Integrating metaheuristic optimization algorithms and modified integral resonant control to minimize stick-slip oscillations

• Developed a novel controller with Particle Swarm Optimization and Integral Control. • Outperformed other optimization methods in tuning controller parameters. • Demonstrated robust control in diverse drilling conditions. • Enhanced real-time drilling efficiency with fast parameter adjustments. • Validated controller effectiveness in multiple simulation scenarios. This paper aims to develop a robust controller capable of suppressing stick-slip oscillations. To achieve this goal, metaheuristic optimization algorithms, including Particle Swarm Optimization (PSO), Artificial Bee Colony (ABC), and Differential Evolution (DE), were integrated with Modified Integral Resonant Control (MIRC) to create a novel hybrid MIRC. Several simulation runs were conducted to investigate the robustness of the hybrid MIRC in automatically responding to disturbances. The results indicated that PSO outperforms the ABC and DE algorithms in the expeditious determination of optimal controller parameters. Additionally, simulation results demonstrated the robustness of the proposed PSO-MIRC in adeptly identifying key control parameters that suppress stick-slip vibrations within a succinct timeframe. The findings of this paper offer a promising tool for ensuring the stability of the drill-string.