Optimization algorithms for wavefront sensorless adaptive optics

Optimization is a process to search the most suitable solution for a problem within an acceptable time interval. The algorithms that solve the optimization problems are called as optimization algorithms. In the literature, there are many optimization algorithms with different characteristics. The optimization algorithms can exhibit different behaviors depending on the size, characteristics and complexity of the optimization problem. In this study, six well-known population based optimization algorithms (artificial algae algorithm - AAA, artificial bee colony algorithm - ABC, differential evolution algorithm - DE, genetic algorithm - GA, gravitational search algorithm - GSA and particle swarm optimization - PSO) were used. These six algorithms were performed on the CEC&rsquo;17 test functions. According to the experimental results, the algorithms were compared and performances of the algorithms were evaluated.

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Designing Stochastic Optimization Algorithms for Real-world Applications

IEEJ Transactions on Electronics Information and Systems ◽

10.1541/ieejeiss.132.2 ◽

2012 ◽

Vol 132 (1) ◽

pp. 2-5

Author(s):

Hiroshi Someya ◽

Hisashi Handa ◽

Seiichi Koakutsu

Keyword(s):

Stochastic Optimization ◽

Real World ◽

Optimization Algorithms ◽

Real World Applications ◽

Stochastic Optimization Algorithms

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Adaptive optics with adaptive filtering and control

Proceedings of the 2004 American Control Conference ◽

10.23919/acc.2004.1384398 ◽

2004 ◽

Author(s):

Yu-Tai Liu ◽

S. Gibson

Keyword(s):

Adaptive Optics ◽

Adaptive Filtering ◽

And Control

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Accounting for mirror dynamics in optimal Adaptive Optics control

2009 European Control Conference (ECC) ◽

10.23919/ecc.2009.7074944 ◽

2009 ◽

Cited By ~ 1

Author(s):

Carlos Correia ◽

Henri-Francois Raynaud ◽

Caroline Kulcsar ◽

Jean-Marc Conan

Keyword(s):

Adaptive Optics

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The Condition for Absolute Stability of an Electroelastic Actuator Control System for Nanomechatronics

Elektrichestvo ◽

10.24160/0013-5380-2020-10-52-58 ◽

2020 ◽

Vol 10 (10) ◽

pp. 52-58

Author(s):

Sergey M. AFONIN ◽

Keyword(s):

Control System ◽

Adaptive Optics ◽

Absolute Stability ◽

Deformation Characteristic ◽

Straight Line Segment ◽

Control Mechanisms ◽

Relative Width ◽

Random Inputs ◽

Deformation Control ◽

Actuator Control

An electroelastic actuator for nanomechatronics is used in nanotechnology, adaptive optics, microsurgery, microelectronics, and biomedicine to actuate or control mechanisms, systems based on the electroelastic effect, and to convert electrical signals into mechanical displacements and forces. In nanomechatronic systems, a piezoactuator is used in scanning microscopy, laser systems, in astronomy for precision alignment, for compensation of temperature, gravitational deformations and atmospheric turbulence, focusing, and stabilizing the image. In this study, a condition for absolute stability of an electroelastic actuator control system for nanomechatronics under deterministic and random inputs is obtained. A number of equilibrium positions in an electroelastic actuator mechatronic control system are found, the totality of which is represented by a straight line segment. The electroelastic actuator’s deformation control system dead band relative width is determined for the actuator’s symmetric and asymmetric hysteresis characteristics. Under deterministic inputs and with fulfilling the condition for the derivative of the nonlinear hysteresis actuator deformation characteristic, the set of equilibrium positions of the electroelastic actuator control system for nanomechatronics is absolutely stable. Under random inputs, the system absolute stability with respect to the mathematical expectations of the electroelastic actuator mechatronic control system equilibrium positions has been determined subject to fulfilling the condition on the derivative of the actuator hysteresis characteristic.

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