Immersion and invariance adaptive decentralized control for the speed and tension system of the reversible cold strip rolling mill

An immersion and invariance (I&I) adaptive decentralized control strategy is proposed for the speed and tension system of the reversible cold strip rolling mill, which is characterized by multiple variable, nonlinearity, strong coupling effect, and uncertainty. First, a sliding mode observer (SMO) is constructed to estimate the unmatched uncertainty of the system to improve the tracking control precision. Second, the I&I theory-based estimators are designed to estimate the perturbation parameters of the system, and the parameter estimation errors converge monotonically following an exponential law. Third, the I&I theory-based decentralized controllers are designed for the speed and tension system of the reversible cold strip rolling mill, which achieve precise tracking controls for the given values of the system. Theoretical analysis shows that the resulting closed-loop system is globally stable. Finally, the simulation research is carried out on the speed and tension system of a 1422 mm reversible cold strip rolling mill using actual data, and the simulation results verify the superiority of the proposed control strategy in comparison with the I&I control strategy and the backstepping dynamic surface control strategy.