A modified shuffled frog-leaping algorithm-based fuzzy controller for magnetorheological damper-building system

Lin, Xiufang; Chen, Shumei

doi:10.1504/ijcat.2016.075514

Cited by 5 publications

(4 citation statements)

References 20 publications

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“…Besides, assuming that y ( t ) = [X·· a ( t ) T , X·( t ) T , X ( t ) T ] T is the output vector of the system, where X··bolda( t ) is the absolute acceleration, then the output equation is defined as (Lin and Chen, 2016) where …”

Section: Numerical Examplementioning

confidence: 99%

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A shuffled frog-leaping algorithm based mixed-sensitivity H∞ control of a seismically excited structural building using MR dampers

Lin¹,

Chen

Huang

2017

Journal of Vibration and Control

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An intelligent robust controller, which combines a shuffled frog-leaping algorithm (SFLA) and an H∞ control strategy, is designed for a semi-active control system with magnetorheological (MR) dampers to reduce seismic responses of structures. Generally, the performance of mixed-sensitivity H∞ (MSH) control highly depends on expert experience in selecting the parameters of the weighting functions. In this study, as a recently-developed heuristic approach, a multi-objective SFLA with constraints is adopted to search for the optimal weighting functions. In the proposed semi-active control, firstly, based on the Bouc–Wen model, the forward dynamic characteristics of the MR damper are investigated through a series of tensile and compression experiments. Secondly, the MR damper inverse model is developed with an adaptive-network-based fuzzy inference system (ANFIS) technique. Finally, the SFLA-optimized MSH control approach integrated with the ANFIS inverse model is used to suppress the structural vibration. The simulation results for a three-story building model equipped with an MR damper verify that the proposed semi-active control method outperforms fuzzy control and two passive control methods. Besides, with the proposed strategy, the changes in structural parameters and earthquake excitations can be satisfactorily dealt with.

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Section: Numerical Examplementioning

confidence: 99%

“…The accuracy and effectiveness of the SFLA-optimized PV model are well validated by both simulation and experimental results. Lin and Chen (2016) adopted a modified SFLA to optimize several parameters and fuzzy rules of a fuzzy logic controller to suppress the structural vibration. Yi et al.…”

Section: Introductionmentioning

confidence: 99%

A shuffled frog-leaping algorithm based mixed-sensitivity H∞ control of a seismically excited structural building using MR dampers

Lin¹,

Chen

Huang

2017

Journal of Vibration and Control

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“…To the best of our knowledge, this problem has not been studied before. Noted that although SFLA was also investigated in our previous study, 39 this study proposes a hybrid inverse modeling strategy for a MR damper, while Lin and Chen 39 proposed a hybrid control strategy for reducing the seismic responses of a structural building with MR dampers. In this study, for selecting the optimum parameters for SFLA, two-way analysis of variance (ANOVA) is employed to study the influences of the parameters for SFLA on the best solutions.…”

Section: Introductionmentioning

confidence: 99%

“…The results showed that SFLA was faster and more accurate in comparison with other EAs including PSO, GA, differential evolution, and simulated annealing. Besides, in our previous study, 39 an intelligent control strategy integrating modified shuffled frog-leaping algorithm (MSFLA) and fuzzy logic controller (FLC) was proposed to mitigate the seismic vibration of structures installed with MR dampers. The MSFLA was used to adaptively optimize the FLC parameters.…”

Section: Introductionmentioning

confidence: 99%

Optimal inverse magnetorheological damper modeling using shuffled frog-leaping algorithm–based adaptive neuro-fuzzy inference system approach

Lin

Chen

2016

Advances in Mechanical Engineering

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Magnetorheological dampers have become prominent semi-active control devices for vibration mitigation of structures which are subjected to severe loads. However, the damping force cannot be controlled directly due to the inherent nonlinear characteristics of the magnetorheological dampers. Therefore, for fully exploiting the capabilities of the magnetorheological dampers, one of the challenging aspects is to develop an accurate inverse model which can appropriately predict the input voltage to control the damping force. In this article, a hybrid modeling strategy combining shuffled frogleaping algorithm and adaptive-network-based fuzzy inference system is proposed to model the inverse dynamic characteristics of the magnetorheological dampers for improving the modeling accuracy. The shuffled frog-leaping algorithm is employed to optimize the premise parameters of the adaptive-network-based fuzzy inference system while the consequent parameters are tuned by a least square estimation method, here known as shuffled frog-leaping algorithm-based adaptive-network-based fuzzy inference system approach. To evaluate the effectiveness of the proposed approach, the inverse modeling results based on the shuffled frog-leaping algorithm-based adaptive-network-based fuzzy inference system approach are compared with those based on the adaptive-network-based fuzzy inference system and genetic algorithm-based adaptive-network-based fuzzy inference system approaches. Analysis of variance test is carried out to statistically compare the performance of the proposed methods and the results demonstrate that the shuffled frogleaping algorithm-based adaptive-network-based fuzzy inference system strategy outperforms the other two methods in terms of modeling (training) accuracy and checking accuracy.

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Optimization Algorithms and Applications

Zhang

et al. 2021

Application of Soft Computing, Machine Learning, Deep Learning and Optimizations in Geoengineering and Geoscience

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A modified shuffled frog-leaping algorithm-based fuzzy controller for magnetorheological damper-building system

Cited by 5 publications

References 20 publications

A shuffled frog-leaping algorithm based mixed-sensitivity H∞ control of a seismically excited structural building using MR dampers

A shuffled frog-leaping algorithm based mixed-sensitivity H∞ control of a seismically excited structural building using MR dampers

Optimal inverse magnetorheological damper modeling using shuffled frog-leaping algorithm–based adaptive neuro-fuzzy inference system approach

Optimization Algorithms and Applications

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