Active Disturbance Rejection Control of Dense Medium Separation Process Based on Improved PI-GPC

Aiming at the complex field environment of dense medium separation process and the large amount of matrix inversion calculation in the traditional PI-GPC solution process, an adaptive stepped generalized predictive control method with proportional-integral structure (PI-ASGPC-LESO) based on active disturbance rejection strategy is proposed. Considering the large amount of calculation when PI-GPC solves the optimal control rate, an adaptive step factor dependent on the system adjustment error is introduced to constrain the change of the control amount, which reduces the amount of calculation in the solution process. In view of the complex on-site environment of dense medium separation and the large interference in the system, LESO is added to the loop to suppress external disturbances and compensate the unmodeled error of the system. In order to verify the effectiveness of the proposed method, a comparative experiment with traditional PI-GPC and PI-GPC-LESO was designed with the dense medium separation system of a coal preparation plant as the control object. The experimental results show that the proposed method effectively improves the dynamic performance of the system, with shorter adjustment time, smaller overshoot, and stronger anti-interference ability.