Modeling, experimental validation, and model order reduction of mirror thermal dynamics

Linear extrapolation method based on multiple equiproportional models for thermal performance prediction of ultra-large array

Strong demand for developing the photothermal (PT) and electrothermal devices with ultra-large array is increasing. Thermal performance prediction is vital to optimize the key properties of the devices with ultra-large array. Finite element method (FEM) provides a powerful numerical approach for solving complex thermophysics issues. However, for calculating the performance of devices with ultra-large array, it is very memory-consuming and time-consuming to build an equal scale three-dimensional (3D) FEM model. For an ultra-large periodic array irradiated with a local heating source, the use of periodic boundary conditions could lead to considerable errors. To solve this problem, a linear extrapolation method based on multiple equiproportional models (LEM-MEM) is proposed in this paper. The proposed method builds several reduced-size FEM models to carry out simulation and extrapolation, which avoids dealing with the ultra-large arrays directly and greatly reduces the computation consumption. To verify the accuracy of LEM-MEM, a PT transducer with beyond 4000 × 4000 pixels is proposed, fabricated, tested and compared with the prediction results. Four different pixel patterns are designed and fabricated to test their steady thermal properties. The experimental results demonstrate that LEM-MEM has great predictability, and the maximum percentage error of average temperature is within 5.22% in four different pixel patterns. In addition, the measured response time of the proposed PT transducer is within 2 ms. The proposed LEM-MEM not only provides design guidance for optimizing PT transducers, but is also very useful for other thermal engineering problems in ultra-large array that requires facile and efficient prediction strategy.

Apparatus and its principle for thermal aberration compensation

Thermal aberrations caused by absorption of laser beams degrade the image quality of exposure tools during the working process. Many compensators, such as lens movement or lens deformation, are used to compensate for low-order thermal aberrations of optical systems. In this paper, an apparatus with higher-order aberration correction capability is presented. The main principle of the apparatus is to actively heat and cool the lens near the pupil to generate a desired temperature profile to compensate for thermal aberrations. We first introduce the basic concept of the apparatus. Then we establish an analytical model to describe the lens temperature of the apparatus based on its working principle and demonstrate its compensation capability. Finally, an algorithm for dynamic thermal aberrations compensation is proposed to overcome the time lag effects of a thermally controlled lens.

Simulation and compensation of thermal lensing in optical systems

High-power optical systems are used in a number of industrial applications. One difficulty in designing such systems is that the beam itself is a significant source of heat, which changes the optical properties of the system. To reduce this effect, we propose a new thermal lensing compensation technique based on a detailed analysis of the optical properties of the high-power optical system. To this end, we have developed a new ray tracing simulation technique that accurately models optical propagation through inhomogeneous, anisotropic, and deformed media. This model enables the performance of systems in physically realistic situations to be evaluated efficiently. Experimental comparisons were conducted to validate the simulation. We found excellent agreement between the simulation and the measured data. We have validated the simulation technique for a single lens setup and a complex optical scanner system.

Multilayer thermal control for high-altitude vertical imaging aerial cameras

Aerial cameras play an important role in obtaining ground information. However, the complex and changeable aviation environment limits its application. Thermal control is vital in improving the environmental adaptability of the camera to obtain high-quality images. Conventional thermal control of aerial cameras is to directly implement active thermal control on the optical system, which is a single layer thermal control method. Such a method cannot isolate the optical system from the external environment. It results in a sharp increase in thermal control power consumption and in temperature gradient, which increases the difficulty of thermal control. Here, we propose a multilayer system-level thermal control approach by partitioning the aerial camera into two parts, i.e., the imaging system and the outline cabin. Two parts are connected by materials with poor thermal conductivity, and an air insulation interlayer is formed in between. Theoretical analysis is carried out to model the internal and external thermal environment of the aerial camera in a complex high-altitude environment. We study passive thermal control of the thermal insulation layer of the outline cabin, the optical window, the imaging optics, the CCD device, and the phase change material, and active thermal control of the thermal convection and heating film. Numerical modeling on the multilayer thermal control of the system is carried out and verified by the thermal equilibrium test and actual field flight test. The total power consumption of the thermal control system is 270 W. High-quality images are obtained when the temperature gradient of the optical lens is less than 5°C and the temperature of the CCD is lower than 30°C. Our technology is simple, accurate, low cost, and easy to implement compared to the conventional thermal control method. It effectively lowers the power consumption and reduces the difficulty of thermal control.

Dual-update data-driven control of deformable mirrors using Walsh basis functions

We develop a novel data-driven method for deformable mirror (DM) control. The developed method updates both the DM model and DM control actions that produce desired mirror surface shapes. The novel method explicitly takes into account actuator constraints and couples a feedback-control algorithm with an algorithm for recursive estimation of DM influence function models. We also explore the possibility of using Walsh basis functions for DM control. By expressing the desired and observed mirror surface shapes as sums of Walsh pattern matrices, we formulate the control problem in the 2D Walsh basis domain. We thoroughly experimentally verify the developed approach on a 140-actuator MEMS DM, developed by Boston Micromachines. Our results show that the novel method produces the root-mean-square surface error in the 14-40 nanometer range. These results can additionally be improved by tuning the control and estimation parameters. The developed approach is also applicable to other DM types such as segmented DMs.

General approach to precise deformable mirror control

We develop a simple and effective control method for accurate control of deformable mirrors (DMs). For a desired DM surface profile and using batches of observed surface profile data, the proposed method adaptively determines both a DM model (influence matrix) and control actions that produce the desired surface profile with good accuracy. In the first iteration, the developed method estimates a DM influence matrix by solving a multivariable least-squares problem. This matrix is then used to compute the control actions by solving a constrained least-squares problem. Then, the computed actions are randomly perturbed and applied to the DM to generate a new batch of surface profile data. The new data batch is used to estimate a new influence matrix that is then used to re-compute control actions. This procedure is repeated until convergence is achieved. The method is experimentally tested on a Boston Micromachines DM with 140 micro-electronic-mechanical-system actuators. Our experimental results show that the developed control approach can achieve accurate correction despite significant DM nonlinearities. Using only a few control iterations, the developed method is able to produce a surface profile root-mean-square error that varies from 5 - 30 [nm] for most of the tested Zernike wave-front modes without using direct feedback control. These results can additionally be improved by using larger data batches and more iterations or by combining the developed approach with feedback control. Finally, as we experimentally demonstrate, the developed method can be used to estimate a DM model that can effectively be used for a single-step open-loop DM control.