Semi-active vibration control of smart isolated highway bridge structures using replicator dynamics

Soto, Mariantonieta Gutierrez; Adeli, Hojjat

doi:10.1016/j.engstruct.2019.02.031

Cited by 66 publications

(30 citation statements)

References 58 publications

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“…Let us assume that the dynamical system is linear and time invariant, and it is characterized by the state‐space equation

\overset{boldx}{true} false(t false) = boldAx false(t false) + boldBu false(t false) + boldE w false(t false)

, where

boldx false(t false) \in ℝ^{n}

is the state vector at time t ,

boldu false(t false) \in ℝ^{m}

is the control signal, and w is an external disturbance. The dynamics of a wide variety of active and semi‐active structures can be modeled by this equation 27‐30 . We consider the feedback control strategy

boldu false(t false) = - boldFx false(t false)

, where F is the control matrix.…”

Section: Control Design Problem With Structural Sparsitymentioning

confidence: 99%

Structural sparsity in control design of active and semi‐active systems

Florez

Giraldo

Soto

et al. 2021

Struct Control Health Monit

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Summary Civil building structures equipped with active or semi‐active control devices help mitigate structural damages in the presence of any seismic excitation. These advanced mitigation systems require additional devices such as sensors, actuators, and communication systems that increase issues related to energy consumption, measurement errors, and costs of implementation. In this work, we propose a methodology based on the concept of structural sparsity to induce a sparse pattern in the feedback control system that takes into account prior information on the inherent relationship between the variables of the controller. This methodology can potentially decrease the implementation costs while keeping a suitable performance of the structure when subjected to external disturbances. We show through mathematical analyses and simulation results the benefits of using the proposed methodology in both active and semi‐active systems.

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“…Let us assume that the dynamical system is linear and time invariant, and it is characterized by the state‐space equation

\overset{boldx}{true} false(t false) = boldAx false(t false) + boldBu false(t false) + boldE w false(t false)

, where

boldx false(t false) \in ℝ^{n}

is the state vector at time t ,

boldu false(t false) \in ℝ^{m}

boldu false(t false) = - boldFx false(t false)

, where F is the control matrix.…”

Section: Control Design Problem With Structural Sparsitymentioning

confidence: 99%

Structural sparsity in control design of active and semi‐active systems

Florez

Giraldo

Soto

et al. 2021

Struct Control Health Monit

Self Cite

View full text Add to dashboard Cite

show abstract

“…This method considers bounded real lemma and linear matrix inequalities methods in its implementation, which demonstrated to be robust for structures where active bracing systems and active tuned mass dampers are installed. Active and semiactive vibration control systems using many‐objective control algorithms (Gutierrez Soto & Adeli, 2017a), multiagent replicator controllers (Gutierrez Soto & Adeli, 2017b), neural dynamic optimization model and replicator dynamics (Gutierrez Soto & Adeli, 2019, 2018; Y. Zhang et al., 2019) have been recently presented in the literature.…”

Section: Introductionmentioning

confidence: 99%

3D active dynamic actuation model for offshore cranes

Fantuzzi

Rustico

Formenti³

et al. 2021

Computer aided Civil Eng

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The handling of offshore payloads is a critical operation that presents numerous challenges, in particular related to the required precision in controlling their oscillations in a safe and accurate manner. The uncontrolled payload oscillations induced by the rolling movement of the vessel have been historically mitigated by the experience of on‐deck operators by means of taglines. The availability of experienced personnel is not always present, and a manual control operation still presents inconsistent performances and a high risk for the safety of men and machines. This study presents a novel approach to an antisway control conceived to mitigate such problems and possibly to automate some of the operations concerning the payload sway control that are currently done manually. In particular, a system consisting of a translating trolley actuated through a proportional–integral–derivative controller is taken into consideration to mitigate the oscillations induced by the vessel's rolling and pitching motion onto a three‐dimensional 8 degrees of freedom with double‐pendulum model representing the hanging payload. The study is completed through an analysis aimed to characterize the bandwidth and frequency response of the controlled closed‐loop system and highlight all the potential areas of interest for which further characterization is needed.

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“…An alternative approach is to incorporate game theory in design optimization (Gutierrez Soto & Adeli, 2017, 2018, 2019). A structural optimization problem can be considered as a game which aims to find the global optimal solution (e.g., minimal weight and optimal structural performance), under given design constraints.…”

Section: Introductionmentioning

confidence: 99%

Game theory‐based metaheuristics for structural design optimization

Mahjoubi

Bao

2021

Computer aided Civil Eng

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This paper presents game theory‐based strategies incorporated with metaheuristics to improve the computation efficiency and effectiveness in design optimization of civil engineering structures. The idea is that a structural optimization problem can be treated as a multiplayer game with optimization algorithms as the players. This study presents an innovative mixed game strategy and provides insights into domain decomposition schemes. Based on game theory strategies, six modified metaheuristic algorithms are proposed and demonstrated through a case study of a 30‐story mega‐braced frame‐core building with a complex configuration. Jaya algorithm is selected as the control to evaluate the proposed methods. The results show that the mixed game strategy helps reduce the computation cost by about 50%, while reducing the weights of the building by 4%, compared with the Jaya algorithm.

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Semi-active vibration control of smart isolated highway bridge structures using replicator dynamics

Cited by 66 publications

References 58 publications

Structural sparsity in control design of active and semi‐active systems

Structural sparsity in control design of active and semi‐active systems

3D active dynamic actuation model for offshore cranes

Game theory‐based metaheuristics for structural design optimization

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