Engineering Transactions, 65, 3, pp. 405–422, 2017

Active Vibration Control with Multi-Objective Control Output for Typical Engineering Equipment

Xu JIAN
China National Machinery Industry Corporation
China

Zhang TONG-YI
China IPPR International Engineering Co., Ltd
China

Huang WEI
China IPPR International Engineering Co., Ltd
China

Hu MING-YI
China IPPR International Engineering Co., Ltd
China

In traditional active vibration control, a single-objective control output is often considered and constrained, but in fact some conflicting performance indexes are always emerging simultaneously and a one-sided method for pursuing only one excellent output is adopted, which may sacrifice other control characteristics. In this paper, a novel active vibration control with multi-objective control output was proposed for machinery equipment and sensitive equipment, and the latest artificial intelligence – multi-objective particle swarm optimization (MOPSO) was utilized, and the active controller was evaluated by the $H_∞$ criterion, meanwhile an active control with a single-objective control output was also carried out for comparison. Numerical studies demonstrated that a pair of conflicting indexes could be balanced well in the proposed strategy, and thus only one blindly pursued control output was effectively overcome.
Keywords: MOPSO; active vibration control; multi-objective control output; equipment
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References

Harris C.M., Shock and vibration handbook, pp. 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, SPIE’s 1994 International Symposium on Optics, Imaging, and Instrumentation, International Society for Optics and Photonics, pp. 38–49, 1994.

Gawronski W., Advanced Structural Dynamics and Active Control of Structures, Springer-Verlag, 2004.

Preumont A., Vibration Control of Active Structures, 3rd ed., Springer, 2011.

Spencer Jr. B.F., Nagarajaiah S., State of the Art of Structural Control, ASCE Journal of Structural Engineering, 129(7): 845–856, 2003.

Blachowski B., Model based predictive control of guyed mast vibration, Journal of Theoretical and Applied Mechanics, 45: 405–423, 2007.

Pnevmatikos N., Gantes C., Control strategy for mitigating the response of structures subjected to earthquake actions, Engineering Structures, 32(11): 3616–3628, 2010.

Khot S.M., Yelve N.P., Tomar R., Desai S., Vittal S., Active vibration control of cantilever beam by using PID based output feedback controller, Journal of Vibration and Control, 18(3): 366–372, 2012.

Huang W., Xu J., Zhu D.Y., Lu J.W., Lu K.L., Hu M.Y., MOPSO based multiobjective robust H2/H1 vibration control for typical engineering equipment, Engineering Transactions, 63(3): 341–359, 2015.

Symans M.D, Kelly S.W., Fuzzy logic control of bridge structures using intelligent semiactive seismic isolation systems, Earthquake Engineering and Structural Dynamics, 28(1): 37–60, 1999.

Eberhart R.C., Kennedy J., A new optimizer using particle swarm theory, Proceedings of the Sixth International Symposium on Micro Machine and Human Science, pp. 39–42, 1995.

Farshidianfar A., Saghafi A., Kalami S.M., Saghafi I., Active vibration isolation of machinery and sensitive equipment using H1 control criterion and particle swarm optimization method, Meccanica, 47(2): 437–453, 2012.

Coello Coello C.A., Lechuga M.S., MOPSO: A proposal for multiple objective particle swarm optimization, Proceedings of the 2002 Congress on Evolutionary Computation, vol. 2, pp. 1051–1056, 2002, doi: 10.1109/CEC.2002.1004388.

Shi Y., Eberhart R., A modified particle swarm optimizer, IEEE World Congress on Computational Intelligence, pp. 69–73, 1998.

Deb K., Pratap A., Agarwal S., Meyarivan T., A fast and elitist multiobjective genetic algorithm: NSGA-II, IEEE Transactions on Evolutionary Computation, 6(2): 182–197, 2002.

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, pp. 41–49, 1987.




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