Hamilton‐based adaptive robust control for the speed and tension system of reversible cold strip rolling mill
Summary The adaptive robust control problem for the speed and tension system of reversible cold strip rolling mill is studied based on the Hamilton theory in this paper. First, the dissipative Hamilton model of the rolling mill system's speed and tension outside loop is built through pre‐feedba...
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Published in | International journal of adaptive control and signal processing Vol. 33; no. 4; pp. 626 - 643 |
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Main Authors | , , , |
Format | Journal Article |
Language | English |
Published |
Bognor Regis
Wiley Subscription Services, Inc
01.04.2019
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Subjects | |
Online Access | Get full text |
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Summary: | Summary
The adaptive robust control problem for the speed and tension system of reversible cold strip rolling mill is studied based on the Hamilton theory in this paper. First, the dissipative Hamilton model of the rolling mill system's speed and tension outside loop is built through pre‐feedback control, and then, dissipative Hamilton controllers are designed by utilizing the interconnection and damping assignment and the energy shaping method. Second, in order to realize tensiometer‐free control and adaptive robust control for the perturbation parameters and load disturbance, full‐order state observers and adaptive robust controllers are designed for the rolling mill system's speed and tension outside loop by using the “extended system + feedback” method. Third, robust controllers for the rolling mill system's current inside loop are designed based on the cascade control thought, so as to realize the tracking control for the speed and tension of reversible cold strip rolling mill. Theoretical analyses show that the resulting closed‐loop system is stable. Finally, simulation research is carried out on the speed and tension system of a 1422‐mm reversible cold strip rolling mill, and simulation results verify the validity of the proposed control strategy in comparison with the decentralized overlapping control strategy. |
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ISSN: | 0890-6327 1099-1115 |
DOI: | 10.1002/acs.2977 |