Research On Adaptive Robust Decentralized Control Of Speed And Tension System Of Reversible Cold Strip Rolling Mill

The production level of cold-rolled strip is an important symbol of the development level of a country's iron and steel industry.Cold strip rolling mill is a special equipment for producing strip steel products.To keep the strip tension constant is an effective way to solve the quality problem of strip shape and thickness.In the actual rolling production process,the left coiler,the main mill and the right coiler of the cold strip rolling mill are connected by a flexible connection of strip steel,and the characteristics of speed and tension system of the cold strip rolling mill is multivariable and nonlinear,strong coupling and uncertainty,and the constraints of heavy load and interference in the rolling process pose new challenges to the analysis and control of the rolling mill system.This paper focuses on the adaptive robust decentralized control of the study of the speed and tension system of the reversible cold strip rolling mill.The main research work is as follows:Firstly,combinning with the rolling production process of cold-rolled strip,based on Hooke's law,relevant rolling theory of cold-rolled strip,motor dynamics equation,rigid body rotation law and other basic theoretical knowledge derive Mechanism model of speed and tension system for reversible cold strip rolling mill.Secondly,a backstepping sliding mode control method based on extended state observer(ESO)is proposed for the speed and tension tracking control problem of the speed and tension system of reversible cold strip rolling mill.The ESOs are constructed to observe the compound disturbances composed of parameter perturbation and load disturbance,and the output observation values are introduced into the backstepping sliding mode controllers for compensation,which effectively enhances the anti-interference performance of the system and simplifies the design process of the system controller.Thirdly,a nonsingular terminal sliding mode control strategy based on time-variable gain extended state observer(TVGESO)is proposed for the finite time control problem of the speed and tension system of reversible cold strip rolling mill.The TVGESOs are used to observe the mismatched uncertainties of the system,and the backstepping control and nonsingular terminal sliding mode control are combined to complete the design of each subsystem controller;the neural network adaptive method is used to approximate the matched uncertainties of the system,and the estimated values are introduced into the designed controllers for compensation,The speed and tension tracking control performance and robust stability of the system are effectively improved.Finally,aiming at the problem of adaptive robust decentralized control for the speed tension system of reversible cold strip rolling mill,an immersion and invariance(I&I)control method based on sliding mode observer(SMO)is proposed.In this method,a sliding mode observer is constructed to observe the uncertainty,and the parameter estimator independent of the system controller is designed based on the I&I adaptive control;the decentralized controller of the speed tension system of the reversible cold strip rolling mill is designed by using the I&I nonlinear control method,which is simple and clear,with few adjustable parameters and no need to be constructed Lyapunov function is constructed,and it has better dynamic and static performance.