PSO-tuned PID Controller for Enhanced Energy Efficiency and Temperature Control in a Time-Varying Distillation Column System

Traditional PID controllers, while widely used in process industries, often face challenges in parameter tuning, especially for nonlinear systems with time-varying input parameters. This finding explores the optimization of Proportional-Integral-Derivative (PID) control systems using Particle Swarm Optimization (PSO) for enhancing energy efficiency and performance in a Distillation Column Pilot Plant (DCPP) used for essential oil extraction. Using Pseudo Random Binary Signal (PRBS) as perturbation input signals, the study estimated the nonlinear transfer function model of DCPP. This research proposed a model that integrated PSO to optimize PID parameters, ensuring precise temperature control crucial for maintaining the quality of essential oils. The performance of the PID-PSO controller is compared with conventional PID controllers, demonstrated superior response characteristics, reduced energy consumption, and enhanced essential oil quality. The results highlighted the effectiveness of PSO in reducing transient response of the complexities nonlinear system behaviors especially PSO tuning method with Integral Time Square Error showed as the best control response with the rise time of 0.000171 s, peak time of 1.054 s, overshoot of $0 \%$ and settling time of 0.00502 s compared to conventional PID and the advantages of precise temperature regulation in industrial distillation processes. Overall, The PID-PSO led to energy efficiency improvement as compared with PID, whereas PID fine-tuning produced the lowest energy consumption with 39760 J.