Online self‐tuning mechanism for direct adaptive control of tall building

Hosseini, Amin; Taghikhany, Touraj

doi:10.1002/acs.2850

Cited by 8 publications

(8 citation statements)

References 50 publications

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“…John von Neumann and Oskar Morgenstern 107 studied human behavior and strategic decisions using mathematical theory and brought forth Game Theory, 39 which was continued by Nash 108 by presenting the concept of Nash Equilibrium (NE). The NE is considered the focal idea of GT.…”

Section: Rd-based Controllermentioning

confidence: 99%

“…36,37 Likewise, these controllers have fixed adjusting parameters, making them unalterable, innately less safe, and less robust controllers with uncertain stability and convergence brought about by unmodeled dynamics. 38,39 As civil structures are highly complicated multi-degree-of-freedom systems, it is dreadfully challenging to find a precise numerical model representing their actual behavior. 40,41 Additionally, these linear and nonlinear MBC schemes often require high computational exertion toward identifying and modeling systems instead of designing controllers.…”

Section: Introductionmentioning

confidence: 99%

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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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Section: Rd-based Controllermentioning

confidence: 99%

Section: Introductionmentioning

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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“…Due to the described advantages, SAC has been employed in different engineering systems (Al-Fahdawi et al, 2019; Amini et al, 2018; Bar-Kana and Kaufman, 1984; Bar-Kana et al, 1983; Bitaraf et al, 2010, 2012; Bitaraf and Hurlebaus, 2013; Hosseini and Taghikhany, 2018; Hosseini et al, 2018; Javanbakht and Amini, 2016) as well as civil infrastructures. Bitaraf et al used the SAC controller to protect building structures under seismic action by MR dampers (Bitaraf and Hurlebaus, 2013; Bitaraf et al, 2010, 2012).…”

Section: Introductionmentioning

confidence: 99%

Optimal tuned direct adaptive controller for seismic protecting of structures

Hosseini

Taghikhany

Jahangiri

2021

Journal of Intelligent Material Systems and Structures

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In the past few years, many studies have proved the efficiency of Simple Adaptive Control (SAC) in mitigating earthquakes’ damages to building structures. Nevertheless, the weighting matrices of this controller should be selected after a large number of sensitivity analyses. This step is time-consuming and it will not necessarily yield a controller with optimum performance. In the current study, an innovative method is introduced to tuning the SAC’s weighting matrices, which dispenses with excessive sensitivity analysis. In this regard, we try to define an optimization problem using intelligent evolutionary algorithm and utilized control indices in an objective function. The efficiency of the introduced method is investigated in 6-story building structure equipped with magnetorheological dampers under different seismic actions with and without uncertainty in the model of the proposed structure. The results indicate that the controller designed by the introduced method has a desirable performance under different conditions of uncertainty in the model. Furthermore, it improves the seismic performance of structure as compared to controllers designed through sensitivity analysis.

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“…SAC is proven to guarantee perfect tracking asymptotically, and successfully avoids the use of identifiers and observers. It has been applied successfully to mitigate excessive response of large structures in many studies (Barkana and Kaufman, 1993;Bitaraf et al, 2010Bitaraf et al, , 2012Bitaraf and Hurlebaus, 2013;Amini, 2015;Javanbakht, 2016;Al-Fahdawi et al, 2018;Hosseini and Taghikhany, 2018;Soares et al, 2018). In this particular study, SAC is implemented to follow a model reference of the bridge considering original design parameters and controlled by LQR with full-feedback.…”

Section: Introductionmentioning

confidence: 99%

Adaptive control for response attenuation of seismically excited cable-stayed bridges

Soares

Barroso

Al-Fahdawi

2019

Journal of Vibration and Control

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Estimation of bridge’s parameters is bound to give rise to a certain amount of inaccuracy. Given the size of cable-stayed bridge structures, any percentage of error can lead to estimated stiffness, mass, and damping that differ greatly from the actual structural parameters. During their service life, bridge structures experience cracking, temperature variations, localized damage, and deterioration, which result in parametric variation. Adaptive control strategies can be a good alternative to control bridges subjected to seismic excitation, as they present robustness when in face of parametric variation. In this study, a semi-active adaptive control approach is proposed for mitigation of seismic responses of cable-stayed bridges. The approach is based on the simple adaptive control, which is a direct model reference adaptive control strategy for multiple-input–multiple-output systems, proven to guarantee perfect tracking asymptotically, and successfully avoid the use of observers. The proposed adaptive scheme adopts the nominal bridge controlled by the linear–quadratic regulator with full-feedback as a model reference. The adaptive technique is implemented to control semi-active magnetorheological damper devices, considering realistic implementation and design. The scheme’s ability in reducing seismic response of a cable-stayed bridge subjected to three earthquake records with different angles of incidence is evaluated and its performance is compared to classical control solutions. In order to evaluate robustness of the control scheme proposed, two different parametric changes are introduced. The proposed adaptive scheme gives the least average variation in performance for all the different parametric variations considered. The control solution presents increased robustness when compared to passive and semi-active resettable controllers; it requires a small number of nodes to be monitored and avoids complicated reconstruction of states.

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Online self‐tuning mechanism for direct adaptive control of tall building

Cited by 8 publications

References 50 publications

Research developments in adaptive intelligent vibration control of smart civil structures

Research developments in adaptive intelligent vibration control of smart civil structures

Optimal tuned direct adaptive controller for seismic protecting of structures

Adaptive control for response attenuation of seismically excited cable-stayed bridges

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