Identification and robust water level control of horizontal steam generators using quantitative feedback theory

In this paper, a robust water level control system for the horizontal steam generator (SG) using the quantitative feedback theory (QFT) method is presented. To design a robust QFT controller for the nonlinear uncertain SG, control oriented linear models are identified. Then, the nonlinear system is modeled as an uncertain linear time invariant (LTI) system. The robust designed controller is applied to the nonlinear plant model. This nonlinear model is based on a locally linear neuro-fuzzy (LLNF) model. This model is trained using the locally linear model tree (LOLIMOT) algorithm. Finally, simulation results are employed to show the effectiveness of the designed QFT level controller. It is shown that it will ensure the entire designer’s water level closed loop specifications.

► A robust water level controller for steam generators (SGs) is designed based on the Quantitative Feedback Theory.
► To design the controller, fairly accurate linear models are identified for the SG.
► The designed controller is verified using a developed novel global locally linear neuro-fuzzy model of the SG.
► Both of the linear and nonlinear models are based on the SG mathematical thermal–hydraulic model developed using the simulation computer code.
► The proposed method is easy to apply and guarantees desired closed loop performance.