Optimal control of jacket platform under wave vibration with Active Tuned Mass Damper

In recent decades, different control strategies (i.e., passive, active, semi-active, or hybrid) have been extensively employed to suppress the response of offshore structures subjected to dynamic lateral loads. Jacket platforms are vital structures for oil-rich countries that are frequently subjected to dynamic harsh sea waves. Therefore, the vibration control of these structures is substantial to increase productivity, safety, and serviceability and prevent premature possible fatigue failure. In this study, the behavior of the Ressalat platform located in the Persian Gulf is evaluated under wave loads with two different return periods of 50 and 100 years. A simplified equivalent seven-degree-of-freedom lumped mass linear model is adopted for the Ressalat platform. In the Persian Gulf, wave loads are the dominant load in the designing procedure. Due to the stochastic nature of wave loads, random wave and constrained new-wave theories are utilized in the generation of the wave records. Then, Passive Tuned Mass Damper (PTMD) and Active Tuned Mass Damper (ATMD) are employed to suppress the platform vibration and subsequently, their control performances are compared. Various calculated normalized performance criteria (responses of controlled to uncontrolled structures) for passive and active controlled platforms including normalized maximum and Root Mean Square (RMS) of displacement, velocity, and acceleration of the deck level are calculated and compared. The uncontrolled and controlled platforms are modeled and analyzed using MATLAB and SIMULINK software. Moreover, the fuzzy intelligent algorithm with a triangular membership function is implemented to calculate the control force and the Harmony Search Algorithm (HAS) is examined to optimize the actuator power. Also, the Fluid-Structure Interaction (FSI), the effect of added mass due to the accelerated motion of the body in the fluid, and the saturation of the actuator are considered. The results show the effectiveness of the proposed control system by reducing 20% and 50% of the maximum and RMS of the platform deck acceleration, respectively, over time.