natural frequencies of the bridge-moving mass system, as well as the presence of the apparent frequencies from the trainloads, are analysed in detail. Besides simplified theoretical analysis, a computational model is developed to simulate the combined bridge-moving vehicle/train system, where the vehicle mass is coupled with the bridge via surface contact. The model is verified by comparison with field measurement data and theoretical predictions. Parametric studies enable a clear identification of the correlation of the frequency contents between the response and the trainload, and provide new insight into the significance of the so-called driving and dominant frequencies. It is found that much of the dynamic response phenomena, including the resonance effect, may be explained from the view point of the frequency characteristics of the trainload pattern, which is governed primarily by the ratio between the carriage length and the bridge length. Finally, a resonance severity indicator (the Z-factor) is developed for the assessment of the resonance effect in the railway bridge response when the trainload moves at a resonance speed. Numerical results demonstrate that the proposed methods are effective for the determination of the critical speed and the resonance effects, including the situations where a significant carriage mass is incorporated.
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McCormack, Anthony Sean. "The design of periodic excitations for dynamic system identification." Thesis, University of Warwick, 1995. http://wrap.warwick.ac.uk/3671/.
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System identification techniques are developed for modelling linear and nonlinear systems. The main results of the work are concerned with the design and utilisation of periodic perturbation signals in general areas of time- and frequency-domain system identification. A design strategy is given for a new class of perturbation signals, together with examples of their use in system identification applications. Signal processing procedures are developed for the practical treatment of drift disturbances and transient effects, and also for the detection of nonlinear contributions to the measurement data. The techniques rely completely on the periodicity of the excitation, and so the advantageous properties of periodic input signals are considered in detail. The use of periodic excitations in discrete- and continuous-time nonlinear system identification is also reported, with the identification methods illustrating the worth of frequency-domain measurements in this area. An automatic tuning procedure for PID controllers is also developed, which illustrates an application of system identification techniques to control problems.
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Szabo, Andrew P. "System Identification and Model-Based Control of Quadcopter UAVs." Wright State University / OhioLINK, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=wright1553197265058507.
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Zaidi, Salman [Verfasser]. "System Identification of Stochastic Nonlinear Dynamic Systems using Takagi-Sugeno Fuzzy Models / Salman Zaidi." Kassel : Kassel University Press, 2019. http://d-nb.info/118450279X/34.
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Martinez-Flores, Rene. "DAMAGE ASSESSMENT POTENTIAL OF A NOVEL SYSTEM IDENTIFICATION TECHNIQUE - EXPERIMENTAL VERIFICATION." Diss., Tucson, Arizona : University of Arizona, 2005. http://etd.library.arizona.edu/etd/GetFileServlet?file=file:///data1/pdf/etd/azu%5Fetd%5F1028%5F1%5Fm.pdf&type=application/pdf.
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Feng, Xiaodan Selina. "Dynamic equivalencing of distribution network with embedded generation." Thesis, University of Edinburgh, 2012. http://hdl.handle.net/1842/6208.
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Renewable energy generation will play an important role in solving the climate change problem. With renewable electricity generation increasing, there will be some significant changes in electric power systems, notably through smaller generators embedded in the distribution network. Historically insignificant volumes of Embedded Generation (EG) mean that traditionally it has been treated by the transmission system operator as negative load, with its impact on the dynamic behaviour of power systems neglected. However, with the penetration level increasing, EG would start to influence the dynamics and stability of the transmission network. Hence the dynamic behaviour of distribution network cannot be neglected any more. In most cases, a detailed distribution network model is not always available or necessary for the study of transmission network dynamics and stability. Thus a dynamic equivalent model of the distribution network that keeps its essential dynamic behavior, is required. Most existing dynamic equivalencing methods are based on the assumption that the detailed information of the complete power system is known. Dynamic equivalencing methods based on coherency of the machines have been applied to transmission networks but cannot be applied to distribution networks due to their radial structure. Hence an alternative methodology has been developed in this project to derive the dynamic equivalent model of the distribution network using system identification, without the detailed information of the distribution network necessarily known. Case studies have been accomplished in PSS/E on a model of the Scottish transmission network with the distribution network in Dumfries and Galloway. Embedded generation with a certain penetration level in either conventional generation or DFIG wind generation has been added to the model of the distribution network. The dynamic equivalent models of the distribution network are compared with the original distribution network model using a series of indicators. A constant power model has also been involved in the comparison to illustrate the advantage of using the dynamic equivalent to represent the distribution network. The results suggest that a proper dynamic equivalent model derived using this methodology may have better agreement to the original power system dynamic response than constant power equivalent. A discussion on factors that influence the performance of the dynamic equivalent model, is given to indicate the proper way to use this methodology. The major advantage of the dynamic equivalencing methodology developed in this project is that it can potentially use the time series obtained from measurements to derive the dynamic equivalent models without knowing detailed information on the distribution network. The derived dynamic equivalent, in a simple spate-space form, can be implemented in commercial simulation tools, such as PSS/E.
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CANTERA, JOSE MARIA CALVO. "DETECTION AND IDENTIFICATION OF ANOMALIES IN POWER SYSTEM DYNAMIC STATE ESTIMATION." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 1987. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=9891@1.
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ELETROBRAS - CENTRAIS ELÉTRICAS BRASILEIRAS S. A.Este trabalho apresenta uma comparação entre o desempenho dos estimadores dinâmicos e rastreador, em sistemas de potência operando sob condições quase-estacionárias, considerando suas características de previsão e filtragem. A partir desta comparação, propõe-se um estimador dinâmico que incorpora as principais vantagens dos estimadores previamente mencionados. Além disso, apresenta-se um novo esquema de detecção e identificação de anormalidades (erros grosseiros nas medidas, mudanças brusca no ponto de operação do sistema e erros na configuração da rede), esquema este apropriadamente construído para algoritmos de estimação dinâmica. Resultados numéricos ilustram o desempenho deste novo algoritmo sob diferentes condições operativas.
This work presents a comparison between the performance of dynamic and tracking estimators, in power systems operating under quasi-static conditions, concerning their characteristics of forecasting and filtering. From this comparison, a new dynamic estimator which incorporates the main advantages of the previous estimators is proposed. Also, a new scheme of detection and identification of anomalies (gross errors in the measurements, sudden changes in the system operating point and errors in the network configuration) is presented. This scheme is properly built for dynamic algorithms. Numerical results showing the performance of the new algorithm under different operational conditions are discussed.
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Benedetti, Lorenzo. "Substructuring approache in state space models for dynamic system parameters identification." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2011. http://amslaurea.unibo.it/2325/.
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In the recent decade, the request for structural health monitoring expertise increased exponentially in the United States. The aging issues that most of the transportation structures are experiencing can put in serious jeopardy the
economic system of a region as well as of a country. At the same time, the monitoring of structures is a central topic of discussion in Europe, where the preservation of historical buildings has been addressed over the last four
centuries. More recently, various concerns arose about security performance of civil structures after tragic events such the 9/11 or the 2011 Japan earthquake: engineers looks for a design able to resist exceptional loadings due to
earthquakes, hurricanes and terrorist attacks. After events of such a kind, the assessment of the remaining life of the structure is at least as important as the initial performance design. Consequently, it appears very clear that the introduction of reliable and accessible damage assessment techniques is crucial for the localization of issues and for a correct and immediate rehabilitation.
