Vibration Isolator Design for Space Application Based on Multiobjective Optimization Method

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A multiobjective optimization based vibration isolator design for space application is described. It is common to use passive isolator and isolate the platform noise in space applications. The design of a passive isolator involves a trade-off between the resonant peak reduction and the high frequency attenuation. The equation of motion and transfer function model for single-stage and two-stage connector model is derived by using basic principle. The multiobjective optimization model is proposed, where the design variables are the damping coefficients and stiffness coefficients, the objective functions are the resonant peak reduction and the high frequency attenuation, and the constraints are the natural frequency of the connector. The multiobjective optimization problems for the design of the passive isolator are solved by using the multiobjective evolutionary algorithm based on decomposition (MOEA/D). The Pareto front obtained can provide multiple candidate solutions for the designer. The method is effective for the design process of the passive isolator.

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77-81

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August 2013

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© 2013 Trans Tech Publications Ltd. All Rights Reserved

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[1] A.J. Bronowicki, Vibration isolator for large space telescopes. Palm Springs, California, (2004).

Google Scholar

[2] M.D. Hasha, Passive isolation/damping system for the Hubble space telescope reaction wheels. California, (1987).

Google Scholar

[3] B. Wie, Space Vehicle Dynamics and Control. American Institute of Aeronautics and Astronautics Inc., Reston, Virginia, (2008).

Google Scholar

[4] W.K. Belvin, Sparks D.W., Horta L.G., et al., On the isolation of science payloads from spacecraft vibrations. New Orleans, LA, (1995).

DOI: 10.2514/6.1995-1234

Google Scholar

[5] E. Flint, Evert M.E., Anderson E., et al., Active/passive counter-force vibration control and isolation systems. Big Sky, Montana, (2000).

DOI: 10.1109/aero.2000.878440

Google Scholar

[6] K.J. Pendergast and Schauwecker C.J., Use of a passive reaction wheel jitter isolation system to meet the advanced X-ray astrophysics facility imaging performance requirements. (1998).

DOI: 10.1117/12.324508

Google Scholar

[7] K. Deb, Pratap A., Agrwal S., et al., A fast and elitist multiobjective genetic algorithm: NSGA-II, IEEE Transaction on Evolutionary Computation. 6(2002): 182-197.

DOI: 10.1109/4235.996017

Google Scholar

[8] A. Messac, Control-structure integrated design with closed-form design metrics using physical programming, AIAA Journal. 36(1998): 855-864.

DOI: 10.2514/3.13901

Google Scholar

[9] E.I. Rivin, Passive Vibration Isolation. American Society of Mechanical Engineers, New York, (2003).

Google Scholar

[10] K.M. Miettinen, Nonlinear Multiobjective Optimization. Kluwer, Norwell, MA, (1999).

Google Scholar

[11] Q. Zhang and Li H., MOEA/D: a multiobjective evolutionary algorithm based on decomposition, IEEE Transaction on Evolutionary Computation. 11(2007): 712-731.

DOI: 10.1109/tevc.2007.892759

Google Scholar

[12] K. Deb and Jain H., An improved NSGA-II procedure for many-objective optimization, part II: handling constraints and extending to an adaptive approach. Indian Institute of Technology, Kanpur, (2012).

DOI: 10.1109/cec.2012.6256519

Google Scholar