Control methodologies for vibration control of smart civil and mechanical structures

Abstract

Artificial intelligence and expert system remains a key technology in the 21st century. Using active controllers, a structure can adaptively adjust its behaviour during dynamic loads. Such structures with self‐modifying capabilities are referred to as intelligent or smart structures. Smart structure technology has the potential to be a game changer in the structural engineering field. It promises to have enormous consequences in terms of preventing loss of life and damage to structure and their content especially for large structures with hundreds or thousands of components. A key element in successful implementation of smart active control technology is an effective control algorithm to compute the magnitudes of actual forces to be applied to the structure. In this paper, an overview of main active control methodologies for vibration control of smart civil and mechanical structures subjected to external dynamic loads is presented. The advantages and the disadvantages of different control algorithms are discussed. Finally, new trends in control algorithm research are pointed out including multiparadigm strategies, decentralized control, application of deep neural network machine learning techniques, control design for sustainability, and unification of the two fields of structural health monitoring and vibration control.

Intelligent control of horizontal vibration of high-speed elevator based on gas–liquid active guide shoes

“…Neural network control (NNC) [30][31][32] is a representative of modern intelligent control. It is an active network composed of a simple computing-processing unit (i.e., a neuron) and a network topology.…”

Optimum distribution of seismic energy dissipation devices using neural network and fuzzy inference system

“…The wind‐induced motion of high‐rise buildings considered a structural control challenge; however, Kim and Adeli (2005b) have proposed a semiactive tuned liquid column damper and showed its effectiveness on a 76‐story building benchmark control problem. Recent literature on structural control showed the potential of recent control algorithms (e.g., Gutierrez Soto & Adeli, 2017a; Li & Adeli, 2018) and vibration control devices with effective placement (e.g., El‐Khoury & Adeli, 2013; Gutierrez Soto & Adeli, 2013). Gutierrez Soto and Adeli (2017b) integrated different replicator controllers with a multiobjective optimization algorithm to obtain Pareto‐optimal values for achieving maximum structural performance with minimum energy consumption.…”

Active Vibration Control of Seismically Excited Building Structures by Upgraded Grey Wolf Optimizer

“…However, these structures may be susceptible to wide-band earthquake-induced lateral loads, especially in high seismicity regions [2]. To this end, active vibration control approaches have been widely pursued in the scientific literature for suppressing earthquake-borne lateral oscillations in high-rise buildings [3], aiming to increase community resilience to the seismic hazard. Such approaches employ large-scale actuators to exert time-varying control forces to buildings such that seismic structural demands, namely lateral relative inter-storey displacements (storey drifts) and floor accelerations, are minimized.…”

“…To this end, this paper focuses on the development of an improved metaheuristic optimization algorithm to design a fuzzy logic controller (FLC) for efficient seismic protection of tall buildings via active control. Note that FLCs have been widely considered in the literature for active vibration control of civil structures for several years and proved their effectiveness over alternative controllers [3,[10][11][12][13]. Further, there is rich literature on the use of metaheuristic optimization algorithms for FLC design in various engineering applications, some of which are reviewed here.…”