Diseño de un observador robusto de blancos aéreos de alta maniobrabilidad basado en sistemas de estructura variable con modos deslizantes
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2022-02-10
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Pontificia Universidad Católica del Perú
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Esta tesis estudia los observadores de estados basados en sistemas de estructura variable con
modos deslizantes, como una solución alterna al algoritmo de modelo múltiple interactivo (IMM)
basado en filtros Kalman y filtro de partículas, para la estimación robusta de posición, velocidad
y aceleración de un blanco aéreo de alta maniobrabilidad, tales como misiles antibuque o aviones
de combate, a pesar de la existencia de incertidumbres o perturbaciones del modelo y utilizando
mediciones de posición o velocidad con ruido angular.
En el capítulo I se efectúa el estudio del estado del arte, se expone la problemática y la solución
actual a esta. Posteriormente, en el capítulo II se efectúa un estudio de los distintos modelos
dinámicos y de medición de blancos aéreos de alta maniobrabilidad existentes en la literatura,
proponiéndose al final del capítulo un modelo lineal incierto del blanco aéreo (misil antibuque) y
presentándose una simulación de la trayectoria completa de este.
En el capítulo III se expone la teoría de sistemas de estructura variable con modos deslizantes
aplicada a observadores de estado, se efectúa el diseño de los observadores más resaltantes y
se presentan simulaciones de las estimaciones de la trayectoria del blanco aéreo de alta
maniobrabilidad, comparándose al final del capítulo los resultados en base a criterios de
desempeño establecidos. Los resultados muestran que en la ausencia de ruido los observadores
“clásicos” de Edwards-Spurgeon (ESSMO), Walcott-Zak (WZSMO) y el diferenciador robusto
exacto adaptativo (ARED) obtienen los mejores desempeños. Asimismo, para hacer uso de los
observadores anteriormente mencionados en un ambiente de ruido angular se propone un nuevo
algoritmo de filtrado, denominado diferenciador robusto exacto y uniforme filtrado (UREDF), que
combina las características de filtrado estándar del diferenciador de Levant con un filtro de
mediana no lineal intra pulso. Cabe resaltar que el desempeño de este algoritmo fue demostrado
paralelamente al desarrollo de esta tesis en el manuscrito “Highly Maneuverable Target Tracking
Under Glint Noise via Uniform Robust Exact Filtering Differentiator with Intra Pulse Median Filter”,
publicado en la revista IEEE “Transactions on Aerospace and Electronic Systems” y escrito por
el Dr. Gustavo Pérez y el suscrito. En este manuscrito se concluye que el UREDF muestra un
desempeño superior al de otros algoritmos de estimación y filtrado del estado del arte tales como
el Extended Kalman Filter (EKF), Unscented Kalman Filter (UKF), Cubature Kalman Filter (CKF),
Particle Filter (PF), y el Robust Student-t based Kalman Filter.
En el capítulo IV dos soluciones al problema en estudio son brindadas, siendo la primera solución
(SMO1) basada en la combinación de la capacidad de filtrado del diferenciador Robusto Exacto
y Uniforme filtrado (UREDF) y la robustez para estimación de variables de estado del
diferenciador robusto exacto adaptativo (ARED). Por otro lado, la segunda solución (SMO2)
involucra la estimación de variables de estado de un radar de traqueo pulse-doppler mediante el
filtrado de las mediciones de posición y velocidad por medio de Diferenciadores Robustos
Exactos y Uniformes filtrados (UREDF) y la posterior estimación de variables de estado por medio
del Observador de modos deslizantes de Walcott-Zak (WZSMO). Asimismo, un diferenciador
robusto exacto adaptativo es utilizado para estimar el vector de entrada de control necesario para
que funcione el WZSMO.
En el capítulo V se efectuaron simulaciones en MATLAB® que comprueban que las soluciones
de modos deslizantes propuestas tienen mejor capacidad de filtrado de ruido angular y robustez
que el algoritmo de modelo múltiple interactivo (IMM) durante los cambios de rumbo y maniobra
terminal. Finalmente, en el capítulo VI se propone la propuesta de implementación en un
hardware PXI de National Instruments y en el capítulo VII se brindan conclusiones y trabajo future
a realizar.
