Intelligent Control Methodology for Smart Highway Bridge Structures Using Optimal Replicator Dynamic Controller

Control algorithms are an essential part of effective semi-active vibration control systems used for the protection of large structures under dynamic loading. Adaptive control algorithms, which are data-driven methods, have recently been developed to replace model-based control algorithms, thus improving efficiency. The dynamic parameters of semi-actively controlled infrastructures will change after significant vibration loading. As a result, these structures require real-time, effective control actions in response to changing conditions, which classical controllers are unable to provide. To improve the efficiency of the semi-active controller, the optimal control algorithm was developed in this study. The algorithm is the integration of the replicator dynamics with an improved non-dominated sorting genetic algorithm (NSGA), which is NSGA-II. The optimal parameters of replicator dynamics (total resources, growth rate, and fitness function), which represent the behavior of the actuators, were obtained through a multi-objective optimization process. The new control system was then used to reduce the vibrations of the isolated highway bridge, which is equipped with semi-active control devices known as MR dampers. Moreover, the current study improved the performance of the structural control system with minimum energy consumption by assigning a specific growth rate to each control device. In order to reduce the vibrations of the highway bridge, the results show that the performance of the optimal replicator controller is better than the performance of the classical control algorithms.