PSO-Tuned FOPID Controller for Optimized Oil Reservoir Injection Flow Control

Background : Injection flow control in oil reservoirs is inherently challenging due to system nonlinearity, multivariable interactions, and parameter uncertainties. Traditional Proportional–Integral–Derivative (PID) controllers often fail to provide robust performance in such environments. The introduction of fractional-order PID (FOPID) controllers has significantly improved control flexibility and robustness in industrial process applications. Aims : This research aims to enhance the performance of reservoir injection flowrate control by combining the adaptability of FOPID controllers with the optimization capabilities of Particle Swarm Optimization (PSO). The objective is to minimize overshoot, reduce steady-state error, and improve overall stability of the injection process in nonlinear reservoir systems. Methods : The study employs a PSO algorithm to automatically tune the five parameters of the FOPID controller ( ,λ,μ) . The proposed approach is implemented and validated in a high-fidelity reservoir simulation environment using MATLAB/Simulink. Key performance indices such as ISE, ITAE, and overshoot are evaluated to compare the optimized controller with conventional PID and manually tuned FOPID controllers . Results : The PSO-tuned FOPID controller demonstrates superior performance, achieving reduced overshoot by 25%, faster settling times, and improved disturbance rejection compared to baseline methods. These findings indicate that the proposed method offers a reliable and efficient solution for optimizing injection control in oil reservoirs, with strong potential for real-world application .