Essential tremor is a neurological disorder that causes involuntary hand tremors, interfering with daily activities such as eating. This study developed a spoon stabilization system controlled by a Proportional-Integral-Derivative (PID) controller, which was tuned using Particle Swarm Optimization (PSO) and the Cohen-Coon method for performance comparison. The system utilized an inertial measurement unit to detect tremors, while a Kalman filter reduced noise before a microcontroller controlled a servo motor to stabilize the spoon. The system was evaluated through simulations and hardware implementation, with performance assessed based on rise time, overshoot, delay time, and settling time. The results showed that the Kalman filter significantly reduced noise, lowering the average pitch angle error deviation from 1.028° to 0.037° and the roll angle error from 0.822° to 0.031°. The PSO-based tuning outperformed the Cohen-Coon method in response speed and system stability, achieving a faster rise time (0.09 s for roll, 0.34 s for pitch), a shorter settling time (0.74 s for roll, 0.59 s for pitch), and a lower delay time (0.1 s for roll, 0.15 s for pitch). However, the Cohen-Coon method resulted in a lower overshoot for the roll angle (6.08%) compared to the PSO-based tuning (11.98%).