Simple adaptive control to attenuate bridge’s seismic responses considering parametric variations

Soares, Rachel W.; Barroso, Luciana R.; Al-Fahdawi, Omar A.S.

doi:10.1177/1369433219866293

Cited by 9 publications

(5 citation statements)

References 37 publications

(38 reference statements)

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“…This research investigates the efficacy of both controllers in addressing parametric uncertainties when exposed to seismic excitation under both far-field and near-field conditions [12]. Furthermore, Several investigations have been successfully conducted on the performance of bridges [11,68,69] and structural systems [64,[70][71][72][73][74][75]. Despite the significant level of interest surrounding the topic, several gaps and deficiencies persist within the domain of adaptive controllers.…”

Section: Introductionmentioning

confidence: 99%

Design of a novel intelligent adaptive fractional-order proportional-integral-derivative controller for mitigation of seismic vibrations of a building equipped with an active tuned mass damper

Jafarzadeh,

Sabetahd,

Mousavi Ghasemi

et al. 2024

Smart Mater. Struct.

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The primary objective of this study is to introduce a novel adaptive fractional order proportional–integral–derivative (FOPID) controller. The adaptive FOPID controller’s parameters are dynamically adjusted in real-time using five distinct multilayer perceptron neural networks. The extended Kalman filter (EKF) is employed to facilitate the parameter-tuning process. A multilayer perceptron neural network, trained using the error Backpropagation algorithm, is employed to identify the structural system and estimate the plant. The real-time estimated Jacobian is applied to the controller to control the model. The stability and robustness of the adaptive interval type-2 fuzzy neural networks controller are enhanced by utilizing the EKF and the feedback error learning strategy for compensator tuning. This improvement increases resilience against estimation errors, seismic disturbances, and unknown nonlinear functions. The primary objective is to address the challenges posed by maximum displacement, acceleration, and drift, as well as the uncertainties arising from variations in stiffness and mass. In order to validate the reliability of the proposed controller, the performance investigation is carried out on an 11-story building equipped with an active tuned mass damper under far and near-field earthquakes. Numerical findings show the remarkable effectiveness of the proposed controllers compared to their predecessors. In addition, it is revealed that the inclusion of the adaptive interval type-2 fuzzy neural networks compensator has increased the performance of the proposed controller and shows significant capabilities in reducing the seismic responses of structures during severe earthquake events.

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Section: Introductionmentioning

confidence: 99%

Design of a novel intelligent adaptive fractional-order proportional-integral-derivative controller for mitigation of seismic vibrations of a building equipped with an active tuned mass damper

Jafarzadeh,

Sabetahd,

Mousavi Ghasemi

et al. 2024

Smart Mater. Struct.

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“…Te primary objective of this study was to minimize the isolation system's displacement, assuming that the superstructure's acceleration did not rise for far-feld and nearfeld earthquake events [90]. Besides, a simple adaptive controller (SAC), which has a good performance, was examined by Soares et al for attenuating the bridge's seismic responses against parametric uncertainties [100]. In another study by Soares et al, the neurofuzzy controller was combined with SAC and applied to the cable-stayed bridge subjected to central US seismic excitations, and acceptable results were presented [10].…”

Section: Introductionmentioning

confidence: 99%

Online Adaptive Neurochaotic Fuzzy Controller Design to Reduce the Seismic Response of Buildings Equipped with Active Tuned Mass Damper System

Jafarzadeh,

Mousavi Ghasemi,

Zahrai

et al. 2023

International Journal of Intelligent Systems

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This paper presents a novel adaptive neurochaotic fuzzy control system based on type-2 fuzzy systems to reduce seismic responses in multistory structures with active tuned mass dampers under near-field and far-field earthquakes. In this proposed control system, the whole parameters of the plant are assumed to be completely unknown, the structural model is estimated using a multilayer perceptron neural network, and the system’s Jacobian is extracted. The online estimation model is used, and the controller parameters are adaptively trained using the extended Kalman filter and error back-propagation method. Subsequently, the control force is applied to the active tuned mass damper, and the control objectives are met. The adaptive controller does not require initial settings, and a fractional-order proportional-integral-derivative controller is added to maximize stability and robustness against seismic vibration. A simple adaptive controller optimized by a particle swarm is also presented as an innovation. Comparing the performance of the improved simple adaptive controller and adaptive neurochaotic fuzzy controller, the proposed controllers appear more efficient and accurate. However, the superiority of the novel adaptive neurochaotic fuzzy over the improved simple adaptive controller in reducing maximum displacement, acceleration, drift, and base shear while maintaining acceptable performance under parametric uncertainties and seismic conditions is substantial.

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“…Many existing studies in the broader literature [76,[95][96][97][98][99][100][101] have successfully implemented adaptive control schemes on structures. Some controllers, such as the Simple Adaptive Controller (SAC), recently studied by Soares et al [18,102], can be used to reduce the seismic response of structures under seismic excitations. ere is no research in the existing literature on the reduction of seismic responses in an ATMD-equipped structure using an adaptive type-2 neural-fuzzy controller.…”

Section: Introductionmentioning

confidence: 99%

Response Attenuation of a Structure Equipped with ATMD under Seismic Excitations Using Methods of Online Simple Adaptive Controller and Online Adaptive Type-2 Neural-Fuzzy Controller

Sabetahd

Ghasemi

Poursorkhabi

et al. 2022

Computational Intelligence and Neuroscience

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The present study aims to design a robust adaptive controller employed in the active tuned mass damper (ATMD) system to overcome undesirable vibrations in multistory buildings under seismic excitations. We propose a novel adaptive type-2 neural-fuzzy controller (AT2NF). All system parameters are taken as unknowns. The MLP neural network is used to extract the Jacobian and estimate the structural model; then, the estimated model is applied to the controller online. To tune the control force applied to the ATMD and achieve the control targets, the controller parameters are adaptively trained using the extended Kalman Filter (EKF) and the error back-propagation algorithm. A PID controller is also included in this method to increase the stability and robustness of the adaptive type-2 neural-fuzzy controller against seismic vibrations. An online simple adaptive controller (OSAC) is studied to demonstrate the suggested controller’s superiority. The OSAC is based on adaptive control of the implicit reference model. In this proposed method, the EKF is used to tune the controller parameters online as a novel feature. The uncertainty associated with identifying the mechanical properties of structures, such as mass and stiffness, is one of the primary challenges in the real-time control of structures. This paper investigates how both controllers cope with parametric uncertainties under far-field and near-field seismic excitation. According to numerical results, the AT2NF controller outperforms OSAC in minimizing the dynamic responses of the structure during an earthquake and accomplishing control objectives when the structure’s characteristics change.

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Simple adaptive control to attenuate bridge’s seismic responses considering parametric variations

Cited by 9 publications

References 37 publications

Design of a novel intelligent adaptive fractional-order proportional-integral-derivative controller for mitigation of seismic vibrations of a building equipped with an active tuned mass damper

Design of a novel intelligent adaptive fractional-order proportional-integral-derivative controller for mitigation of seismic vibrations of a building equipped with an active tuned mass damper

Online Adaptive Neurochaotic Fuzzy Controller Design to Reduce the Seismic Response of Buildings Equipped with Active Tuned Mass Damper System

Response Attenuation of a Structure Equipped with ATMD under Seismic Excitations Using Methods of Online Simple Adaptive Controller and Online Adaptive Type-2 Neural-Fuzzy Controller

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