Browsing by Author "Guzman, Dani"
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- ItemComparison of vibration mitigation controllers for adaptive optics systems(OPTICAL SOC AMER, 2012) Guesalaga, Andres; Neichel, Benoit; Rigaut, Francois; Osborn, James; Guzman, DaniVibrations are detrimental to the performance of modern adaptive optics (AO) systems. In this paper, we describe new methods tested to mitigate the vibrations encountered in some of the instruments of the Gemini South telescope. By implementing a spectral analysis of the slope measurements from several wavefront sensors and an imager, we can determine the frequencies and magnitude of these vibrations. We found a persistent vibration at 55 Hz with others occurring occasionally at 14 and 100 Hz. Two types of AO controllers were designed and implemented, Kalman and H-infinity, in the multiconjugate AO tip-tilt loop. The first results show a similar performance for these advanced controllers and a clear improvement in vibration rejection and overall performance over the classical integrator scheme. It is shown that the reduction in the standard deviation of the residual slopes (as measured by wavefront sensors) is highly dependent on turbulence, wind speed, and vibration conditions, ranging-in terms of slopes RMS value-from an almost negligible reduction for high speed wind to a factor of 5 for a combination of low wind and strong vibrations. (c) 2012 Optical Society of America
- ItemDeformable mirror model for open-loop adaptive optics using multivariate adaptive regression splines(OPTICAL SOC AMER, 2010) Guzman, Dani; de Cos Juez, Francisco Javier; Sanchez Lasheras, Fernando; Myers, Richard; Young, LauraOpen-loop adaptive optics is a technique in which the turbulent wavefront is measured before it hits the deformable mirror for correction. We present a technique to model a deformable mirror working in open-loop based on multivariate adaptive regression splines (MARS), a non-parametric regression technique. The model's input is the wavefront correction to apply to the mirror and its output is the set of voltages to shape the mirror. We performed experiments with an electrostrictive deformable mirror, achieving positioning errors of the order of 1.2% RMS of the peak-to-peak wavefront excursion. The technique does not depend on the physical parameters of the device; therefore it may be included in the control scheme of any type of deformable mirror. (C) 2010 Optical Society of America
- ItemModeling a MEMS deformable mirror using non-parametric estimation techniques(OPTICAL SOC AMER, 2010) Guzman, Dani; de Cos Juez, Francisco Javier; Myers, Richard; Guesalaga, Andres; Sanchez Lasheras, FernandoUsing non-parametric estimation techniques, we have modeled an area of 126 actuators of a micro-electro-mechanical deformable mirror with 1024 actuators. These techniques produce models applicable to open-loop adaptive optics, where the turbulent wavefront is measured before it hits the deformable mirror. The model's input is the wavefront correction to apply to the mirror and its output is the set of voltages to shape the mirror. Our experiments have achieved positioning errors of 3.1% rms of the peak-to-peak wavefront excursion. (C) 2010 Optical Society of America
- ItemUsing artificial neural networks for open-loop tomography(OPTICAL SOC AMER, 2012) Osborn, James; De Cos Juez, Francisco Javier; Guzman, Dani; Butterley, Timothy; Myers, Richard; Guesalaga, Andres; Laine, JesusModern adaptive optics (AO) systems for large telescopes require tomographic techniques to reconstruct the phase aberrations induced by the turbulent atmosphere along a line of sight to a target which is angularly separated from the guide sources that are used to sample the atmosphere. Multi-object adaptive optics (MOAO) is one such technique. Here, we present a method which uses an artificial neural network (ANN) to reconstruct the target phase given off-axis references sources. We compare our ANN method with a standard least squares type matrix multiplication method and to the learn and apply method developed for the CANARY MOAO instrument. The ANN is trained with a large range of possible turbulent layer positions and therefore does not require any input of the optical turbulence profile. It is therefore less susceptible to changing conditions than some existing methods. We also exploit the non-linear response of the ANN to make it more robust to noisy centroid measurements than other linear techniques. (C) 2012 Optical Society of America