Two robust mutlivariable controllers, H_∞ and a decentralized quantitative feedback theory (QFT), are designed in the frequency domain for the 2 × 2 looper system in a steel hot rolling mill to keep stability in the presence of parametric uncertainties. The H_∞ controller is designed by using the mixed sensitivity approach, while the multivariable decentralized QFT is designed by the extension of the sequential loop closing method presented elsewhere. Stability robustness conditions are verified in the frequency domain, while simulations in time domain are carried out to evaluate the controllers and compare their performance along with that of proportional + integral (PI) and single input single output (SISO) QFT controllers designed earlier. The QFT controller shows the best balance among the performance indicators analyzed here; however, at the expenses of using higher power in one of the control inputs.

Entry temperature estimation is a major concern for finishing mill set-up in hot strip mills. Variations in the incoming bar conditions, frequent product changes and measurement uncertainties may cause erroneous estimation, and hence, an incorrect mill set-up causing a faulty bar head-end. In earlier works, several varieties of neuro-fuzzy systems have been tested due to their adaptation capabilities. In order to test the combination of the simplicity offered by Takagi–Sugeno–Kang systems (also known as Sugeno systems) and the modeling power of type-2 fuzzy, in this work, hybrid-learning type-2 Sugeno fuzzy systems are evaluated and compared with the results presented earlier. Systems with both empirically and fuzzy c-means-generated rules as well as purely fuzzy systems and grey-box models are tested. Experimental data were collected from a real-life mill; datasets for rule-generation, training, and validation were randomly drawn. Two of the grey-box models presented here reach 100% of bars with 20 °C or less prediction error, while two of the purely fuzzy systems improved performance with respect to purely fuzzy systems presented elsewhere, however it was only a slight improvement.