Multi-objective control optimization of isolated bridge using replicator controller and NSGA-II

Earthquakes can cause significant damage to constructed structures, leading engineers to design systems that effectively reduce damage and improve real-time vibration control. While base isolation is a commonly used passive method for seismic protection in highway structures, it has limitations such...

Full description

Bibliographic Details
Main Authors: Zahrasadat Momeni, Ashotush Bagchi
Format: Article
Language:English
Published: Elsevier 2023-09-01
Series:Heliyon
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S2405844023065891
_version_ 1797669924190027776
author Zahrasadat Momeni
Ashotush Bagchi
author_facet Zahrasadat Momeni
Ashotush Bagchi
author_sort Zahrasadat Momeni
collection DOAJ
description Earthquakes can cause significant damage to constructed structures, leading engineers to design systems that effectively reduce damage and improve real-time vibration control. While base isolation is a commonly used passive method for seismic protection in highway structures, it has limitations such as a lack of immediate adaptation, constrained power dissipation capacity, and poor performance during earthquakes. To address the limitations of passive base isolation bearings, a hybrid control system that includes semi-active MR dampers is being introduced into isolated highway bridge structures. The aim is to enhance vibration reduction and improve overall performance. One of the major challenges in implementing this technology is developing appropriate control algorithms to handle the nonlinear behavior of semi-active devices. This paper proposes an adaptive data-driven control algorithm, informed by evolutionary game theory and a multi-objective optimization process, to optimize the distribution of voltage to semi-active MR dampers based on measurements of the damper's response to input signals. The algorithm is designed to provide optimal seismic protection. The performance of the replicator dynamics in the control system depends on three critical parameters: total population, which represents the total available resources or the sum of actuator forces; growth rate, which is the rate at which resources are distributed among control devices; and the fictitious fitness function, which regulates power consumption. Previous studies used sensitivity analysis to ascertain the best values for population size and growth rate, a time-consuming and unreliable process. This study aims to improve the performance of the system by solving a multi-objective problem. The proposed approach integrates a control algorithm with a multi-objective optimization algorithm, namely NSGA-II, to find Pareto optimal values for all parameters of the replicator dynamics. These parameters include total population, growth rate, and the fictitious function, with the aim of ensuring sustainability. By considering multiple objectives simultaneously, the proposed approach can provide a more comprehensive and effective solution for the bridge control problem. The effectiveness of this proposed approach is demonstrated through sample results Utilizing a case study centered around the Southern California Interstate 91/5 Overcrossing Highway Bridge, which is exposed to seismic activities.
first_indexed 2024-03-11T20:52:03Z
format Article
id doaj.art-b6e0df5572ce4a9d831479a8a3998ca2
institution Directory Open Access Journal
issn 2405-8440
language English
last_indexed 2024-03-11T20:52:03Z
publishDate 2023-09-01
publisher Elsevier
record_format Article
series Heliyon
spelling doaj.art-b6e0df5572ce4a9d831479a8a3998ca22023-10-01T05:59:24ZengElsevierHeliyon2405-84402023-09-0199e19381Multi-objective control optimization of isolated bridge using replicator controller and NSGA-IIZahrasadat Momeni0Ashotush Bagchi1Corresponding author.; Building Civil and Environmental Engineering Department, Gina Cody School of Engineering and Computer Science, Concordia University, Montreal, Quebec, H3G 1M8, CanadaCorresponding author.; Building Civil and Environmental Engineering Department, Gina Cody School of Engineering and Computer Science, Concordia University, Montreal, Quebec, H3G 1M8, CanadaEarthquakes can cause significant damage to constructed structures, leading engineers to design systems that effectively reduce damage and improve real-time vibration control. While base isolation is a commonly used passive method for seismic protection in highway structures, it has limitations such as a lack of immediate adaptation, constrained power dissipation capacity, and poor performance during earthquakes. To address the limitations of passive base isolation bearings, a hybrid control system that includes semi-active MR dampers is being introduced into isolated highway bridge structures. The aim is to enhance vibration reduction and improve overall performance. One of the major challenges in implementing this technology is developing appropriate control algorithms to handle the nonlinear behavior of semi-active devices. This paper proposes an adaptive data-driven control algorithm, informed by evolutionary game theory and a multi-objective optimization process, to optimize the distribution of voltage to semi-active MR dampers based on measurements of the damper's response to input signals. The algorithm is designed to provide optimal seismic protection. The performance of the replicator dynamics in the control system depends on three critical parameters: total population, which represents the total available resources or the sum of actuator forces; growth rate, which is the rate at which resources are distributed among control devices; and the fictitious fitness function, which regulates power consumption. Previous studies used sensitivity analysis to ascertain the best values for population size and growth rate, a time-consuming and unreliable process. This study aims to improve the performance of the system by solving a multi-objective problem. The proposed approach integrates a control algorithm with a multi-objective optimization algorithm, namely NSGA-II, to find Pareto optimal values for all parameters of the replicator dynamics. These parameters include total population, growth rate, and the fictitious function, with the aim of ensuring sustainability. By considering multiple objectives simultaneously, the proposed approach can provide a more comprehensive and effective solution for the bridge control problem. The effectiveness of this proposed approach is demonstrated through sample results Utilizing a case study centered around the Southern California Interstate 91/5 Overcrossing Highway Bridge, which is exposed to seismic activities.http://www.sciencedirect.com/science/article/pii/S2405844023065891Smart structuresOptimal vibration controlReplicator dynamicsEarthquake engineeringSemi-active control
spellingShingle Zahrasadat Momeni
Ashotush Bagchi
Multi-objective control optimization of isolated bridge using replicator controller and NSGA-II
Heliyon
Smart structures
Optimal vibration control
Replicator dynamics
Earthquake engineering
Semi-active control
title Multi-objective control optimization of isolated bridge using replicator controller and NSGA-II
title_full Multi-objective control optimization of isolated bridge using replicator controller and NSGA-II
title_fullStr Multi-objective control optimization of isolated bridge using replicator controller and NSGA-II
title_full_unstemmed Multi-objective control optimization of isolated bridge using replicator controller and NSGA-II
title_short Multi-objective control optimization of isolated bridge using replicator controller and NSGA-II
title_sort multi objective control optimization of isolated bridge using replicator controller and nsga ii
topic Smart structures
Optimal vibration control
Replicator dynamics
Earthquake engineering
Semi-active control
url http://www.sciencedirect.com/science/article/pii/S2405844023065891
work_keys_str_mv AT zahrasadatmomeni multiobjectivecontroloptimizationofisolatedbridgeusingreplicatorcontrollerandnsgaii
AT ashotushbagchi multiobjectivecontroloptimizationofisolatedbridgeusingreplicatorcontrollerandnsgaii