Traditional proportional-integral-derivative (PID) controllers may not achieve the control performance desired for large time delay processes. Meanwhile, PI-PD controller is an improved version of PID controller, which can effectively improve the control performance of large time delay plants. However, it still has difficulty in parameter tuning. Even if its parameters can be tuned, the PI-PD may not ensure desired performance because of the large time delay and uncertainties of processes.
Recently, predictive function control (PFC) has been widely applied in practice since it is suitable for effectively coping with large time delays and uncertainties. Therefore, combining PFC with PI-PD control may be a good choice.
Kang Chung Hyok, a researcher at the Faculty of Metallic Engineering, designed a PI-PD controller using predictive functional control (PFC) based on the state space model of processes in order to solve the problem of complex parameter tuning. In order to further improve the performance of the controller, he used an improved grasshopper optimization algorithm (GOA) to optimize the weighting matrix of cost function that has a great impact on the performance of the state space PFC.
The simulation results showed that the proposed design method is far superior to other methods in terms of set-point tracking, disturbance rejection and robustness.
You can find more information in his paper “A Novel PI-PD Controller Design Based on Extended State Space Predictive Functional Control using Improved Grasshopper Optimization Algorithm” in “Proceedings of KUTIC-2025”.