Optimal control of nonlinear frames by Newmark and distributed genetic algorithms

Abstract

Active control of multi‐storey frame structures with nonlinear hysteretic response has been studied in this paper. A new nonlinear optimal control algorithm based on nonlinear Newmark integration method and distributed genetic algorithm (DGA) has been developed. The objective has been to reduce the response to below any desired level. In this study, DGA has been used to determine the weights in the control law corresponding to displacement, velocity and acceleration. The capabilities of the method has been assessed through simulation where an eight‐storey frame with bilinear hysteretic behaviour has been subjected to a white noise ground acceleration and controlled by the controllers designed by the new algorithm. An active tendon control system comprised of prestressed tendons and either a single actuator, which could apply a force to one of the floors, or eight actuators, which could fully control the frame, has been used. Also, the optimum actuator placement in the single actuator case has been studied. The designed controllers have been tested under both near and far‐field earthquakes and have performed successfully. Copyright © 2009 John Wiley & Sons, Ltd.

Technical Note: Active and Semi-Active Strategies to Control Building Structures Under Large Earthquake Motion

“…Further strategies to increase structural control under large earthquakes include comparative studies (e.g., SAVD systems using passive, viscous, and ER dampers presented by Ribakov et al, 2001); the use of combined systems (e.g., smart isolation Madden et al, 2003]; smart isolation plus semi-active stiffness dampers [Agrawal and Yang, 2000]; and SAMD plus variable damping devices [Chey et al, 2010;Collins et al, 2008]); and the incorporation of MR dampers, especially in smart isolation [Jung et al, 2006;Spencer et al, 2001;Yoshioka et al, 2002]), but also with the purpose to assess specific issues, such as the torsional seismic response control of a 3-story reinforced concrete frame-shear wall eccentric structure [Hong-Nan and XiuLing, 2009] and the whipping effect between podium structure and multi-story buildings while subjected to earthquake motions [Xu et al, 2005]. Experimental research in systems targeting earthquake control have also focused on active bracing systems (ABS) [Loh et al, 1999;Reinhorn et al, 1993;Soong et al, 1991] and tendons systems [Cha et al, 1988;Chung et al, 1988Chung et al, , 1989Joghataie and Mohebbi, 2012;Lin et al, 2010;Soong and Manolis, 1987;Spencer et al, 1998]. Integration of structural design and control scheme [Cimellaro et al, 2009a,b;Lu and Skelton, 2000], and the achievement of truly smart structures by integrating devices and materials within the main load-bearing structure [Chopra, 2002;Morales-Beltran and Teuffel, 2013] has been proposed previously with the purpose of increasing the efficiency of controlled response building structures.…”

A genetic algorithm–based design approach for smart base isolation systems

“…GA developed by Holland (1975) is a powerful and capable optimization tool which has been used to generate useful solutions for complicated optimization problems in different fields of engineering. In designing structural control systems, GAs have been previously applied for optimal design of fuzzy controllers (Yan and Zhou, 2006), determining the optimum parameters of TMDs (Hadi and Arfiadi, 1998; Mohebbi and Joghataie, 2012), or MTMDs (Mohebbi et al, 2015b) for linear and nonlinear frames, designing optimal MR dampers (Xue et al, 2011), optimal design of AMDs (Mohebbi et al, 2015c) as well as optimal design and placement of sensors or actuators on structures for active control of structures (Abdullah et al, 2001; Askari et al, 2017; Joghataie and Mohebbi, 2012).…”

DGA-based approach for optimal design of active mass damper for nonlinear structures considering ground motion effect

“…This method was later improved for application to nonlinear and hysteretic structures by Joghataie and Mohebbi [38] who used the full feedback of response (displacement, velocity and acceleration) in the performance index. Later, Joghataie and Mohebbi [39] also used Newmark integration method and distributed genetic algorithm (DGA) and developed a nonlinear optimal control algorithm to design optimal controllers for active controlling of nonlinear frames against earthquakes using active tendon control (ATC) mechanism to apply the control force on the structure. In their research by using ATC as a simple mechanism, the main objective was to develop a control algorithm for nonlinear frames without considering any practical limitations in designing controllers.…”