Receding-horizon adaptive control of aero-optical wavefronts

Tesch, Jonathan; Gibson, Steve; Verhaegen, Michel

doi:10.1117/1.oe.52.7.071406

Cited by 21 publications

(8 citation statements)

References 30 publications

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“…This latency problem has previously been addressed using various prediction methods such as dynamic mode decomposition 19 , receding-horizon adaptive control 20 , and simple "frozen-flow" advection prediction 21 . We recently developed a method 7 for overcoming this latency problem using a predictive neural network controller in conjunction with a conventional feedback loop as shown in Figure 6.…”

Section: American Institute Of Aeronautics and Astronauticsmentioning

confidence: 99%

A Robust Modification of a Predictive Adaptive-Optic Control Method for Aero-Optics

Burns

Jumper

Gordeyev

2016

47th AIAA Plasmadynamics and Lasers Conference

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A modification of a previous predictive adaptive-optic controller is presented in this paper. Conventional adaptive-optic controllers suffer from bandwidth limitations caused by latency in their control loops. This latency severely limits their capabilities in aero-optic applications that cannot be overcome with conventional feedback techniques. Our method uses prior knowledge of flow behavior to predict future behavior, and thus overcome deadtime. We have modified our previous neural network controller to use a linearized predictor, which we demonstrate to be more accurate, more robust to noise and flow disturbances, and less computationally expensive. Our previous neural network method showed disturbance rejection in the range of 35-55% in simulation over our test conditions in the most optically-active regions, while the improved method shows disturbance rejection between 45-75% over the same range. Additionally, we demonstrate that the predictive control method is stable, even in the presence of latency uncertainty.

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Section: American Institute Of Aeronautics and Astronauticsmentioning

confidence: 99%

A Robust Modification of a Predictive Adaptive-Optic Control Method for Aero-Optics

Burns

Jumper

Gordeyev

2016

47th AIAA Plasmadynamics and Lasers Conference

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“…The Nelder-Mead [26] algorithm was used in [21] for correction of optical aberrations in a closed-loop feedback. The receding horizon approach was recently applied for control of aero-optical wavefronts [22].…”

Section: B Purpose Of This Papermentioning

confidence: 99%

“…For example, for the AO system with a membrane mirror considered in [22] and [23], the prediction horizon of N c = 20 was used. Further analysis of different prediction horizons is out of scope of this paper, but will be the subject of future work.…”

Section: Length Of the Prediction Horizon And The Computational Timentioning

confidence: 99%

Feasibility of Constrained Receding Horizon Control Implementation in Adaptive Optics

Konnik

Doná

2015

IEEE Trans. Contr. Syst. Technol.

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Adaptive optics (AO) provide real-time compensation for atmospheric turbulence to improve the resolution of images acquired by ground-based optical telescopes. The actuators in deformable mirrors, which are used as correctors, are constrained by a maximal allowable movement. The control techniques used in current AO systems do not account for these constraints, leading to inferior performance and a risk of damage of the deformable mirror's surface. This paper presents a feasibility study for receding horizon control (RHC) with online constrained quadratic programming (QP). The results of numerical simulations provided in this paper are based on realistic models obtained from an optical test-bench. We compare QP algorithms that represent three main methods for convex optimization: 1) interior point; 2) active set (AS); and 3) gradient-based algorithms. It is shown that constrained RHC is computationally feasible for moderate-size AO systems using hot-started structure-exploiting AS QP solvers with bound constraints. An evaluation of performance indicates that RHC is advantageous in terms of atmospheric turbulence rejection in the case of active constraints.

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“…Receding Horizon Control: pros and cons. The slower the dynamics of the actuators, the longer the prediction horizons must be (e.g., membrane mirrors 16 may require N p = 20), which makes a constrained operation difficult. For certain types of mirrors, such as MEMS with decoupled actuators, RHC is unlikely to provide noticeable performance advantages (apart from easier implementation).…”

Section: Summary Of Computational Performance Evaluationmentioning

confidence: 99%

Preliminary evaluation and comparison of atmospheric turbulence rejection performance for infinite and receding horizon control in adaptive optics systems

Konnik

Doná

2014

SPIE Proceedings

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Model-based optimal control such as Linear Quadratic Gaussian (LQG) control has been attracting considerable attention for adaptive optics systems. The ability of LQG to handle the complex dynamics of deformable mirrors and its relatively simple implementation makes LQG attractive for large adaptive optics systems. However, LQG has its own share of drawbacks, such as suboptimal handling of constraints on actuators movements and possible numerical problems in case of fast sampling rate discretisation of the corresponding matrices. Unlike LQG, the Receding Horizon Control (RHC) technique provides control signals for a deformable mirror that are optimal within the prescribed constraints. This is achieved by reformulating the control problem as an online optimisation problem that is solved at each sampling instance. In the unconstrained case, RHC produces the same control signals as LQG. However, when the control signals reach the constraints of actuator's allowable movement in a deformable mirror, RHC finds the control signals that are optimal within those constraints, rather than just clipping the unconstrained optimum as commonly done in LQG control. The article discusses the consequences of high-gain LQG control operation in the case when the constraints on the actuator's movement are reached. It is shown that clipping / saturating the control signals is not only suboptimal, but may be hazardous for the surface of a deformable mirror. The results of numerical simulations indicate that high-gain LQG control can lead to abrupt changes and spikes in the control signal when saturation occurs. The article further discusses a possible link between high-gain LQG and the waffle mode in the closed-loop operation of astronomical adaptive optics systems. Performance evaluation of Receding Horizon Control in terms of atmospheric disturbance rejection and a comparison with Linear Quadratic Gaussian control are performed. The results of the numerical simulations suggest that the disturbance rejection performance in the unconstrained case is the same for LQG and RHC, while RHC clearly outperforms the saturated LQG control in terms of atmospheric turbulence rejection. More importantly, RHC can be used in high-gain mode, unlike LQG, providing better atmospheric disturbance rejection in the constrained case.

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Receding-horizon adaptive control of aero-optical wavefronts

Cited by 21 publications

References 30 publications

A Robust Modification of a Predictive Adaptive-Optic Control Method for Aero-Optics

A Robust Modification of a Predictive Adaptive-Optic Control Method for Aero-Optics

Feasibility of Constrained Receding Horizon Control Implementation in Adaptive Optics

Preliminary evaluation and comparison of atmospheric turbulence rejection performance for infinite and receding horizon control in adaptive optics systems

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