Application of simple adaptive control to an MR damper-based control system for seismically excited nonlinear buildings

Javanbakht, Majd; Amini, Fereidoun

doi:10.12989/sss.2016.18.6.1251

Cited by 11 publications

(9 citation statements)

References 24 publications

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“…The PI filter is used to improve the behavior of the online parameter identification and adaptive control approach. It has also been used to create stability in nonlinear systems (Javanbakht and Amini, 2016).…”

Section: Sac Algorithmmentioning

confidence: 99%

“…One of the adaptive controllers, namely SAC method, is introduced and its stability is discussed (Barkana, 2013; Kaufman et al, 1998). This algorithm has been used to control (Javanbakht and Amini, 2016) with the neural network inverse model in the MR damper command voltage (Amini and Javanbakht, 2014), rotational asymmetric structures (Amini et al, 2018), and large space structures (Hu et al, 2018). Therefore, The SAC algorithm is significantly effective in reducing structure vibrations.…”

Section: Introductionmentioning

confidence: 99%

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Online parameter estimation and adaptive control with limited information in structures

Amini

Aghabarari

2021

Journal of Vibration and Control

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An online parameter estimation is important along with the adaptive control, that is, a time-dependent plant. This study uses both online identification and the simple adaptive control algorithm with velocity feedback. The recursive least squares method was used to identify the stiffness and damping parameters of the structure’s stories. Identification was carried out online without initial estimation and only by measuring the structural responses. The limited information regarding sensor measurements, parameter convergence, and the effects of the covariance matrix is examined. The integration of the applied online identification, the appropriate reference model selection in simple adaptive control, and adopting the proportional integral filter was used to limit the structural control response error. Some numerical examples are simulated to verify the ability of the proposed approach. Despite the limited information, the results show that the simultaneous use of online identification with the recursive least squares method and simple adaptive control algorithm improved the overall structural performance.

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Section: Sac Algorithmmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Online parameter estimation and adaptive control with limited information in structures

Amini

Aghabarari

2021

Journal of Vibration and 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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Application of simple adaptive control to an MR damper-based control system for seismically excited nonlinear buildings

Cited by 11 publications

References 24 publications

Online parameter estimation and adaptive control with limited information in structures

Online parameter estimation and adaptive control with limited information in 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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