Due to its highly favorable physical and chemical properties,titanium and titanium alloy are widely used in a variety of industries.Because of the low output of a single batch,plate cold rolling without tension is the...Due to its highly favorable physical and chemical properties,titanium and titanium alloy are widely used in a variety of industries.Because of the low output of a single batch,plate cold rolling without tension is the most common rolling production method for titanium alloy.This method is lack of on-line thickness closed-loop control,with carefully thickness setting models for precision.A set of high-precision thickness setting models are proposed to suit the production method.Because of frequent variations in rolling specification,a model structural for the combination of analytical models and statistical models is adopted to replace the traditional self-learning method.The deformation resistance and friction factor,the primary factors which affect model precision,are considered as the objectives of statistical modeling.Firstly,the coefficient fitting of deformation resistance analytical model based on over-determined equations set is adopted.Additionally,a support vector machine(SVM)is applied to the modeling of the deformation resistance and friction factor.The setting models are applied to a 1450 plate-coiling mill for titanium alloy plate rolling,and then thickness precision is found consistently to be within 3%,exceeding the precision of traditional setting models with a self-learning method based on a large number of stable rolling data.Excellent application performance is obtained.The proposed research provides a set of high-precision thickness setting models which are well adapted to the characteristics of titanium alloy plate cold rolling without tension.展开更多
Uncertain friction is a key factor that influences the accuracy of servo system in CNC machine.In this paper,based on the principle of Active Disturbance Rejection Control(ADRC),a control method is proposed,where both...Uncertain friction is a key factor that influences the accuracy of servo system in CNC machine.In this paper,based on the principle of Active Disturbance Rejection Control(ADRC),a control method is proposed,where both the extended state observer(ESO) and the reduced order extended state observer(RESO) are used to estimate and compensate for the disturbance.The authors prove that both approaches ensure high accuracy in theory,and give the criterion for parameters selection.The authors also prove that ADRC with RESO performs better than that with ESO both in disturbance estimation and tracking error.The simulation results on CNC machine show the effectiveness and feasibility of our control approaches.展开更多
基金Supported by National Natural Science Foundation of China(Grant No.51304017)National Key Technology R&D Program of the 12th Five-year Plan of China(Grant Nos.2012BAF04B02,2011BAE23B04)Fundamental Research Funds for Central Universities,China(Grant No.FRF-SD-12-013B)
文摘Due to its highly favorable physical and chemical properties,titanium and titanium alloy are widely used in a variety of industries.Because of the low output of a single batch,plate cold rolling without tension is the most common rolling production method for titanium alloy.This method is lack of on-line thickness closed-loop control,with carefully thickness setting models for precision.A set of high-precision thickness setting models are proposed to suit the production method.Because of frequent variations in rolling specification,a model structural for the combination of analytical models and statistical models is adopted to replace the traditional self-learning method.The deformation resistance and friction factor,the primary factors which affect model precision,are considered as the objectives of statistical modeling.Firstly,the coefficient fitting of deformation resistance analytical model based on over-determined equations set is adopted.Additionally,a support vector machine(SVM)is applied to the modeling of the deformation resistance and friction factor.The setting models are applied to a 1450 plate-coiling mill for titanium alloy plate rolling,and then thickness precision is found consistently to be within 3%,exceeding the precision of traditional setting models with a self-learning method based on a large number of stable rolling data.Excellent application performance is obtained.The proposed research provides a set of high-precision thickness setting models which are well adapted to the characteristics of titanium alloy plate cold rolling without tension.
基金partially supported by the National Key Basic Research Project of China under Grant No.2011CB302400the National Basic Research Program of China under Grant No.2014CB845303the National Center for Mathematics and Interdisciplinary Sciences,Chinese Academy of Sciences
文摘Uncertain friction is a key factor that influences the accuracy of servo system in CNC machine.In this paper,based on the principle of Active Disturbance Rejection Control(ADRC),a control method is proposed,where both the extended state observer(ESO) and the reduced order extended state observer(RESO) are used to estimate and compensate for the disturbance.The authors prove that both approaches ensure high accuracy in theory,and give the criterion for parameters selection.The authors also prove that ADRC with RESO performs better than that with ESO both in disturbance estimation and tracking error.The simulation results on CNC machine show the effectiveness and feasibility of our control approaches.