The System Identification is a branch of the more general Control Theory. In Civil Engineering, this field addresses the techniques needed to find mechanical characteristics as the stiffness or the mass starting from the signals captured by sensors.
The objective of the Dynamic Structural Identification (DSI) is to define, starting from experimental measurements, the modal fundamental parameters of a generic structure in order to characterize, via a mathematical model, the dynamic behavior.
The knowledge of these parameters is helpful in the Model Updating procedure, that permits to define corrected theoretical models through experimental validation. The main aim of this technique is to minimize the differences between the theoretical model results and in situ measurements of
dynamic data.
Therefore, the new model becomes a very effective control practice when it comes to rehabilitation of structures or damage assessment.
The instrumentation of a whole structure is an unfeasible procedure sometimes because of the high cost involved or, sometimes, because it’s not possible to physically reach each point of the structure. Therefore, numerous scholars
have been trying to address this problem. In general two are the main involved methods.
Since the limited number of sensors, in a first case, it’s possible to gather time histories only for some locations, then to move the instruments to another location and replay the procedure. Otherwise, if the number of sensors is
enough and the structure does not present a complicate geometry, it’s usually sufficient to detect only the principal first modes. This two problems are well presented in the works of Balsamo [1] for the application to a simple system and Jun [2] for the analysis of system with a
limited number of sensors.
Once the system identification has been carried, it is possible to access the actual system characteristics. A frequent practice is to create an updated FEM model and assess whether the structure fulfills or not the requested functions.
Once again the objective of this work is to present a general methodology to analyze big structure using a limited number of instrumentation and at the same time, obtaining the most information about an identified structure without
recalling methodologies of difficult interpretation. A general framework of the state space identification procedure via OKID/ERA algorithm is developed and
implemented in Matlab. Then, some simple examples are proposed to highlight the principal characteristics and advantage of this methodology. A new algebraic manipulation for a prolific use of substructuring results is developed
and implemented.
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Yang, Yang. "Two-dimensional dynamic analysis of functionally graded structures by using meshfree boundary-domain integral equation method." Thesis, University of Macau, 2015. http://umaclib3.umac.mo/record=b3335354.
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Lyubchyk, Leonid, and Galina Grinberg. "Inverse Dynamic Models in Chaotic Systems Identification and Control Problems." Thesis, Ternopil National Economic University, 2018. http://repository.kpi.kharkov.ua/handle/KhPI-Press/36824.
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Inverse dynamic models approach for chaotic system synchronization in the presence of uncertain parameters is considered. The problem is identifying and compensating unknown state-dependent parametric disturbance describing an unmodelled dynamics that generates chaotic motion. Based on the method of inverse model control, disturbance observers and compensators are synthesized. A control law is proposed that ensures the stabilization of chaotic system movement along master reference trajectory. The results of computational simulation of controlled Rösller attractor synchronization are also presented.
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Ciccone, Francesco. "Dynamic system model identification of inertial sensors by means of neural networks." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2020. http://amslaurea.unibo.it/21548/.
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The thesis presents the design of a feedforward neural network for the model identification of a dynamical system of a general inertial sensor.
According to the universal approximation theorem, feedforward network with a linear output layer and at least one hidden layer with any activation function can approximate any measurable function with any desired non-zero amount of error provided that the network is given enough hidden units. This theorem simply states that no matter what function we are trying to learn there is always a neural network which will be able to represent the function. So, strong of this result, the work consisted to simulate a black box approach in which the data of input and output of the dynamical system have been used first to train the neural network to predict the future behaviour of the system itself, and then to validate the model.
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Arcila, Ana María Molina. "High resolution Fabry-Pérot interferometer - dynamic system modeling and nanopositioning control system design." Universidade de São Paulo, 2014. http://www.teses.usp.br/teses/disponiveis/3/3139/tde-23122014-155735/.
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This work represents the research project to obtain the degree of Master of Sciences in Electrical Engineering, specializing in Systems Engineering, at the Escola Politécnica of the Universidade de São Paulo, in São Paulo, Brazil. The main objective of the project is to design the mirror nanopositioning controller of the state-of-the-art Fabry-Pérot interferometer to be installed in the Brazilian Tunable Filter Imager (BTFI) on the Southern Astrophysical Research (SOAR) telescope in Chile. A three-input-three-output multivariable prototype of the Fabry-Pérot system is comprised of three high-range Amplified Piezoelectric Actuators (APA) of 360 m stroke and three 400 m range capacitive measurement systems. A characterization of the instrumentation of the system, which consists of capacitive sensors and capacitance-to-voltage converters, piezoelectric actuators, power drivers of the piezoelectric actuators and data acquisition system was done as part of the identification and study of the system. With the characterization of the system, a sixth-order complete system model was built on top of a second-order piezoelectric actuator parametric model, required for the design of the controllers. Subsequently, the scientific specifications were translated to a control problem and the design of a robust controller was made following the Linear Quadratic Gaussian/Loop Transfer Recovery (LQG/LTR) method. Also a Proportional-Integral controller tuned using a genetic algorithm was designed to be used as benchmark. Finally the built controllers were validated in the real system. Results show that both controllers achieve the performance requirements of following reference signals and having null steady-state error. However, the robust controller is by far the best suited for the Fabry- Pérot instrument in terms of performance and stability because of its higher bandwidth and robustness to modeling errors.Este trabalho apresenta o projeto de pesquisa para obtenção do título de Mestre em Engenharia Elétrica, área de concentração de engenharia de sistemas, da Escola Politécnica da Universidade de São Paulo. O objetivo principal deste projeto foi desenvolver um controlador de nanoposicionamento para o interferômetro de Fabry-Pérot que será instalado no instrumento BTFI (Brazilian Tunable Filter Imager), no telescópio SOAR (Southern Astrophysical Research Telescope), no Chile. O interferômetro de Fabry-Pérot é um sistema multivariável de três entradas e três saídas composto por três atuadores piezoelétricos de 370 m de deslocamento, e três sistemas capacitivos de medida de distância de 400 m de faixa de medição. A caracterização da instrumentação do sistema, que consiste em sensores capacitivos, conversores de capacitância para tensão, atuadores piezoelétricos, drivers de potência para os atuadores piezoelétricos e sistemas de aquisição de dados, fez parte do estudo e da identificação do sistema. Após a caracterização da instrumentação, foi desenvolvido um modelo físico de sexta ordem para o sistema completo, partindo do modelo de segunda ordem dos atuadores piezoelétricos. Este modelo é necessário para o projeto dos controladores. Subsequentemente, as especificações científicas foram traduzidas em um problema de controle e o projeto do controlador robusto foi feito seguindo a técnica LQG/LTR (Linear Quadratic Gaussian/Loop Transfer Recovery). Um controlador Proporcional-Integral (PI) também foi desenvolvido e sintonizado usando um algoritmo genético, para funcionar como ponto de comparação. Finalmente, os controladores desenvolvidos foram validados no sistema real. Com os resultados concluiu-se que ambos controladores atingiram as especificações de desempenho no que diz respeito a seguir sinais de referência com erro nulo no estado estacionário. Pôde-se concluir ainda que o controlador robusto mostrou-se mais adaptado ao instrumento Fabry- Pérot em termos de desempenho e estabilidade, pois, comparado ao PI, é um controlador com maior largura de banda e robustez aos erros de modelamento.
