Effective ballast water management is critical for maintaining the stability, trim, and structural integrity of ocean vehicles and floating structures under dynamic operating conditions. This paper presents a comparative analysis of Proportional-Integral (PI), Proportional-Integral-Derivative (PID), and Model Predictive Control (MPC) strategies for ballast tank flow management. A dynamic system model capturing the behavior of a ballast tank was developed using an experimental system identification technique. This involved an experimental setup consisting of two interconnected tanks, simulating ship ballast tanks, equipped with a Telemecanique ultrasonic sensor for water level measurement and controlled via a Siemens SIMATIC S7-1200 Programmable Logic Controller (PLC), configured through the Totally Integrated Automation (TIA) Portal. The derived model was then implemented in MATLAB/Simulink for further analysis and validation. The controllers were designed, tuned, and evaluated based on performance metrics, including rise time, settling time, overshoot, and constraint handling. Results demonstrate that while PI and PID controllers provide satisfactory performance in steady-state conditions, their effectiveness diminishes under dynamic and constraint-laden scenarios. Conversely, MPC exhibits superior performance, particularly in managing operational constraints and disturbances, making it a robust candidate for real-time ballast flow control in advanced marine systems. The study underscores the potential of MPC to enhance the stability and operational efficiency of ocean vehicles and floating structures, paving the way for further research into hybrid and adaptive control strategies for ballast management systems.