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G. Foutsitzi¹, C. Gogos¹, G.E. Stavroulakis² and N.A. Antoniadis³

¹Department of Accounting and Finance, Technological Educational Institution of Epirus, Preveza, Greece
²Institute of Computational Mechanics and Optimization, Department of Production Engineering and Management, Technical University of Crete, Chania, Greece
³Department of Informatics Engineering, Technological Educational Institute of Epirus, Kostakioi, Arta, Greece

doi:10.4203/ccp.106.222

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G. Foutsitzi, C. Gogos, G.E. Stavroulakis, N.A. Antoniadis, "Optimization of Piezoelectric Patches in Smart Structures using Multi-Objective Genetic Algorithms", in , (Editors), "Proceedings of the Twelfth International Conference on Computational Structures Technology", Civil-Comp Press, Stirlingshire, UK, Paper 222, 2014. doi:10.4203/ccp.106.222

Keywords: multi-objective genetic algorithms, active vibration control, smart structures, actuator placement, NSGAII..

Summary

In this paper multi-objective genetic algorithms have been used to search for the optimal placement of the piezoelectric sensors and actuators bonded on smart beams. A finite element method based on Timoshenko beam theory is used accounting for the piezoelectric layers. The discrete optimal sensor and actuator location problem is formulated in the framework of a zero-one optimization problem with multi-objective functions as performance measures. A cantilever beam example is considered to demonstrate the performance of the selected multi-objective genetic algorithm which is NSGAII. It is shown that the proposed algorithm is effective in developing optimal Pareto front curves for optimal placement and number of actuators and sensors such that the performance on dynamic responses is also satisfied.

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Front Page Browse CCP CSETS CTR IJRT Other Authors Search Purchase Guide FAQ Contact us	Civil-Comp Proceedings ISSN 1759-3433 CCP: 106 PROCEEDINGS OF THE TWELFTH INTERNATIONAL CONFERENCE ON COMPUTATIONAL STRUCTURES TECHNOLOGY Edited by: Paper 222 Optimization of Piezoelectric Patches in Smart Structures using Multi-Objective Genetic Algorithms G. Foutsitzi¹, C. Gogos¹, G.E. Stavroulakis² and N.A. Antoniadis³ ¹Department of Accounting and Finance, Technological Educational Institution of Epirus, Preveza, Greece ²Institute of Computational Mechanics and Optimization, Department of Production Engineering and Management, Technical University of Crete, Chania, Greece ³Department of Informatics Engineering, Technological Educational Institute of Epirus, Kostakioi, Arta, Greece doi:10.4203/ccp.106.222 purchase the full-text of this paper Full Bibliographic Reference for this paper G. Foutsitzi, C. Gogos, G.E. Stavroulakis, N.A. Antoniadis, "Optimization of Piezoelectric Patches in Smart Structures using Multi-Objective Genetic Algorithms", in , (Editors), "Proceedings of the Twelfth International Conference on Computational Structures Technology", Civil-Comp Press, Stirlingshire, UK, Paper 222, 2014. doi:10.4203/ccp.106.222 Keywords: multi-objective genetic algorithms, active vibration control, smart structures, actuator placement, NSGAII.. Summary In this paper multi-objective genetic algorithms have been used to search for the optimal placement of the piezoelectric sensors and actuators bonded on smart beams. A finite element method based on Timoshenko beam theory is used accounting for the piezoelectric layers. The discrete optimal sensor and actuator location problem is formulated in the framework of a zero-one optimization problem with multi-objective functions as performance measures. A cantilever beam example is considered to demonstrate the performance of the selected multi-objective genetic algorithm which is NSGAII. It is shown that the proposed algorithm is effective in developing optimal Pareto front curves for optimal placement and number of actuators and sensors such that the performance on dynamic responses is also satisfied. purchase the full-text of this paper (price £20) go to the previous paper go to the next paper return to the table of contents return to the book description purchase this book (price £65 +P&P)
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