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Lyubchyk, Leonid, Vladislav Kolbasin, and Galina Grinberg. "Nonlinear dynamic system kernel based reconstruction from time series data." Thesis, ТВіМС, 2015. http://repository.kpi.kharkov.ua/handle/KhPI-Press/36826.
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A unified approach to reccurent kernel identification algorithms design is proposed. In order to fix the auxiliary vector dimension, the reduced order model kernel method is proposed and proper reccurent identification algorithms are designed.
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Burak, Senad A. "Modelling and identification of dynamic systems using modal and spectral data /." Title page, contents and abstract only, 1997. http://web4.library.adelaide.edu.au/theses/09PH/09phb945.pdf.
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Tugsal, Umut. "FAULT DIAGNOSIS OF ELECTRONIC FUEL CONTROL (EFC) VALVES VIA DYNAMIC PERFORMANCE TEST METHOD." ProQuest, 2009. http://hdl.handle.net/1805/2094.
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Indiana University-Purdue University Indianapolis (IUPUI)Electronic Fuel Control (EFC) valve regulates fuel flow to the injector fuel supply line in the Cummins Pressure Time (PT) fuel system. The EFC system controls the fuel flow by means of a variable orifice that is electrically actuated. The supplier of the EFC valves inspects all parts before they are sent out. Their inspection test results provide a characteristic curve which shows the relationship between pressure and current provided to the EFC valve. This curve documents the steady state characteristics of the valve but does not adequately capture its dynamic response. A dynamic test procedure is developed in order to evaluate the performance of the EFC valves. The test itself helps to understand the effects that proposed design changes will have on the stability of the overall engine system. A by product of this test is the ability to evaluate returned EFC valves that have experienced stability issues. The test determines whether an EFC valve is faulted or not before it goes out to prime time use. The characteristics of a good valve and bad valve can be observed after the dynamic test. In this thesis, a mathematical model has been combined with experimental research to investigate and understand the behavior of the characteristics of different types of EFC valves. The model takes into account the dynamics of the electrical and mechanical portions of the EFC valves. System Identification has been addressed to determine the transfer functions of the different types of EFC valves that were experimented. Methods have been used both in frequency domain as well as time domain. Also, based on the characteristic patterns exhibited by the EFC valves, fuzzy logic has been implemented for the use of pattern classification.
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Goel, Gautam. "Dynamic flux estimation a novel framework for metabolic pathway analysis /." Diss., Atlanta, Ga. : Georgia Institute of Technology, 2009. http://hdl.handle.net/1853/31769.
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Thesis (Ph.D)--Biomedical Engineering, Georgia Institute of Technology, 2010.Committee Chair: Voit, Eberhard O.; Committee Member: Butera, Robert; Committee Member: Chen, Rachel; Committee Member: Kemp, Melissa; Committee Member: Neves, Ana Rute. Part of the SMARTech Electronic Thesis and Dissertation Collection.
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Pham, Hoang Anh [Verfasser], and Christian [Akademischer Betreuer] Bucher. "Dynamic system identification based on selective sensitivity / Hoang Anh Pham ; Betreuer: Christian Bucher." Weimar : Professur Baumechanik, 2007. http://d-nb.info/1115335561/34.
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Föll, Roman [Verfasser]. "Sparse Deep Gaussian Process Approximation and Application of Dynamic System Identification / Roman Föll." München : Verlag Dr. Hut, 2021. http://d-nb.info/123284750X/34.
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Narby, Erik. "Modeling and Estimation of Dynamic Tire Properties." Thesis, Linköping University, Department of Electrical Engineering, 2006. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-6153.
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Information about dynamic tire properties has always been important for drivers of wheel driven vehicles. With the increasing amount of systems in modern vehicles designed to measure and control the behavior of the vehicle information regarding dynamic tire properties has grown even more important.
In this thesis a number of methods for modeling and estimating dynamic tire properties have been implemented and evaluated. The more general issue of estimating model parameters in linear and non-linear vehicle models is also addressed.
We conclude that the slope of the tire slip curve seems to dependent on the stiffness of the road surface and introduce the term combined stiffness. We also show that it is possible to estimate both longitudinal and lateral combined stiffness using only standard vehicle sensors.
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Joodi, Benjamin Michael. "Comparative Assessment of Frequency Dependent Joint Properties Using Direct and Inverse Identification Methods." The Ohio State University, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=osu1417024616.
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Guo, Tingyan. "On-line identification of power system dynamic signature using PMU measurements and data mining." Thesis, University of Manchester, 2015. https://www.research.manchester.ac.uk/portal/en/theses/online-identification-of-power-system-dynamic-signature-using-pmu-measurements-and-data-mining(989938d4-c236-48a7-a653-17326937f5b4).html.
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This thesis develops a robust methodology for on-line identification of power system dynamic signature based on incoming system responses from Phasor Measurement Units (PMUs) in Wide Area Measurement Systems (WAMS). Data mining techniques are used in the methodology to convert real-time monitoring data into transient stability information and the pattern of system dynamic behaviour in the event of instability. The future power system may operate closer to its stability limit in order to improve its efficiency and economic value. The changing types and patterns of load and generation are resulting in highly variable operating conditions. Corrective control and stabilisation is becoming a potentially viable option to enable safer system operation. In the meantime, the number of WAMS projects and PMUs is rising, which will significantly improve the system situational awareness. The combination of all these factors means that it is of vital importance to exploit a new and efficient Transient Stability Assessment (TSA) tool in order to use real-time PMU data to support decisions for corrective control actions. Data mining has been studied as the innovative solution and considered as promising. This work contributes to a number of areas of power systems stability research, specifically around the data driven approach for real-time emergency mode TSA. A review of past research on on-line TSA using PMU measurements and data mining is completed, from which the Decision Tree (DT) method is found to be the most suitable. This method is implemented on the test network. A DT model is trained and the sensitivity of its prediction accuracy is assessed according to a list of network uncertainties. Results showed that DT is a useful tool for on-line TSA for corrective control approach. Following the implementation, a generic probabilistic framework for the assessment of the prediction accuracy of data mining models is developed. This framework is independent of the data mining technique. It performs an exhaustive search of possible contingencies in the testing process and weighs the accuracies according to the realistic probability distribution of uncertain system factors, and provides the system operators with the confidence level of the decisions made under emergency conditions. After that, since the TSA for corrective control usually focuses on transient stability status without dealing with the generator grouping in the event of instability, a two-stage methodology is proposed to address this gap and to identify power system dynamic signature. In this methodology, traditional binary classification is used to identify transient stability in the first stage; Hierarchical Clustering is used to pre-define patterns of unstable dynamic behaviour; and different multiclass classification techniques are investigated to identify the patterns in the second stage. Finally, the effects of practical issues related to WAMS on the data mining methodologies are investigated. Five categories of issues are discussed, including measurement error, communication noise, wide area signal delays, missing measurements, and a limited number of PMUs.
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Vu, Ky Minh. "System identification, control algorithms and control interval for the Box-Jenkins dynamic model structure." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1997. http://www.collectionscanada.ca/obj/s4/f2/dsk3/ftp04/nq25181.pdf.
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Hernandez, Moreno Andres Felipe. "A metamodeling approach for approximation of multivariate, stochastic and dynamic simulations." Diss., Georgia Institute of Technology, 2012. http://hdl.handle.net/1853/43690.
