Particle Swarm Optimization for Active Structural Control of Highway Bridges Subjected to Impact Loading

• Main Authors: Jake Edmond Hughes, Yeesock Kim, Jo Woon Chong, Changwon Kim
• Format: Article
• Language: English
• Published: Hindawi Limited 2018-01-01
• Series: Shock and Vibration
• Online Access: http://dx.doi.org/10.1155/2018/4932870

The application of active structural control technology to highway bridge structures subjected to high-impact loadings is investigated. The effects of high-impact loads on infrastructure, like heavy vehicle collisions with bridge piers, have not been studied as much as seismic load effects on structures. Due to this lack of research regarding impact loads and structural control, a focused study on the application of active control devices to infrastructure after impact events can provide valuable results and conclusions. This research applies active structural control to an idealized two-span, continuous girder, concrete highway bridge structure. The idealization of a highway bridge structure as a two degree-of-freedom structural system is used to investigate the effectiveness of control devices installed between the bridge pier and deck, the two degrees of freedom. The control devices are fixed to bracing between the bridge pier and girders and controlled by the proportional-integral-derivative (PID) control. The PID control gains are optimized by both the Ziegler–Nichols ultimate sensitivity method (USM) and a new method for this impact load application called particle swarm optimization (PSO). The controlled time-domain responses are compared to the uncontrolled responses, and the effectiveness of PID control, USM optimization, and PSO is compared for this control device configuration. The results of this investigation show PID control to be effective for minimizing both superstructure and substructure responses of highway bridges after high-impact loads. Deck response reductions of greater than 19% and 37% were seen for displacement and acceleration responses, respectively, regardless of the performance index used to analyze them. PSO was much more effective than USM optimization for tuning PID control gains.