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

Abstract

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.

Adaptive sliding mode observers‐based dissipative Hamilton finite time optimization control for the speed and tension system of reversible cold strip rolling mill

“…Combined with related rolling theory of cold rolled strip steel, the mathematical model for the speed and tension system of a RCSRM is 3 :…”

Fixed‐time prescribed performance optimization control for the speed and tension system of the cold strip rolling mill with output constraints

“…A dissipative Hamilton controller based on the interconnection‐damping configuration and energy shaping method was designed in Reference 6, which effectively weakened the coupling between the state variables of the cold strip rolling mill system. In Reference 7, a sliding mode observer was constructed to dynamically observe the unmatched uncertainty of the system, and an immersion and invariance adaptive decentralized controller was designed, which made the cold strip rolling mill system had better dynamic and static performance and anti‐interference ability. In Reference 8, the command filtered method was employed to solve the problem of the “differential explosion”, and the finite‐time controller based on the backstepping control method was designed to guarantee the tracking errors converge in finite time, which exhibited faster convergence speed and stronger robust stability for the system.…”

“…It should be noted that most of the controller design methods in References 4–9 can only achieve asymptotic or finite‐time convergences of the system states. Among them, the former is when $$$ t\to \infty $$$, the system states can converge to equilibrium point or neighbors near equilibrium point, while it is difficult to meet people's requirements on the convergence speed and control accuracy of the rolling mill system in practice.…”

“…In addition, References 4–9 mainly focused on improving the steady‐state performance of the cold strip rolling mill system, but the transient‐state performance and output constraints of the system were not fully considered. For the cold strip rolling mill system in this article, if the speed and tension output states are constrained and stably operate in feasible range, then the impact on the rolling mill equipment during rolling production can be reduced, and belt breaking, steel stacking and other production accidents can be avoided.…”

“…Furthermore, the empirical trial and error method was adopted in controller parameter settings in References 4–14. Although certain control effect can be achieved, the whole process is cumbersome, and it is difficult to achieve the optimal control potential of the controllers.…”