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This thesis describes the implementation of metamodeling approaches as a solution to approximate multivariate, stochastic and dynamic simulations. In the area of statistics, metamodeling (or ``model of a model") refers to the scenario where an empirical model is build based on simulated data. In this thesis, this idea is exploited by using pre-recorded dynamic simulations as a source of simulated dynamic data. Based on this simulated dynamic data, an empirical model is trained to map the dynamic evolution of the system from the current discrete time step, to the next discrete time step. Therefore, it is possible to approximate the dynamics of the complex dynamic simulation, by iteratively applying the trained empirical model. The rationale in creating such approximate dynamic representation is that the empirical models / metamodels are much more affordable to compute than the original dynamic simulation, while having an acceptable prediction error.
The successful implementation of metamodeling approaches, as approximations of complex dynamic simulations, requires understanding of the propagation of error during the iterative process. Prediction errors made by the empirical model at earlier times of the iterative process propagate into future predictions of the model. The propagation of error means that the trained empirical model will deviate from the expensive dynamic simulation because of its own errors. Based on this idea, Gaussian process model is chosen as the metamodeling approach for the approximation of expensive dynamic simulations in this thesis. This empirical model was selected not only for its flexibility and error estimation properties, but also because it can illustrate relevant issues to be considered if other metamodeling approaches were used for this purpose.
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Sabbagh, Yvonne. "Maximum Likelihood Estimation of Hammerstein Models." Thesis, Linköping University, Department of Electrical Engineering, 2003. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-2061.
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In this Master's thesis, Maximum Likelihood-based parametric identification methods for discrete-time SISO Hammerstein models from perturbed observations on both input and output, are investigated.
Hammerstein models, consisting of a static nonlinear block followed by a dynamic linear one, are widely applied to modeling nonlinear dynamic systems, i.e., dynamic systems having nonlinearity at its input.
Two identification methods are proposed. The first one assumes a Hammerstein model where the input signal is noise-free and the output signal is perturbed with colored noise. The second assumes, however, white noises added to the input and output of the nonlinearity and to the output of the whole considered Hammerstein model. Both methods operate directly in the time domain and their properties are illustrated by a number of simulated examples. It should be observed that attention is focused on derivation, numerical calculation, and simulation corresponding to the first identification method mentioned above.
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Barnard, Jakobus Petrus. "Empirical state space modelling with application in online diagnosis of multivariate non-linear dynamic systems." Thesis, Stellenbosch : Stellenbosch University, 1999. http://hdl.handle.net/10019.1/51258.
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Dissertation (Ph.D)--University of Stellenbosch, 1999.ENGLISH ABSTRACT: System identification has been sufficiently formalized for linear systems, but not for empirical identification of non-linear, multivariate dynamic systems. Therefore this dissertation formalizes and extends non-linear empirical system identification for the broad class of nonlinear multivariate systems that can be parameterized as state space systems. The established, but rather ad hoc methods of time series embedding and nonlinear modeling, using multilayer perceptron network and radial basis function network model structures, are interpreted in context with the established linear system identification framework. First, the methodological framework was formulated for the identification of non-linear state space systems from one-dimensional time series using a surrogate data method. It was clearly demonstrated on an autocatalytic process in a continuously stirred tank reactor, that validation of dynamic models by one-step predictions is insufficient proof of model quality. In addition, the classification of data as either dynamic or random was performed, using the same surrogate data technique. The classification technique proved to be robust in the presence of up to at least 10% measurement and dynamic noise. Next, the formulation of a nearly real-time algorithm for detection and removal of radial outliers in multidimensional data was pursued. A convex hull technique was proposed and demonstrated on random data, as well as real test data recorded from an internal combustion engine. The results showed the convex hull technique to be effective at a computational cost two orders of magnitude lower than the more proficient Rocke and Woodruff technique, used as a benchmark, and incurred low cost (0.9%) in terms of falsely identifying outliers. Following the identification of systems from one-dimensional time series, the methodological framework was expanded to accommodate the identification of nonlinear state space systems from multivariate time series. System parameterization was accomplished by combining individual embeddings of each variable in the multivariate time series, and then separating this combined space into independent components, using independent component analysis. This method of parameterization was successfully applied in the simulation of the abovementioned autocatalytic process. In addition, the parameterization method was implemented in the one-step prediction of atmospheric N02 concentrations, which could become part of an environmental control system for Cape Town. Furthermore, the combination of the embedding strategy and separation by independent component analysis was able to isolate some of the noise components from the embedded data. Finally the foregoing system identification methodology was applied to the online diagnosis of temporal trends in critical system states. The methodology was supplemented by the formulation of a statistical likelihood criterion for simultaneous interpretation of multivariate system states. This technology was successfully applied to the diagnosis of the temporal deterioration of the piston rings in a compression ignition engine under test conditions. The diagnostic results indicated the beginning of significant piston ring wear, which was confirmed by physical inspection of the engine after conclusion of the test. The technology will be further developed and commercialized.
AFRIKAANSE OPSOMMING: Stelselidentifikasie is weI genoegsaam ten opsigte van lineere stelsels geformaliseer, maar nie ten opsigte van die identifikasie van nie-lineere, multiveranderlike stelsels nie. In hierdie tesis word nie-lineere, empiriese stelselidentifikasie gevolglik ten opsigte van die wye klas van nielineere, multiveranderlike stelsels, wat geparameteriseer kan word as toestandveranderlike stelsels, geformaliseer en uitgebrei. Die gevestigde, maar betreklik ad hoc metodes vir tydreeksontvouing en nie-lineere modellering (met behulp van multilaag-perseptron- en radiaalbasisfunksie-modelstrukture) word in konteks met die gevestigde line ere stelselidentifikasieraamwerk vertolk. Eerstens is die metodologiese raamwerk vir die identifikasie van nie-lineere, toestandsveranderlike stelsels uit eendimensionele tydreekse met behulp van In surrogaatdatametode geformuleer. Daar is duidelik by wyse van 'n outokatalitiese proses in 'n deurlopend geroerde tenkreaktor getoon dat die bevestiging van dinamiese modelle deur middel van enkelstapvoorspellings onvoldoende bewys van die kwaliteit van die modelle is. Bykomend is die klassifikasie van tydreekse as 6f dinamies Of willekeurig, met behulp van dieselfde surrogaattegniek gedoen. Die klassifikasietegniek het in die teenwoordigheid van tot minstens 10% meetgeraas en dinamiese geraas robuust vertoon. / Vervolgens is die formulering van In bykans intydse algoritme vir die opspoor en verwydering van radiale uitskieters in multiveranderlike data aangepak. 'n Konvekse hulstegniek is V:oorgestel en op ewekansige data, sowel as op werklike toetsdata wat van 'n binnebrandenjin opgeneem is, gedemonstreer. Volgens die resultate was die konvekse hulstegniek effektief teen 'n rekenkoste twee grootte-ordes kleiner as die meer vermoende Rocke en Woodrufftegniek, wat as meetstandaard beskou is. Die konvekse hulstegniek het ook 'n lae loopkoste (0.9%) betreffende die valse identifisering van uitskieters behaal. Na aanleiding van die identifisering van stelsels uit eendimensionele tydreekse, is die metodologiese raamwerk uitgebiei om die identifikasie van nie-lineere, toestandsveranderlike stelsels uit multiveranderlike data te omvat. Stelselparameterisering is bereik deur individuele ontvouings van elke veranderlike in die multidimensionele tydreeks met die skeiding van die gesamenlike ontvouingsruimte tot onafhanklike komponente saam te span. Sodanige skeiding is deur middel van onafhanklike komponentanalise behaal. Hierdie metode van parameterisering is suksesvc1 op die simulering van bogenoemde outokatalitiese proses toegepas. Die parameteriseringsmetode is bykomend in die enkelstapvoorspelling van atmosferiese N02-konsentrasies ingespan en sal moontlik deel van 'n voorgestelde omgewingsbestuurstelsel vir Kaapstad uitmaak. Die kombinasie van die ontvouingstrategie en skeiding deur onafhanklike komponentanalise was verder ook in staat om van die geraaskomponente in die data uit te lig. Ten slotte is die voorafgaande tegnologie vir stelselidentifikasie op die lopende diagnose van tydsgebonde neigings in kritiese stelseltoestande toegepas. Die metodologie is met die formulering van 'n statistiese waarskynlikheidsmaatstaf vir die gelyktydige vertolking van multiveranderlike stelseltoestande aangevul. Hierdie tegnologie is suksesvol op die diagnose van die tydsgebonde verswakking van die suierringe in 'n kompressieontstekingenj in tydens toetstoestande toegepas. Die diagnostiese resultate het die aanvang van beduidende slytasie in die suierringe aangedui, wat later tydens fisiese inspeksie van die enjin met afloop van die toets, bevestig is. Die tegnologie sal verder ontwikkel en markgereed gemaak word.
