Minimum variance control for mitigation of vibrations in adaptive optics systems

An Optimal Integral Controller for Adaptive Optics Systems

Integral controllers are commonly employed in astronomical adaptive optics. This work presents a novel tuning procedure for integral controllers in adaptive optics systems which relies on information about the measured disturbances. This tuning procedure consists of two main steps. First, it models and identifies measured disturbances as continuous-time-damped oscillators using Whittles´s likelihood and the wavefront sensor output signal. Second, it determines the integral controller gain of the adaptive optics system by minimizing the output variance. The effectiveness of this proposed method is evaluated through theoretical examples and numerical simulations conducted using the Object-Oriented Matlab Adaptive Optics toolbox. The simulation results demonstrate that this approach accurately estimates the disturbance model and can reduce the output variance. Our proposal results in improved performance and better astronomical images even in challenging atmospheric conditions. These findings significantly contribute to adaptive optics system operations in astronomical observatories and establish our procedure as a promising tool for fine-tuning integral controllers in astronomical adaptive optics systems.

Dynamic data reconciliation to improve the result of controller performance assessment based on GMVC

Due to the complexity of the industrial working environment, controllers are susceptible to various disturbance signals, resulting in unsatisfactory control performance. Therefore, it is especially important to assess the controller performance. Considering the harmful effect of measurement noise on controller performance assessment (CPA) based on generalized minimum variance control (GMVC), this paper proposes dynamic data reconciliation (DDR) to improve the accuracy of CPA based on GMVC. The paper first introduces CPA based on GMVC, and then analyzes the influence of measurement noise on GMVC based CPA index. DDR combined with GMVC based CPA is then proposed and analyzed in both SISO and MIMO systems to weaken the impact of measurement noise on CPA index. For both Gaussian distributed noise and non-Gaussian distributed noise, the formulation of DDR is derived from the Bayesian formula and maximum likelihood estimate. The effectiveness of the proposed method is verified in different case studies (involving both SISO and MIMO systems), and further verified by the control process of DC-AC converter. The simulation and experiment results demonstrate that the results of CPA based on GMVC can be obviously improved by using DDR.

Disturbance Modelling for Minimum Variance Control in Adaptive Optics Systems Using Wavefront Sensor Sampled-Data

Modern large telescopes are built based on the effectiveness of adaptive optics systems in mitigating the detrimental effects of wavefront distortions on astronomical images. In astronomical adaptive optics systems, the main sources of wavefront distortions are atmospheric turbulence and mechanical vibrations that are induced by the wind or the instrumentation systems, such as fans and cooling pumps. The mitigation of wavefront distortions is typically attained via a control law that is based on an adequate and accurate model. In this paper, we develop a modelling technique based on continuous-time damped-oscillators and on the Whittle’s likelihood method to estimate the parameters of disturbance models from wavefront sensor time-domain sampled-data. On the other hand, when the model is not accurate, the performance of the minimum variance controller is affected. We show that our modelling and identification techniques not only allow for more accurate estimates, but also for better minimum variance control performance. We illustrate the benefits of our proposal via numerical simulations.

Theoretical and experimental study on the testing accuracy of the image stabilization system of a space astronomical telescope

Space astronomical telescopes must test the image stabilization accuracy of their image stabilization system prior to entering the orbit. According to the position characteristics of the fine guidance sensor of telescopes required by the China National Space Administration, a simulation model of moving guide stars is proposed in this study to test the image stabilization accuracy of space telescopes. The simulation model for synchronous moving guide stars is based on the principle of mutual collimation of the diagonal field of view of the optical system of telescope. Realize the multi-field moving guide stars with high synchronization accuracy simulated by the same target source. Compared to traditional methods, this method requires simple manufacturing and has high flexibility. The error sources affecting the simulation accuracy of the moving guide stars are analyzed, and an error model is established. Analysis results show that the simulation accuracy of the moving guide stars can reach 0.046^''. The simulation model of guide stars is verified through experiments in which the influence of the vibration isolation platform is considered. Experiment results show that the simulation accuracy of motion guide stars is 0.036^'', satisfying the accuracy requirements (<0.08^'') of the accuracy test for the telescope image stabilization of telescopes.