Research on Gas Turbine Speed Control Based on PSO-MPC Rolling Optimization of PI Parameters

To address the control challenges arising from the highly nonlinear characteristics of gas turbines and overcome issues related to tuning PI controller parameters, this study presents an innovative speed control methodology specifically designed for gas turbines. By integrating Particle Swarm Optimization with Model Predictive Control in real-time, our proposed approach effectively optimizes PI controller parameters. To serve as a predictive model, we employ a state-space model obtained through system identification techniques. Through rolling optimization using the PSO algorithm, dynamic adjustments can be made to fine-tune the PI controller parameters accordingly. Our digital simulations demonstrate that this approach yields faster response times compared to conventional PI controllers while significantly enhancing system adaptability. Consequently, our research provides valuable insights into optimizing control strategies for nonlinear systems.