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McEwen, Matthew D. "Dynamic system identification and modeling of a rotary wing UAV for stability and control analysis." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 1998. http://handle.dtic.mil/100.2/ADA349878.
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Ramos, Pablo D. Jr. "SYSTEM IDENTIFICATION OF A BRIDGE-TYPE BUILDING STRUCTURE." DigitalCommons@CalPoly, 2013. https://digitalcommons.calpoly.edu/theses/944.
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The Bridge House is a steel building structure located in Poly Canyon, a rural area inside the campus of California Polytechnic State University, San Luis Obispo. The Bridge House is a one story steel structure supported on 4 concrete piers with a lateral force resisting system (LFRS) composed of ordinary moment frames in the N-S direction and braced frames in the E-W direction and vertically supported by a pair of trusses. The dynamic response of the Bridge House was investigated by means of system identification through ambient and forced vibration testing. Interesting findings such as diaphragm flexibility, foundation flexibility and frequency shifts due to thermal effects were all found throughout the mode shape mapping process. Nine apparent mode shapes were experimentally identified, N-S and E-W translational, rotational and 6 vertical modes. A computational model was also created and refined through correlation with the modal parameters obtained through FVTs. When compared to the experimental results, the computational model estimated the experimentally determined building period within 8% and 10% for both N-S and E-W translational modes and within 10% for 4 of the vertical modes.
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Hatzenbuehler, Mark A. "Modeling of jet vane heat-transfer characteristics and simulation of thermal response." Thesis, Monterey, California. Naval Postgraduate School, 1988. http://hdl.handle.net/10945/23314.
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Approved for public release; distribution is unlimitedThe development of a dynamic computational model capable of predicting, with the requisite design certainty, the transient thermal response of jet vane thrust control systems has been undertaken. The modeling and simulation procedures utilized are based on the concept that the thermal processes associated with jet vane operation can be put into a transfer function form commonly found in the discipline of automatic controls. Well established system identification methods are employed to formulate and verify the relationships between the various gains and frequencies of the transfer function model and experimental data provided by Naval Weapons Center, China Lake.
http://archive.org/details/modelingofjetvan00hatz
Lieutenant, United States Navy
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Tutturen, Svenn Are. "Topics in dynamic positioning : System identification, GNSS and MRU lever arm estimation, and hybrid integral action." Thesis, Norges teknisk-naturvitenskapelige universitet, Institutt for marin teknikk, 2014. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-27252.
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This thesis consists of three main parts. The first part of the master thesis looks at the identification of thruster dynamics and low speed ship dynamics. The relevant parameters identified are time constants and time delays in the system. Simple step tests are used for the identification. Different models for identification are suggested, both for uncoupled surge, sway, and yaw dynamics. Other test results, such as agility plots, DP 4 corner tests, and pure DP tests (stationkeeping) are reported. All the results are to be compared to similar tests performed after R/V Gunnerus has a retrofit of the thruster system.The second part discusses another problem, and that is the topic of numerically estimat- ing the body frame position of the GNSS and MRU sensors. For the GNSS position an Luenberger observer design and an adaptive scheme are proposed and analyzed. The es- timation designs are tested using numerical simulations and experimental data from the Gunnerus sea trials. A similar Luenberger observer is proposed for the MRU positions, and experimental data from the sea trials are used to test the observer.The third part discusses a hybrid augmentation of integral action. The motivation is a DP system, where typically the integral action is tuned very low to avoid oscillations due to the integral action. When there is a sudden load change, such as a ice load that hits the vessel, or if a mooring wire snaps, then a hybrid update augmentation could be useful, to speed up the convergence of the integral action. The update law is a linear update law based on the error in the states (the velocity for the DP system). The augmentation can significantly improve performance, especially for very large disturbance changes.
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Jiang, Xiaomo. "Dynamic fuzzy wavelet neural network for system identification, damage detection and active control of highrise buildings." Connect to this title online, 2005. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1110266591.
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Thesis (Ph. D.)--Ohio State University, 2005.Title from first page of PDF file. Document formatted into pages; contains xvii, 221 p.; also includes graphics (some col.). Includes bibliographical references (p. 210-221). Available online via OhioLINK's ETD Center
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Schön, Thomas B. "Estimation of Nonlinear Dynamic Systems : Theory and Applications." Doctoral thesis, Linköpings universitet, Reglerteknik, 2006. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-7124.
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This thesis deals with estimation of states and parameters in nonlinear and non-Gaussian dynamic systems. Sequential Monte Carlo methods are mainly used to this end. These methods rely on models of the underlying system, motivating some developments of the model concept. One of the main reasons for the interest in nonlinear estimation is that problems of this kind arise naturally in many important applications. Several applications of nonlinear estimation are studied. The models most commonly used for estimation are based on stochastic difference equations, referred to as state-space models. This thesis is mainly concerned with models of this kind. However, there will be a brief digression from this, in the treatment of the mathematically more intricate differential-algebraic equations. Here, the purpose is to write these equations in a form suitable for statistical signal processing. The nonlinear state estimation problem is addressed using sequential Monte Carlo methods, commonly referred to as particle methods. When there is a linear sub-structure inherent in the underlying model, this can be exploited by the powerful combination of the particle filter and the Kalman filter, presented by the marginalized particle filter. This algorithm is also known as the Rao-Blackwellized particle filter and it is thoroughly derived and explained in conjunction with a rather general class of mixed linear/nonlinear state-space models. Models of this type are often used in studying positioning and target tracking applications. This is illustrated using several examples from the automotive and the aircraft industry. Furthermore, the computational complexity of the marginalized particle filter is analyzed. The parameter estimation problem is addressed for a relatively general class of mixed linear/nonlinear state-space models. The expectation maximization algorithm is used to calculate parameter estimates from batch data. In devising this algorithm, the need to solve a nonlinear smoothing problem arises, which is handled using a particle smoother. The use of the marginalized particle filter for recursive parameterestimation is also investigated. The applications considered are the camera positioning problem arising from augmented reality and sensor fusion problems originating from automotive active safety systems. The use of vision measurements in the estimation problem is central to both applications. In augmented reality, the estimates of the camera’s position and orientation are imperative in the process of overlaying computer generated objects onto the live video stream. The objective in the sensor fusion problems arising in automotive safety systems is to provide information about the host vehicle and its surroundings, such as the position of other vehicles and the road geometry. Information of this kind is crucial for many systems, such as adaptive cruise control, collision avoidance and lane guidance.
