Evolutionary-Based BEL Controller Applied to a Magneto-Rheological Structural System

Braz-César, Manuel; Coelho, João Paulo; Gonçalves, José

doi:10.3390/act7020029

Cited by 7 publications

(8 citation statements)

References 35 publications

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“…The use of PSO for computing the parameters of a building vibration BELBIC controller has already been explored in one of the authors previous works [17]. In the referred work, it was shown that this approach led to a set of controller parameters, that were able to outperform an empirical parameters selection method, based on trial-and-error.…”

Section: Results Discussionmentioning

confidence: 99%

“…Since then, this control strategy has been applied in a myriad of distinct engineering problems. For example in [16,17] a BEL controller performance was applied to semi-active vibration control and [34] have used BELBIC to control the voltage tracking in a boost converter. In [35] a sliding mode control-based on BELBIC was tested over robotic manipulators.…”

Section: The Bel-based Control Systemmentioning

confidence: 99%

“…The two main problems with the use of BELBIC as a control strategy is, on the one hand, its very large number of parameters and, on the other, the overall controller sensitivity to the value of those parameters. In [17] this issue was tackled by means of an off-line training procedure where the BELBIC controller parameters were obtained by an evolutionary search algorithm. The article has shown that the vibration of one degree-of-freedom building under an 1D base disturbance was largely improved by this method when compared to simple ad-hoc controller tuning.…”

Section: Introductionmentioning

confidence: 99%

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Semi-Active Vibration Control of a Non-Collocated Civil Structure Using Evolutionary-Based BELBIC

2019

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A buildings resilience to seismic activity can be increased by providing ways for the structure to dynamically counteract the effect of the Earth’s crust movements. This ability is fundamental in certain regions of the globe, where earthquakes are more frequent, and can be achieved using different strategies. State-of-the-art anti-seismic buildings have, embedded on their structure, mostly passive actuators such as base isolation, Tuned Mass Dampers (TMD) and viscous dampers that can be used to reduce the effect of seismic or even wind induced vibrations. The main disadvantage of this type of building vibration reduction strategies concerns their inability to adapt their properties in accordance to both the excitation signal or structural behaviour. This adaption capability can be promoted by adding to the building active type actuators operating under a closed-loop. However, these systems are substantially larger than passive type solutions and require a considerable amount of energy that may not be available during a severe earthquake due to power grid failure. An intermediate solution between these two extremes is the introduction of semi-active actuators such as magneto–rheological dampers. The inclusion of magneto–rheological actuators is among one of the most promising semi-active techniques. However, the overall performance of this strategy depends on several aspects such as the actuators number and location within the structure and the vibration sensors network. It can be the case where the installation leads to a non-collocated system which presents additional challenges to control. This paper proposes to tackle the problem of controlling the vibration of a non-collocated three-storey building by means of a brain–emotional controller tuned using an evolutionary algorithm. This controller will be used to adjust the stiffness coefficient of a magneto–rheological actuator such that the building’s frame oscillation under earthquake excitation, is mitigated. The obtained results suggest that, using this control strategy, it is possible to reduce the building vibration to secure levels.

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Section: Results Discussionmentioning

confidence: 99%

Section: The Bel-based Control Systemmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Semi-Active Vibration Control of a Non-Collocated Civil Structure Using Evolutionary-Based BELBIC

2019

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“…45 BELBIC Applications. Braz César et al 82 developed a BELBIC combined with PSO algorithms for the seismic vibration control of single storey building subjected to seismic loading and the actuating mechanism is incorporated through MR damper. Their proposed PSO optimized controller has shown higher performance in achieving control objectives.…”

Section: Brain Emotional Learning-based Intelligent Controllermentioning

confidence: 99%

“…Notably, the PSO tuning enhanced the controller's efficiency by almost 20%, far better than the traditional empirically tune controller. Braz César et al 82 developed PSO optimized BELBIC for the single-storey building structure subjected to seismic loading, and the actuating mechanism is supported by MR damper. In addition, their proposed PSO optimized controller has shown higher performance in achieving control objectives.…”

Section: Meta-heuristic Algorithms-based Hybrid Aic Controllersmentioning

confidence: 99%

Research developments in adaptive intelligent vibration control of smart civil structures

Saeed

Sun

Elias

2021

Journal of Low Frequency Noise, Vibration and Active Control

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Control algorithms are the most critical aspects in the successful control of civil structures subjected to earthquake and wind forces. In recent years, adaptive intelligent control algorithms are emerging as an acceptable substitute method to conventional model-based control algorithms. These algorithms mainly work on the principles of artificial intelligence (AI) and soft computing (SC) methods that make them highly efficient in controlling highly nonlinear, time-varying, and time-delayed complex civil structures. The current research probes to control algorithms, that this article set forth an inclusive state-of-the-art review of adaptive intelligent control (AIC) algorithms for vibration control of smart civil structures. First, a general introduction to adaptive intelligent control is presented along with its advantages over conventional control algorithms. Second, their classification concerning artificial intelligence and soft computing methods is provided that mainly consists of artificial neural network-based controller, brain emotional learning-based intelligent controller, replicator dynamics-based controller, multi-agent system-based controller, support vector machine-based controller, fuzzy logic control, adaptive neuro-fuzzy inference system-based controller, adaptive filters-base controller, and meta-heuristic algorithms-based hybrid controllers. Third, a brief review of these algorithms with their developments on the theory and applications is provided. Fourth, we demonstrate a summarized overview of the cited literature with a brief trend analysis is presented. Finally, this study presents an overview of these innovative AIC methods that can demonstrate future directions. The contribution of this article is the anticipation of detailed and in-depth discussion into the perspective of AI and SC-based AIC method advances that enabled practical applications in attenuating vibration response of smart civil structures. Moreover, the review demonstrates the computing advantages of AIC over conventional controllers that are important in creating the next generation of smart civil structures.

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BELBIC Based Step-Down Controller Design Using PSO

Coelho

Braz-César

Gonçalves

2021

Communications in Computer and Information Science

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Evolutionary-Based BEL Controller Applied to a Magneto-Rheological Structural System

Cited by 7 publications

References 35 publications

Semi-Active Vibration Control of a Non-Collocated Civil Structure Using Evolutionary-Based BELBIC

Semi-Active Vibration Control of a Non-Collocated Civil Structure Using Evolutionary-Based BELBIC

Research developments in adaptive intelligent vibration control of smart civil structures

BELBIC Based Step-Down Controller Design Using PSO

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