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Fuzzy control optimized by a Multi-Objective Particle Swarm Optimization algorithm for vibration suppression of smart structures

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Abstract

Smart structures include elements of active, passive or hybrid control. In this paper, a new Multi-Objective Particle Swarm Optimization (MOPSO), with a different velocity equation, for the calculation of the free parameters in active control systems is proposed and tested. A fuzzy control system is considered. Fuzzy control is a suitable tool for the systematic development of nonlinear active control strategies and can be fine tuned if no experience exists or if one designs more complicated control schemes. The usage of MOPSO with a combination of continuous and discrete variables for the optimal design of the controller is proposed. Numerical applications on smart piezoelastic beams are presented.

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Authors and Affiliations

  1. Department of Production Engineering and Management, Technical University of Crete, University Campus, 73100, Chania, Crete, Greece

    Magdalene Marinaki, Yannis Marinakis & Georgios E. Stavroulakis

  2. Institute of Applied Mechanics, Carolo Wilhelmina Technical University, Braunschweig, Germany

    Georgios E. Stavroulakis

Authors
  1. Magdalene Marinaki
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  2. Yannis Marinakis
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  3. Georgios E. Stavroulakis
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Correspondence to Georgios E. Stavroulakis.

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Marinaki, M., Marinakis, Y. & Stavroulakis, G.E. Fuzzy control optimized by a Multi-Objective Particle Swarm Optimization algorithm for vibration suppression of smart structures. Struct Multidisc Optim 43, 29–42 (2011). https://doi.org/10.1007/s00158-010-0552-4

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