A float-encoded genetic algorithm technique for integrated optimization of piezoelectric actuator and sensor placement and feedback gains

ZHANG, Hongwei, LENNOX, Barry, GOULDING, Peter R. and LEUNG, Andrew Y. T. (2000). A float-encoded genetic algorithm technique for integrated optimization of piezoelectric actuator and sensor placement and feedback gains. Smart Materials and Structures, 9 (4), 552-557.

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Abstract

This paper presents a novel float-encoded genetic algorithm and applies it to the optimal control of flexible smart structures bonded with piezoelectric actuators and sensors. A performance function is initially developed, based on the maximization of dissipation energy due to a control action. Then, according to this characteristic, a float-encoded genetic algorithm is presented which is capable of solving this optimization problem reliably and efficiently. The optimization algorithm that is developed for the control of flexible systems allows an integrated determination of actuator and sensor locations and feedback gains. The paper demonstrates the suitability of the proposed technique through its application to three standard benchmark test functions and a collocated cantilever beam.

Item Type:	Article
Research Institute, Centre or Group - Does NOT include content added after October 2018:	Materials and Engineering Research Institute > Modelling Research Centre > Microsystems and Machine Vision Laboratory
Identification Number:	https://doi.org/10.1088/0964-1726/9/4/319
Page Range:	552-557
Depositing User:	Margaret Boot
Date Deposited:	21 Apr 2017 15:54
Last Modified:	18 Mar 2021 17:31
URI:	https://shura.shu.ac.uk/id/eprint/15022

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