A Noble PI-PD Controller Design Based on Extended State Space Predictive Functional Control Using Improved Grasshopper Optimization Algorithm

Abstract

In proportional-integral-proportional-derivative (PI-PD) controller design based on extended state space predictive functional control (ESSPFC), the proper tuning of weighting matrix of cost function has a direct influence on the controller performance. However, the analytical method to determine it has not been unknown. To solve this problem, in this paper, an improved grasshopper optimization algorithm (GOA) is used to improve the performance of controller by optimizing the weighting matrix of cost function. To overcome the drawbacks of standard GOA, a linear shrinking coefficient is replaced by nonlinear shrinking coefficient, a mutation operation is adopted, and position updating formula is modified. The performance of proposed method is tested and compared with other methods based on PFC. Simulation results show that the proposed design method is much superior to other methods in terms of the set-point tracking, disturbance rejection and robustness.