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Boggs, Christopher Matthew. "The Use of Simulation to Expedite Experimental Investigations of the Effect of High-Performance Shock Absorbers." Diss., Virginia Tech, 2009. http://hdl.handle.net/10919/26108.
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Successful race teams rely heavily on track testing to search for the ideal suspension setup. As more restrictions are placed on the amount of on-track testing by major racing sanctioning bodies, such as NASCAR, teams have increased their attention to alternate testing methods to augment their track data and better understand the dynamics of their racecars. One popular alternate to track testing is 8-post dynamic shaker rig testing. Eight-post rig testing gives the team a better understanding of the vehicle's dynamics before they arrive at the race track, allowing them to use their limited track testing time more efficiently.
While 8-post rig testing certainly is an attractive option, an extensive test matrix is often required to find the best suspension setups. To take full advantage of 8-post rig tests, more efficient experimental methods are needed. Since investigating shock absorber selection is often the most time-consuming task, this study focuses on developing more efficient methods to select the best shock absorber setups.
This study develops a novel method that applies dynamic substructuring and system identification to generate a mathematical model that predicts the results of future tests as both command inputs and components are changed. This method is used to predict the results of 8-post rig tests as actuator commands and shock absorber forces are varied. The resulting model can then be coupled with shock absorber models to simulate how the vehicle response changes with shock absorber selection. This model can then be applied to experimental design.
First, a physically-motivated nonlinear dynamic shock absorber model is developed, suitable for quickly fitting experimental data and implementing in simulation studies. Next, a system identification method to identify a vehicle model using experimental data is developed. The vehicle model is then used to predict response trends as shock absorber selection is varied. Comparison of simulation and experimental results show that this model can be used to predict the response levels for 8-post rig tests and aid in streamlining 8-post rig testing experimental designs.Ph. D.
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Souflas, Ioannis. "Qualitative Adaptive Identification for Powertrain Systems. Powertrain Dynamic Modelling and Adaptive Identification Algorithms with Identifiability Analysis for Real-Time Monitoring and Detectability Assessment of Physical and Semi-Physical System Parameters." Thesis, University of Bradford, 2015. http://hdl.handle.net/10454/14427.
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A complete chain of analysis and synthesis system identification tools for detectability assessment and adaptive identification of parameters with physical interpretation that can be found commonly in control-oriented powertrain models is presented. This research is motivated from the fact that future powertrain control and monitoring systems will depend increasingly on physically oriented system models to reduce the complexity of existing control strategies and open the road to new environmentally friendly technologies. At the outset of this study a physics-based control-oriented dynamic model of a complete transient engine testing facility, consisting of a single cylinder engine, an alternating current dynamometer and a coupling shaft unit, is developed to investigate the functional relationships of the inputs, outputs and parameters of the system. Having understood these, algorithms for identifiability analysis and adaptive identification of parameters with physical interpretation are proposed. The efficacy of the recommended algorithms is illustrated with three novel practical applications. These are, the development of an on-line health monitoring system for engine dynamometer coupling shafts based on recursive estimation of shaft’s physical parameters, the sensitivity analysis and adaptive identification of engine friction parameters, and the non-linear recursive parameter estimation with parameter estimability analysis of physical and semi-physical cyclic engine torque model parameters. The findings of this research suggest that the combination of physics-based control oriented models with adaptive identification algorithms can lead to the development of component-based diagnosis and control strategies. Ultimately, this work contributes in the area of on-line fault diagnosis, fault tolerant and adaptive control for vehicular systems.
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Aljuri, A. Nikolai (Antony Nikolai) 1968. "System identification of dynamic closed-loop cardiovascular control of total peripheral resistance by arterial and cardiopulmonary baroreceptors." Thesis, Massachusetts Institute of Technology, 2002. http://hdl.handle.net/1721.1/29900.
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Thesis (Ph.D.)--Harvard--Massachusetts Institute of Technology Division of Health Sciences and Technology, 2002.Vita.
Includes bibliographical references (leaves 72-76).
Prolonged exposure to microgravity in space flight missions (days) impairs the mechanisms responsible for defense of cardiac output (CO) and arterial blood pressure (Pa) against orthostatic stress during re-entry and in the post-flight period. To date, available countermeasures have not been able to eliminate the observed orthostatic hypotension. The mechanisms responsible for the observed orthostatic intolerance are not yet completely understood. Pa is maintained by control pathways, which influence either total peripheral resistance (Ra) or CO. Central control of Ra is achieved by a complex closed-loop negative feedback system composed of the arterial and the cardiopulmonary baroreflexes. The aims of the doctoral research presented in this thesis were: 1) design and employ a novel conscious animal model for the examination of arterial and cardiopulmonary baroreceptors in the dynamic closed-loop short-term control of Ra. 2) develop and apply a system identification method for the analysis of fluctuations in Pa, right atrial pressure (Pra), and Ra to quantitatively characterize the physiologic mechanisms responsible for the couplings between these variables. For this purpose, eight conscious sheep were used, where both types of baroreceptors were simultaneously exposed to random independent beat pressure variations over a small range around their operating points, while Ra was measured. Subsequently, system identification was applied to determine the quantitative dynamic contributions of Pa and Pra to short-term closed-loop regulation of Ra. To validate the dynamic properties of the transfer function estimates from the developed system identification method, step response estimates from Pa to Ra and from Pra to Ra were compared to directly measured step response observations.
by A. Nikolai Aljuri.
Ph.D.
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Inga, Charaja Juan Jairo [Verfasser], and S. [Akademischer Betreuer] Hohmann. "Inverse Dynamic Game Methods for Identification of Cooperative System Behavior / Juan Jairo Inga Charaja ; Betreuer: S. Hohmann." Karlsruhe : KIT-Bibliothek, 2020. http://d-nb.info/1221186906/34.
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Inga, Charaja Juan Jairo [Verfasser], and S. [Akademischer Betreuer] Hohmann. "Inverse Dynamic Game Methods for Identification of Cooperative System Behavior / Juan Jairo Inga Charaja ; Betreuer: S. Hohmann." Karlsruhe : KIT-Bibliothek, 2021. http://d-nb.info/1234063751/34.
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Carter, Matthew Edward. "Setting location priors using beamforming improves model comparison in MEG-DCM." Thesis, Virginia Tech, 2014. http://hdl.handle.net/10919/50418.
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Modelling neuronal interactions using a directed network can be used to provide insight into
the activity of the brain during experimental tasks. Magnetoencephalography (MEG) allows
for the observation of the fast neuronal dynamics necessary to characterize the activity of
sources and their interactions. A network representation of these sources and their con-
nections can be formed by mapping them to nodes and their connection strengths to edge
weights. Dynamic Causal Modelling (DCM) presents a Bayesian framework to estimate the
parameters of these networks, as well as the ability to test hypotheses on the structure of
the network itself using Bayesian model comparison. DCM uses a neurologically-informed
representation of the active neural sources, which leads to an underdetermined system and
increased complexity in estimating the network parameters. This work shows that inform-
ing the MEG DCM source location with prior distributions defined using a MEG source
localization algorithm improves model selection accuracy. DCM inversion of a group of can-
didate models shows an enhanced ability to identify a ground-truth network structure when
source-localized prior means are used.Master of Science
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Wiese, Johannes Jacobus. "System identification and model-based control of a filter cake drying process." Thesis, Stellenbosch : University of Stellenbosch, 2011. http://hdl.handle.net/10019.1/6654.
