Implementing PID controller tuning using the Jellyfish Search Algorithm in MATLAB involves creating a fitness function that evaluates the performance of the PID controller with a particular set of parameters. The Jellyfish Search Algorithm is a nature-inspired optimization technique that mimics the collective behavior of jellyfish. In this context, the algorithm is applied to search for optimal PID parameters that minimize the fitness function, reflecting the control system's response. The algorithm's iterative process simulates the movement of jellyfish in the search space, with each jellyfish representing a candidate solution (PID parameters). The fitness of each solution is assessed using the objective function, and the algorithm updates the positions of the jellyfish to guide the search towards optimal PID parameters. The process continues until convergence, resulting in a tuned PID controller that enhances the closed-loop system's performance. The MATLAB implementation involves coding the Jellyfish Search Algorithm and integrating it with the PID controller simulation, allowing for automated and efficient tuning of the controller for a specific dynamic system.