Repository logo
  • Research Outputs
  • Researchers
  • Schools
    Felizberta Lo Padilla Tong School of Social SciencesIp Ying To Lee Yu Yee School of Humanities and LanguagesRita Tong Liu School of Business and Hospitality ManagementS.K. Yee School of Health SciencesYam Pak Charitable Foundation School of Computing and Information Sciences
  • Help
Repository logo
  1. Home
  2. Computing and Information Sciences
  3. CIS Publication
  4. A float-encoded genetic algorithm technique for integrated optimization of piezoelectric actuator and sensor placement and feedback gains
 
  • Details

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

Author(s)
Leung, Andrew Yee Tak  
Author(s)
Zhang, H.
Lennox, B.
Goulding, P. R.
Date Issued
2000
Publisher
IOP Publishing Ltd
Journal
Smart Materials and Structures
Volume
9
Issue
4
Start page
552
End page
557
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.
URI
https://repository.sfu.edu.hk/handle/sfu/3047
DOI
10.1088/0964-1726/9/4/319
SFU Affiliated Publication
No
Availability at SFU Library

No database links found.

Responsible Use of E‑Resources | Privacy Policy | Disclaimer
© SFU Library. All Rights Reserved.
SFU Library