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Actuator Layout Optimization for Adaptive Structures Performing Large Shape Changes

  • Arka P. Reksowardojo
  • Gennaro Senatore
  • Ian F. C. Smith
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10864)

Abstract

Adaptive structures are sensed and actuated to modify internal forces and shape to maintain optimal performance in response to loads. The use of large shape changes as a structural adaptation strategy to counteract the effect of loads has been investigated previously. When large shape changes are employed, structures are designed to change shape as the load changes thus giving the opportunity to homogenize stresses. In this way, the design is not governed by peak loads that occur very rarely. Simulations have shown a significant amount of embodied energy can be reduced with respect to optimized active structures limited to small shape changes and with respect to passive structures. However, in these previous studies, the actuator layout was assigned a-priori.

This paper presents a new method to search for an actuator layout that is optimum to counteract the effect of loads via large shape changes. The objective is to design the actuation system allowing the structure to ‘morph’ into shapes optimized to maximize material utilization for each load case. A combination of simulated annealing and the nonlinear force method is proposed to meet both the actuator placement problem and to determine appropriate actuator commands. A heuristic for near-neighbor generation based on the actuator control efficacy is employed to explore effectively the large search space. Case studies show the proposed method converges to the global optimum for simple configurations and generally produces actuator layouts enabling shape control even with a low number of actuators.

Keywords

Adaptive structures Shape control Actuator layout optimization Nonlinear force method Stochastic search 

Notes

Acknowledgements

The research presented in this paper is supported by the Swiss Government Excellence Scholarship (ESKAS-Nr: 2016.0749).

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Applied Computing and Mechanics Laboratory (IMAC), School of Architecture, Civil and Environmental Engineering (ENAC)Swiss Federal Institute of Technology (EPFL)LausanneSwitzerland

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