This thesis studies state observers based on sliding mode variable structure systems, as an alternative solution to the interactive multiple model algorithm (IMM) based on Kalman and Particle Filters, for the robust estimation of position, velocity, and acceleration of a high maneuverability air target, such as anti-ship missiles or combat aircraft, despite model uncertainties or disturbances and using fire control radar’s position or velocity measurements corrupted by glint noise. In chapter I a study of the state of the art is done, exposing the problem and the current solution to it. Subsequently, in chapter II a study is made of the different dynamic and measurement models of high maneuverability air targets existing in the literature, proposing at the end of the chapter an uncertain linear model of the air target (anti-ship missile) and presenting a simulation of the complete trajectory of it. In chapter III the theory of sliding mode variable structure systems applied to state observers is exposed, the design of the most representative observers is carried out, and simulations of the air target’s estimated trajectory are conducted, comparing at the end of the chapter the results of all state observers based on established performance criteria. Results show that in the absence of noise the Edwards-Spurgeon observer (ESSMO) and Walcott-Zak observer (WZSMO) and Adaptive Robust Exact Differentiator obtain the best performances. In addition, in order to use the observers and differentiators mentioned above a new filtering algorithm is proposed, named Uniform Robust Exact filtering differentiator (UREDF), which combines Levant’s standard filtering with a non-linear median intra pulse filter. It is important to state that the performance of this algorithm was demonstrated along with the writing of this thesis in the manuscript “Highly Maneuverable Target Tracking Under Glint Noise via Uniform Robust Exact Filtering Differentiator with Intra Pulse Median Filter”, which has been published in the IEEE journal “Transactions on Aerospace and Electronic Systems” by Dr. Gustavo Pérez and myself. In this manuscript, it is concluded that the UREDF shows a superior performance than other state-of-the-art estimation and filtering algorithms such as the Extended Kalman Filter (EKF), Unscented Kalman Filter (UKF), Cubature Kalman Filter (CKF), Particle Filter (PF), and the Robust Student-t based Kalman Filter. In chapter IV two solutions to the studied problem are proposed, being the first solution (SMO1) based on the combination of the Uniform robust exact filtered differentiator’s (UREDF) filtering capability and the Adaptive Robust Exact Differentiator’s robustness, exactness, and convergence speed capabilities for state variable estimation. On the other hand, the second solution (SMO2) involves state variable estimation of a pulse-doppler tracking radar by filtering both position and doppler velocity measurements with Uniform Robust Exact Filtered Differentiators (UREDF) and estimating state variables with the Walcott-Zak Sliding Mode Observer (WZSMO). Also, an adaptive robust exact differentiator (ARED) is used to provide the estimated input control vector necessary for the WZSMO to work. In chapter V, MATLAB® simulations were conducted, proving that the sliding mode solutions proposed in chapter IV have better glint noise filtering and robustness capabilities that the Interactive Multiple Model (IMM) algorithm during the misil’s course changes and terminal maneuver. Finally, in chapter VI is proposed the implementation solution in a National Instruments’ PXI and in chapter VII conclusions and future work remarks are given.
This thesis studies state observers based on sliding mode variable structure systems, as an alternative solution to the interactive multiple model algorithm (IMM) based on Kalman and Particle Filters, for the robust estimation of position, velocity, and acceleration of a high maneuverability air target, such as anti-ship missiles or combat aircraft, despite model uncertainties or disturbances and using fire control radar’s position or velocity measurements corrupted by glint noise. In chapter I a study of the state of the art is done, exposing the problem and the current solution to it. Subsequently, in chapter II a study is made of the different dynamic and measurement models of high maneuverability air targets existing in the literature, proposing at the end of the chapter an uncertain linear model of the air target (anti-ship missile) and presenting a simulation of the complete trajectory of it. In chapter III the theory of sliding mode variable structure systems applied to state observers is exposed, the design of the most representative observers is carried out, and simulations of the air target’s estimated trajectory are conducted, comparing at the end of the chapter the results of all state observers based on established performance criteria. Results show that in the absence of noise the Edwards-Spurgeon observer (ESSMO) and Walcott-Zak observer (WZSMO) and Adaptive Robust Exact Differentiator obtain the best performances. In addition, in order to use the observers and differentiators mentioned above a new filtering algorithm is proposed, named Uniform Robust Exact filtering differentiator (UREDF), which combines Levant’s standard filtering with a non-linear median intra pulse filter. It is important to state that the performance of this algorithm was demonstrated along with the writing of this thesis in the manuscript “Highly Maneuverable Target Tracking Under Glint Noise via Uniform Robust Exact Filtering Differentiator with Intra Pulse Median Filter”, which has been published in the IEEE journal “Transactions on Aerospace and Electronic Systems” by Dr. Gustavo Pérez and myself. In this manuscript, it is concluded that the UREDF shows a superior performance than other state-of-the-art estimation and filtering algorithms such as the Extended Kalman Filter (EKF), Unscented Kalman Filter (UKF), Cubature Kalman Filter (CKF), Particle Filter (PF), and the Robust Student-t based Kalman Filter. In chapter IV two solutions to the studied problem are proposed, being the first solution (SMO1) based on the combination of the Uniform robust exact filtered differentiator’s (UREDF) filtering capability and the Adaptive Robust Exact Differentiator’s robustness, exactness, and convergence speed capabilities for state variable estimation. On the other hand, the second solution (SMO2) involves state variable estimation of a pulse-doppler tracking radar by filtering both position and doppler velocity measurements with Uniform Robust Exact Filtered Differentiators (UREDF) and estimating state variables with the Walcott-Zak Sliding Mode Observer (WZSMO). Also, an adaptive robust exact differentiator (ARED) is used to provide the estimated input control vector necessary for the WZSMO to work. In chapter V, MATLAB® simulations were conducted, proving that the sliding mode solutions proposed in chapter IV have better glint noise filtering and robustness capabilities that the Interactive Multiple Model (IMM) algorithm during the misil’s course changes and terminal maneuver. Finally, in chapter VI is proposed the implementation solution in a National Instruments’ PXI and in chapter VII conclusions and future work remarks are given.
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Teoría del control, Control automático, Estadística robusta, Vehículos aéreos no tripulados
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