63 research outputs found
Adaptive Input Reconstruction with Application to Model Refinement, State Estimation, and Adaptive Control.
Input reconstruction is the process of using the output of a system to estimate its input. In some cases, input reconstruction can be accomplished by determining the output of the inverse of a model of the system whose input is the output of the original system. Inversion, however, requires an exact and fully known analytical model, and is limited by instabilities arising from nonminimum-phase zeros.
The main contribution of this work is a novel technique for input reconstruction that does not require model inversion. This technique is based on a retrospective cost, which requires a limited number of Markov parameters. Retrospective cost input reconstruction (RCIR) does not require knowledge of nonminimum-phase zero locations or an analytical model of the system.
RCIR provides a technique that can be used for model refinement, state estimation, and adaptive control. In the model refinement application, data are used to refine or improve a model of a system. It is assumed that the difference between the model output and the data is due to an unmodeled subsystem whose interconnection with the modeled system is inaccessible, that is, the interconnection signals cannot be measured and thus standard system identification techniques cannot be used. Using input reconstruction, these inaccessible signals can be estimated, and the inaccessible subsystem can be fitted. We demonstrate input reconstruction in a model refinement framework by identifying unknown physics in a space weather model and by estimating an unknown film growth in a lithium ion battery. The same technique can be used to obtain estimates of states that cannot be directly measured.
Adaptive control can be formulated as a model-refinement problem, where the unknown subsystem is the idealized controller that minimizes a measured performance variable. Minimal modeling input reconstruction for adaptive control is useful for applications where modeling information may be difficult to obtain. We demonstrate adaptive control of a seeker-guided missile with unknown aerodynamics.Ph.D.Aerospace EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/91520/1/amdamato_1.pd
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Design of a Multiloop Pyroelectric Neutron Generator Control System
Pyroelectric neutron generators are compact, low power systems which may be capable of producing short intense pulses of neutrons from D-D fusion reactions. Initial analysis of pyrofusion dynamics has indicated the potential to manipulate the pulse characteristics through system control. This thesis presents the development of novel pyroelectric neutron
generator dynamics models in MATLAB/Simulink that can be used to support the predictability and control of the neutron pulse.
Plant models have been developed using two control system modelling approaches: lumped-parameter and system identification modelling. Describing equations for the pyroelectric subsystem components are detailed and implemented using lumped-parameter modelling. Novel work towards the analysis of the pyroelectric subsystem responses, stability
and performance using control system techniques is presented. Frequency-domain studies, stability analysis and time-domain simulations are reported. The dynamic characteristics of pyroelectric neutron generators have indicated that they could be effective neutron sources for nuclear reactor plants. The development of a prototype
pyroelectric neutron source for the purpose of system identification is reported. Plans to progress the work are discussed, including validation against data collected through experiments at an actual zero-power reactor. The key research areas are: pyroelectric neutron generation; thermoelectric cooler modelling; control system modelling; and controller design
Identification & control of nonlinear systems
This thesis investigates some problems on nonlinear system identification, parameter estimation, and signal processing.
Random signal spectral analysis and system frequency response estimation are studied from incomplete time series. Both recursive and direct estimators are presented based on either an unbiased or minimum mean square error criterion.
Nonlinear system identification and parameter estimation are studied. A quantisation technique is developed to give a clear geometrical interpretation for structure detection and parameter estimation. A new concept, state amplitude distance between current and previous operating states, is introduced, and results in a
Variable Weighted Least Squares (VWLS) algorithm. A modified version makes on-line application possible. Jump resonance is predicted by the VWLS algorithm as one of the applications.
Self-tuning controllers, including a nonlinear general predictive controller and a nonlinear deadbeat controller, are designed. A vector backward shift operator is defined to simplify the expression of the Hammerstein model, and is introduced to analyse the general feedback controller design problem for nonlinear plant described by the Hammerstein model. A fast root-solver developed facilitates nonlinear model treatment in on-line applications.
Theoretical results are confirmed by simulation studies
System Engineering Applied to Fuenmayor Karst Aquifer (San Julián de Banzo, Huesca) and Collins Glacier (King George Island, Antarctica)
La ingenierÃa de sistemas, definida generalmente como arte y ciencia de crear soluciones integrales a problemas complejos, se aplica en el presente documento a dos sistemas naturales, a saber, un sistema acuÃfero kárstico y un sistema glaciar, desde una perspectiva hidrológica. Las técnicas de identificación, desarrolladas tÃpicamente en ingenierÃa para representar sistemas artificiales por medio de modelos lineales y no lineales, pueden aplicarse en el estudio de los sistemas naturales donde se producen fenómenos de acoplamiento entre el clima y la hidrosfera. Los métodos evolucionan para afrontar nuevos campos de identificación donde se requieren estrategias para encontrar el modelo idóneo adaptado a las peculiaridades del sistema. En este sentido, se han considerado especialmente las herramientas basadas en la transformada wavelet utilizadas en la preparación de series temporales, suavizado de señales, análisis espectral, correlación cruzada y predicción, entre otros. Bajo este enfoque, una aplicación a mencionar entre las tratadas en esta tesis, es la determinación analÃtica del núcleo efectivo estacional (SEC) a través del estudio de la coherencia wavelet entre temperatura del aire y la descarga del glaciar, que establece un conjunto de perÃodos de muestreo aceptablemente coherentes, a partir del cual se crearán los modelos del sistema glacial. El estudio está dirigido especÃficamente a estimar la influencia de la precipitación sobre la descarga del acuÃfero kárstico de Fuenmayor, en San Julián de Banzo, Huesca, España. De la misma manera, se ocupa de las consecuencias de la temperatura del aire en la fusión del hielo glaciar, que se manifiesta en la corriente de drenaje del glaciar Collins, isla King George, Antártida. En el proceso de identificación paramétrica y no paramétrica se buscan los modelos que mejor representen la dinámica interna del sistema. Eso conduce a pruebas iterativas, donde se van creando modelos que se verifican sistemáticamente con los datos reales del muestreo, de acuerdo a un criterio de eficiencia dado. La solución mejor valorada según los resultados obtenidos en los casos tratados apuntan a estructuras de modelos en bloques. Esta tesis significa una exposición formal de la metodologÃa de identificación de sistemas propios de la ingenierÃa en el contexto de los sistemas naturales, que mejoran los resultados obtenidos en muchos casos de la hidrologÃa kárstica que comúnmente usaban métodos ad hoc ocasionales de carácter estadÃstico; asà mismo, los enfoques propuestos en los casos de glaciologÃa con el análisis wavelet y los modelos orientados a datos raramente considerados en la literatura, revelan información esencial ante la imposibilidad de precisar la totalidad de la fÃsica que rige el sistema. Notables resultados se derivan en la caracterización de la respuesta del manantial de Fuenmayor y su correlación con la precipitación, desde la perspectiva de un sistema lineal, que se complementa con los métodos de identificación basados en técnicas no lineales. Asà mismo, la implementación del modelo para el glaciar Collins, obtenido también mediante métodos de identificación de caja negra, puede revelar una inestabilidad de los lÃmites de los periodos activos de la descarga, y consecuentemente la variabilidad en la tendencia actual en el cambio climático global
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