Examinando por Materia "Adaptive control systems"

Mostrando 1 - 2 de 2
  • No hay miniatura disponible
    Ítem
    Effects of aberrations in vortex-beams generated with amplitude diffraction gratings
    (SPIE, 2016-01-01) Cuartas-Vélez, C.; Echeverri-Chacón, S.; Restrepo, R.; Universidad EAFIT. Departamento de Ciencias Básicas; Óptica Aplicada
    We present a mathematical model for the generation of vortex-beams by using a square profile amplitude fork diffraction grating with arbitrary topological charge. The mathematical framework of aberrations in the forked-shape diffraction grating is analysed, and the resulting diffracted pattern is simulated. Three cases of desired distortions (aberrations) in the diffraction grating are considered, obtaining phase modulation from the amplitude grating. Experimental optical vortices are generated by using a transmission spatial light modulator, which is used as a dynamic diffraction grating, allowing us to aberrate it. We show the effect of aberrations in the experimental diffracted vortex-beams and compare it with the numerical simulation. © 2016 SPIE.
  • No hay miniatura disponible
    Ítem
    Modeling and control of nonlinear systems using an Adaptive LAMDA approach
    (Elsevier BV, 2020-01-01) Morales L.; Aguilar J.; Rosales A.; Chávez D.; Leica P.; Morales L.; Aguilar J.; Rosales A.; Chávez D.; Leica P.; Universidad EAFIT. Departamento de Ingeniería de Sistemas; I+D+I en Tecnologías de la Información y las Comunicaciones
    This paper presents a soft computing technique for modeling and control of nonlinear systems using the online learning criteria. In order to obtain an accurate modeling, and therefore a controller with good performance, a method based on the fundamentals of the artificial intelligence algorithm, called LAMDA (Learning Algorithm for Multivariate Data Analysis), is proposed, with a modification of its structure and learning method that allows the creation of an adaptive approach. The novelty of this proposal is that for the first time LAMDA is used for fuzzy modeling and control of complex systems, which is a great advantage if the mathematical model is not available, partially known, or variable. The adaptive LAMDA consists of a training stage to establish initial parameters for the controller, and the application stage in which the control strategy is computed and updated using an online learning that evaluates the closed-loop system. We validate the method in several control tasks: (1) Regulation of mixing tank with variable dead-time (slow variable dynamics), (2) Regulation of a Heating, Ventilation and Air-Conditioning (HVAC) system (multivariable slow nonlinear dynamics), and (3) trajectory tracking of a mobile robot (multivariable fast nonlinear dynamics). The results of these experiments are analyzed and compared with other soft computing control techniques, demonstrating that the proposed method is able to perform an accurate control through the proposed learning technique. © 2020 Elsevier B.V.