Short-term Motion Control for Semi-submersible Platform Based on Constrained Fuzzy Genetic Optimization Controller

Semi-submersible platforms (SSPs) are used for offshore oil and gas exploration and production activities in deep-sea areas. The short-term motion of SSPs, propelled by thrusters controlled by a dynamic positioning system (DPS), enables the SSP to move short distances and position itself reliably while considering constraints and environmental impacts. This study proposes a hybrid fuzzy genetic control solution for the optimal short-term motion control of the SSP, whereas the membership function is globally optimized for the fitness function (30) subject to the thruster constraints. Additionally, this approach enhances the system's adaptability to external influences, thereby improving the accuracy of the controller's responses in practice, that is, error approaches zero. In addition, the proposed solution is experimentally integrated into the operation of the UT-SSP-02 model, which is a scale model of the actual Stena Don rig. This setup provides realistic control forces for the physical thrusters. The results from the comparative analysis of response quality, whereas compared to other advanced algorithms, demonstrate the effectiveness of the proposed controller.