Adaptive Intelligent Backsteeping Control Of Cold Rolling Thickness Control Systems With Multivariable Constraints

The cold rolling mill hydraulic automatic gauge control(HAGC)systems has been widely used in every field due to its advantages of fast response,high accuracy and strong bearing ability.However,the control performance of the systems is restricted by measurement delay,external disturbance and uncertainty.This paper proposes an adaptive backstepping control strategy for the control problem of HAGC systems.The main contents are as follows:Firstly,in view of the external disturbance and the measurement delay in the cold rolling mill HAGC systems,an adaptive fuzzy backstepping control scheme is proposed based on barrier Lyapunov function.The dynamic model is transformed into a strict feedback form with the external disturbances and the measurement delay is converted into input delay.An anxiliary system is developed to compensate for the effect of time delay.The barrier Lyapunov function is introduced to ensure output error constraints of thickness of the rolling mill.Fuzzy logic systems and disturbance observer are used to deal with the nonlinear term and unknown compound uncertainty respectively.Based on Lyapunov stability theory,the semi-globally uniformly ultimately boundedness of the closed-loop systems is proved.The validity of control strategy is verified by simulation.Secondly,for HAGC system with external disturbance,the measurement delay,unmeasurable states and input saturation,the control strategy is designed combine adaptive fuzzy backstepping control with the fuzzy states observer.An auxiliary system is developed to compensate for the effect of time delay and input saturation,respectively.Moreover,an asymmetric barrier Lyapunov function is introduced to ensure output error constraints of thickness of the rolling mill and the fuzzy states observer is constructed to estimate unmeasurable states and unkown nonlinear functions.With the aid of backstepping,controller is designed to can guarantee the semi-globally boundedness of the closed-loop systems.The validity of the proposed control strategy is verified by the compared simulation.Finally,considering the control problem of HAGC system under measurement delay,full-state constraints,actuator failures and input constraints,an adaptive neural network faulttolerant controller is proposed for HAGC systems.An auxiliary system for input delay is introduced.Furthermore,a transformation is introduced to ensure the full-state constraints of the systems.Adaptive law is used to estimate the upper bound of unknown parameters to eliminate the effect of actuator failure on the system.Based on Lyapunov stability theory,the semi-global finited-time uniformly bounded stability of the systems is proved.The validity of control strategy is verified by simulation.