Simultaneous tuning of cascade controllers based on nonlinear optimization

Cascade control is widely used in the process industry, especially to reject disturbances. Typically, the controller parameters in the inner and outer loops of the cascade controller structure are defined in a strict sequence. In this paper, simultaneous tuning of cascade controllers is proposed to improve the performance of the system under load disturbance. For this purpose, the cost function of a nonlinear optimization problem is formulated to minimize the effect of disturbances on the system output. In addition, robustness constraints are defined for the maximum sensitivity function to independently guarantee a robust system for inner and outer loops. In this sense, the designer can explicitly and independently address the trade-off between performance and robustness for both loops. Simulation studies illustrate the performance and effectiveness of the proposed controller design method compared to well-known methods in the literature. These results indicate that the proposed method reduces the integrated absolute error (IAE) under load disturbance by up to 58%. In addition, experimental results from a tank-level control application in the mineral process industry illustrate the practical applicability of the proposed method. In this case, the proposed method reduces the IAE under load disturbance by 37%.

Automated summary

This paper proposes a method for simultaneous tuning of cascade controllers to improve system performance under load disturbance. By formulating a cost function for a nonlinear optimization problem and defining robustness constraints, designers can explicitly and independently address the trade-off between performance and robustness. Simulation and experimental results demonstrate that the proposed method successfully reduces the integrated absolute error under load disturbance.