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Thesis (MScEng (Process Engineering))--University of Stellenbosch, 2011.ENGLISH ABSTRACT: A mineral concentrate drying process consisting of a hot gas generator, a flash dryer and a feeding section is found to be the bottleneck in the platinum concentrate smelting process. This operation is used as a case study for system identification and model-based control of dryers. Based on the availability of a month's worth of dryer data obtained from a historian, a third party modelling and control software vendor is interested in the use of this data for data driven model construction and options for dryer control. The aimed contribution of this research is to use only data driven techniques and attempt an SID experiment and use of this model in a controller found in literature to be applicable to the dryer process. No first principle model was available for simulation or interpretation of results. Data were obtained for the operation from the plant historian, reduced, cleaned and investigated for deterministic information through surrogate data comparison – resulting in usable timeseries from the plant data. The best datasets were used for modelling of the flash dryer and hot gas generator operations individually, with the hot gas generator providing usable results. The dynamic, nonlinear autoregressive models with exogenous inputs were identified by means of a genetic programming with orthogonal least squares toolbox. The timeseries were reconstructed as a latent variable set, or “pseudo-embedding”, using the delay parameters as identified by average mutual information, autocorrelation and false nearest neighbours. The latent variable reconstruction resulted in a large solution space, which need to be investigated for an unknown model structure. Genetic Programming is capable of identifying unknown structures. Freerun prediction stability and sensitivity analysis were used to assess the identified best models for use in model based control. The best two models for the hot gas generator were used in a basic model predictive controller in an attempt to only track set point changes. One step ahead modelling of the flash dryer outlet air temperature was unsuccessful with the best model obtaining a validation R2 = 43%. The lack of process information contained in the available process variables are to blame for the poor model identification. One-step ahead prediction of the hot gas generator resulted in a top model with validation R2 = 77.1%. The best two hot gas generator models were implemented in a model predictive controller constructed in a real time plant data flow simulation. This controller's performance was measured against set point tracking ability. The MPC implementation was unsuccessful due to the poor freerun prediction ability of the models. The controller was found to be unable to optimise the control moves using the model. This is assigned to poor model freerun prediction ability in one of the models and a too complex freerun model structure required. It is expected that the number of degrees of freedom in the freerun model is too much for the optimiser to handle. A successful real time simulation architecture for the plant dataflow could however be constructed in the supplied software. It is recommended that further process measurements, specifically feed moisture content, feed temperature and air humidity, be included for the flash dryer; closed loop system identification be investigated for the hot gas generator; and a simpler model structure with smaller reconstructed latent variable regressor set be used for the model predictive controller.
AFRIKAANSE OPSOMMING: 'n Drogings proses vir mineraal konsentraat bestaan uit drie eenhede: 'n lug verwarmer-, 'n blitsdroeër- en konsentraat toevoer eenheid. Hierdie droeër is geïdentifiseer as die bottelnek in die platinum konsentraat smeltingsproses. Die droeër word gebruik as 'n gevallestudie vir sisteem identifikasie asook model-gebasseerder beheer van droeërs. 'n Maand se data verkry vanaf die proses databasis, het gelei tot 'n derde party industriële sagteware en beheerstelsel maatskappy se belangstelling in data gedrewe modelering en beheer opsies vir die drogings proses. Die doelwit van hierdie studie is om data gedrewe modeleringstegnieke te gebruik en die model in 'n droeër-literatuur relevante beheerder te gebruik. Geen eerste beginsel model is beskikbaar vir simulasie of interpretasie van resultate nie. Die verkrygde data is gereduseer, skoon gemaak en bestudeer om te identifiseer of die tydreeks deterministiese inligting bevat. Dit is gedoen deur die tydreeks met stochastiese surrogaat data te vergelyk. Die mees gepaste datastelle is gebruik vir modellering van die blitsdroeër en lugverwarmer afsonderlik. Die nie-liniêre, dinamiese nie-linieêre outeregressie modelle met eksogene insette was deur 'n genetiese programmering algoritme, met ortogonale minimum kwadrate, identifiseer. Die betrokke tydreeks is omskep in 'n hulp-veranderlike stel deur gebruik te maak van vertragings-parameters wat deur gemiddelde gemeenskaplike inligting, outokorrelasie en vals naaste buurman metodes verkry is. Die GP algoritme is daartoe in staat om the groot oplossings ruimte wat deur hierdie hulp-veranderlike rekonstruksie geskep word, te bestudeer vir 'n onbekende model struktuur. Die vrye vooruitskattings vermoë, asook die model sensitiwiteit is inag geneem tydens die analiese van die resultate. Die beste modelle se gepastheid tot model voorspellende beheer is gemeet deur die uitkomste van 'n sensitiwiteits analise, asook 'n vrylopende voorspelling, in oënskou te neem. Die een-stap vooruit voorspellende model van die droeër was onsusksesvol met die beste model wat slegs 'n validasie R2 = 43% kon behaal. Die gebrekkige meet instrumente in die droeër is te blameer vir die swak resultate. Die een-stap vooruit voorspellende model van die lug verwarmer wat die beste gevaar het, het 'n validasie R2 = 77.1% gehad. 'n Basiese model voorspellende beheerder is gebou deur die 2 beste modelle van slegs die lugverwarmer te gebruik in 'n intydse simulasie van die raffinadery data vloei struktuur. Hierdie beheerder se vermoë om toepaslike beheer uit te oefen, is gemeet deur die slegs die stelpunt te verander. Die beheerder was egter nie daartoe in staat om die insette te optimeer, en so die stelpunt te volg nie. Hierdie onvermoë is as gevolg van die kompleks vrylopende model struktuur wat oor die voorspellingsvenster optimeer moet word, asook die onstabiele vryvooruitspellings vermoë van die modelle. Die vermoede is dat die loslopende voorspelling te veel vryheids grade het om die insette maklik genoeg te optimeer. Die intydse simulasie van die raffinadery se datavloei struktuur was egter suksesvol. Beter meting van noodsaaklike veranderlikes vir die droër, o.a. voginhoud van die voer, voer temperatuur, asook lug humiditeit; geslotelus sisteem identifikasie vir die lugverwarmer; asook meer eenvoudige model struktuur vir gebruik in voorspellende beheer moontlik vermag deur 'n kleiner hulp veranderlike rekonstruksie te gebruik.
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Noxon, Nikola John Linn. "A MODEL PREDICTIVE CONTROL APPROACH TO ROLL STABILITY OF A SCALED CRASH AVOIDANCE VEHICLE." DigitalCommons@CalPoly, 2012. https://digitalcommons.calpoly.edu/theses/783.
