10.24423/engtrans.242.2015
MOPSO Based Multi-Objective Robust H2/H∞ Vibration Control for Typical Engineering Equipment
References
Harris C.M., Shock and vibration handbook, 33–50, McGraw-Hill, New York, 1987.
Beard A.M., Schubert D.W., von Flotow A.H., Practical product implementation of an active/passive vibration isolation system, Proceedings of SPIE 1994 International Symposium on Optics, Imaging, and Instrumentation, International Society for Optics and Photonics, 38–49, 1994.
Bronowicki A.J., MacDonald R., Gursel Y., Dual stage passive vibration isolation for optical interferometer missions, Astronomical Telescopes and Instrumentation, International Society for Optics and Photonics, 753–763, 2003.
Daley S., Hätönen J., Owens D.H., Active vibration isolation in a “smart spring” mount using a repetitive control approach, Control Engineering Practice, 14, 9, 991–997, 2006.
Karnopp D., Crosby M.J., Harwood R.A., Vibration control using semi-active force generators, Journal of Manufacturing Science and Engineering, 96, 2, 619–626, 1974.
Hrovat D., Applications of optimal control to advanced automotive suspension design, Journal of Dynamic Systems, Measurement, and Control, 115, 2, 328–342, 1993.
Du H., Yim Sze K., Lam J., Semi-active H∞ control of vehicle suspension with magnetorheological dampers, Journal of Sound and Vibration, 283, 3, 981–996, 2005.
Baeyens E., Khargonekar P.P., Some examples in mixed H2/H∞ control, American Control Conference, Vol. 2, 1608–1612, 1994.
Deb K., Pratap A., Agarwal S., Meyarivan T., A fast and elitist multiobjective genetic algorithm: NSGA-II, Evolutionary Computation, IEEE Transactions on Evolutionary Computation, 6, 2, 182–197, 2002.
Zitzler E., Thiele L., Multiobjective evolutionary algorithms: a comparative case study and the strength Pareto approach, Evolutionary Computation, 3, 4, 257–271, 1999.
Laumanns M., SPEA2: Improving the strength Pareto evolutionary algorithm, 19–26, 2001.
Molina-Cristóbal A., Griffin I.A., Fleming P.J., Linear matrix inequalities and evolutionary optimization in multiobjective control, International Journal of Systems Science, 37, 8, 513–522, 2006.
Pedersen G.K.M., Langballe A.S., Wisniewski R., Synthesizing multi-objective H2/H∞ dynamic controller using evolutionary algorithms, 15th Triennial World Congress, 2002.
Eberhart R.C., Kennedy J., A new optimizer using particle swarm theory, Proceedings of the Sixth International Symposium on Micro Machine and Human Science, 39–42, 1995.
Farshidianfar A., Saghafi A., Kalami S.M., Saghafi I., Active vibration isolation of machinery and sensitive equipment using H∞ control criterion and particle swarm optimization method, Meccanica, 47, 2, 437–453, 2012.
Coello C.A., Lechuga M.S., MOPSO: A proposal for multiple objective particle swarm optimization, Proceedings of the 2002 Congress on IEEE, 1051–1056, 2002.
Fonseca C.M., Fleming P.J., An overview of evolutionary algorithms in multi-objective optimization, evolutionary computation, 3, 1, 1–16, 1995.
Goldberg D.E., Richardson J., Genetic algorithms with sharing for multimodal function optimization, Genetic Algorithms and their Applications: Proceedings of the Second International Conference on Genetic Algorithms, 41–49, 1987.
Xu Y.L., Yang Z.C., Chen J., Liu H.J., Micro vibration control platform for high technology facilities subject to traffic-induced ground Motion, Engineering Structures, 25, 8, 1069-1082, 2003.
DOI: 10.24423/engtrans.242.2015