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In this paper, a roll stability controller (RSC) is presented based on an eight degree of freedom dynamic vehicle model. The controller is designed for and tested on a scaled vehicle performing obstacle avoidance maneuvers on a populated test track. A rapidly-exploring random tree (RRT) algorithm is used for the vehicle to execute a trajectory around an obstacle, and examines the geographic, non-homonymic, and dynamic constraints to maneuver around the obstacle. A model predictive controller (MPC) uses information about the vehicle state and, based on a weighted performance measure, generates an optimal trajectory around the obstacle. The RSC uses the standard vehicle state sensors: four wheel mounted encoders, a steering angle sensor, and a six degree of freedom inertial measurement unit (IMU). An emphasis is placed on the mitigation of rollover and spin-out, however if a safe maneuver is not found and a collision is inevitable, the program will run a brake command to reduce the vehicle speed before impact. The trajectory is updated at a rate of 20 Hz, providing improved stability and maneuverability for speeds up to 10 ft/s and turn angles of up to 20°.
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Das, Ajoy Kumar. "Health Assessment of Three Dimensional Large Structural Systems Using Limited Uncertain Dynamic Response Information." Diss., The University of Arizona, 2012. http://hdl.handle.net/10150/268597.
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A novel system identification (SI)-based structural health assessment (SHA) procedure has been developed integrating several theoretical and implementation aspects. The procedure assesses health of structures using limited noise-contaminated dynamic responses and without using input excitation information. Since most practical structures are three dimensional (3D), the procedure has been developed for general 3D structures, represented by finite elements (FEs). The procedure identifies defects by tracking the changes in the stiffness of the elements in the FE representation. Once a defective element is identified, defect spot can be identified accurately within the defective element. The procedure is denoted as 3D Generalized Iterative Least-Squares Extended Kalman Filter with Unknown Input (3D GILS-EKF-UI) and implemented in two stages. In Stage 1, based on the available responses, substructure(s) are selected and the 3D GILS-UI procedure is used to generate the unknown input excitation, stiffness parameters of the elements in the substructure, and two Rayleigh damping coefficients. Using information from Stage 1, stiffness parameters for the whole structure are identified using EKF with Weighted Global Iteration (EKF-WGI) in Stage 2. The procedure accurately identified defect-free and defective states of various 3D structures using only analytically generated limited responses. To increase the robustness, 3D GILS-EKF-UI has been extended to develop an integrated structural health assessment strategy, denoted as Iterative Least-Squares Extended Kalman Filter with Unknown Input and Advanced Digital Integration Technique (ILS-EKF-UI-ADIT). The procedure has been implemented in three stages. In Stage 1, an advanced digital integration technique (ADIT) is implemented for post-processing of noise-contaminated acceleration time-histories, addressing all major challenges of digital integration. It also overcomes non-convergence issue in Stage 2 that arises due to phase-shift and amplitude errors. In Stage 2, substructure(s) are identified using the least-squares procedure. In Stage 3, stiffness parameters for the whole structure are identified using the EKF-WGI procedure. ILS-EKF-UI-ADIT has been verified in presence of relatively large noise in the acceleration time-histories, measured at small part(s) of defect-free and defective structures, without using excitation information. The SHA procedure is robust and has the potential to be applied for the health assessment, maintenance, retrofitting, and life extension of existing structural systems.
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Jain, Sulabh. "Event-Driven Dynamic Query Model for Sleep Study Outcomes Research." Case Western Reserve University School of Graduate Studies / OhioLINK, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=case1323377417.
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Boberg, Frida. "Simulation of dynamic and static behavior of an electrically powered lift gate." Thesis, Linköping University, Department of Electrical Engineering, 2008. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-11627.
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Continental Automotive Systems is a German company that develops control systems for different applications in cars. A control system for electrically powered lift gates that are opened or closed on the driver’s command is one of the products developed. The drive system itself is composed of a spindle that is driven by a DC-motor over a gear and a spring. When developing the control system it is convenient to use a simulation model instead of having to implement it on the system every time. The simulation analytically describes how the system is behaving.
In this thesis a simulation model of a drive system and a lift gate is developed and evaluated. The model parameters are estimated using System Identification Toolbox in Matlab.
Continental Automotive Systems är ett tyskt företag som utvecklar styrsystem för olika tillämpningar i bilar. Bland annat utvecklas ett styrsystem till eldrivna bakluckor som öppnas och stängs av föraren per knapptryck. Själva drivanordningen består av en skruv som drivs av en likströmsmotor över en utväxling och en fjäder. Då man vill utveckla styrsystemet utan att behöva implementera det på systemet varje gång är en simuleringsmodell av drivanordningen och luckan ett bra hjälpmedel. Denna simuleringsmodell kan då analytiskt beräkna hur systemet uppför sig.
I detta examensarbete har en simuleringsmodell av en drivanordning med tillhörande lucka utvecklats och utvärderats. Modellparametrarna estimerades med hjälp av System Identification Toolbox i Matlab.
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Samal, Mahendra Engineering & Information Technology Australian Defence Force Academy UNSW. "Neural network based identification and control of an unmanned helicopter." Awarded by:University of New South Wales - Australian Defence Force Academy. Engineering & Information Technology, 2009. http://handle.unsw.edu.au/1959.4/43917.
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This research work provides the development of an Adaptive Flight Control System (AFCS) for autonomous hover of a Rotary-wing Unmanned Aerial Vehicle (RUAV). Due to the complex, nonlinear and time-varying dynamics of the RUAV, indirect adaptive control using the Model Predictive Control (MPC) is utilised. The performance of the MPC mainly depends on the model of the RUAV used for predicting the future behaviour. Due to the complexities associated with the RUAV dynamics, a neural network based black box identification technique is used for modelling the behaviour of the RUAV. Auto-regressive neural network architecture is developed for offline and online modelling purposes. A hybrid modelling technique that exploits the advantages of both the offline and the online models is proposed. In the hybrid modelling technique, the predictions from the offline trained model are corrected by using the error predictions from the online model at every sample time. To reduce the computational time for training the neural networks, a principal component analysis based algorithm that reduces the dimension of the input training data is also proposed. This approach is shown to reduce the computational time significantly. These identification techniques are validated in numerical simulations before flight testing in the Eagle and RMAX helicopter platforms. Using the successfully validated models of the RUAVs, Neural Network based Model Predictive Controller (NN-MPC) is developed taking into account the non-linearity of the RUAVs and constraints into consideration. The parameters of the MPC are chosen to satisfy the performance requirements imposed on the flight controller. The optimisation problem is solved numerically using nonlinear optimisation techniques. The performance of the controller is extensively validated using numerical simulation models before flight testing. The effects of actuator and sensor delays and noises along with the wind gusts are taken into account during these numerical simulations. In addition, the robustness of the controller is validated numerically for possible parameter variations. The numerical simulation results are compared with a base-line PID controller. Finally, the NN-MPCs are flight tested for height control and autonomous hover. For these, SISO as well as multiple SISO controllers are used. The flight tests are conducted in varying weather conditions to validate the utility of the control technique. The NN-MPC in conjunction with the proposed hybrid modelling technique is shown to handle additional disturbances successfully. Extensive flight test results provide justification for the use of the NN-MPC technique as a reliable technique for control of non-linear complex dynamic systems such as RUAVs.
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Pant, Gaurav. "Hybrid Dynamic Modelling of Engine Emissions on Multi-Physics Simulation Platform. A Framework Combining Dynamic and Statistical Modelling to Develop Surrogate Models of System of Internal Combustion Engine for Emission Modelling." Thesis, University of Bradford, 2018. http://hdl.handle.net/10454/17223.
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