A new modeling and monitoring approach for multi-mode processes is proposed.The method of similarity measure(SM) and kernel principal component analysis(KPCA) are integrated to construct SM-KPCA monitoring scheme,wher...A new modeling and monitoring approach for multi-mode processes is proposed.The method of similarity measure(SM) and kernel principal component analysis(KPCA) are integrated to construct SM-KPCA monitoring scheme,where SM method serves as the separation of common subspace and specific subspace.Compared with the traditional methods,the main contributions of this work are:1) SM consisted of two measures of distance and angle to accommodate process characters.The different monitoring effect involves putting on the different weight,which would simplify the monitoring model structure and enhance its reliability and robustness.2) The proposed method can be used to find faults by the common space and judge which mode the fault belongs to by the specific subspace.Results of algorithm analysis and fault detection experiments indicate the validity and practicability of the presented method.展开更多
In order to continuously simulate multi-pass plate rolling process,a 3-D elastic hollow-roll model was proposed and an auto mesh-refining module with data passing was developed and integrated with FE software,Marc.The...In order to continuously simulate multi-pass plate rolling process,a 3-D elastic hollow-roll model was proposed and an auto mesh-refining module with data passing was developed and integrated with FE software,Marc.The hollow-roll model has equivalent stiffness of bending resistance and deformation to the real solid and much less meshes,so the computational time is greatly reduced.Based on these,the factors influencing plate profile,such as the roll-bending force,initial crown,thermal crown and heat transfer during rolling and inter-pass cooling can be taken into account in the simulation.The auto mesh-refining module with data passing can automatically refine and re-number elements and transfer the nodal and elemental results to the new meshes.Furthermore,the 3-D modeling routine is parametrically developed and can be run independently of Marc pre-processing program.A seven-pass industrial hot rolling process was continuously simulated to validate the accuracy of model.By comparison of the calculated results with the industrial measured data,the rolling force,temperature and plate profile are in good accordance with the measured ones.展开更多
In order to obtain accurate prediction model and compensate for the influence of model mismatch on the control performance of the system and avoid solving nonlinear programming problem,an adaptive fuzzy predictive fun...In order to obtain accurate prediction model and compensate for the influence of model mismatch on the control performance of the system and avoid solving nonlinear programming problem,an adaptive fuzzy predictive functional control(AFPFC) scheme for multivariable nonlinear systems was proposed.Firstly,multivariable nonlinear systems were described based on Takagi-Sugeno(T-S) fuzzy models;assuming that the antecedent parameters of T-S models were kept,the consequent parameters were identified on-line by using the weighted recursive least square(WRLS) method.Secondly,the identified T-S models were linearized to be time-varying state space model at each sampling instant.Finally,by using linear predictive control technique the analysis solution of the optimal control law of AFPFC was established.The application results for pH neutralization process show that the absolute error between the identified T-S model output and the process output is smaller than 0.015;the tracking ability of the proposed AFPFC is superior to that of non-AFPFC(NAFPFC) for pH process without disturbances,the overshoot of the effluent pH value of AFPFC with disturbances is decreased by 50% compared with that of NAFPFC;when the process parameters of AFPFC vary with time the integrated absolute error(IAE) performance index still retains to be less than 200 compared with that of NAFPFC.展开更多
基金Projects(61273163,61325015,61304121)supported by the National Natural Science Foundation of China
文摘A new modeling and monitoring approach for multi-mode processes is proposed.The method of similarity measure(SM) and kernel principal component analysis(KPCA) are integrated to construct SM-KPCA monitoring scheme,where SM method serves as the separation of common subspace and specific subspace.Compared with the traditional methods,the main contributions of this work are:1) SM consisted of two measures of distance and angle to accommodate process characters.The different monitoring effect involves putting on the different weight,which would simplify the monitoring model structure and enhance its reliability and robustness.2) The proposed method can be used to find faults by the common space and judge which mode the fault belongs to by the specific subspace.Results of algorithm analysis and fault detection experiments indicate the validity and practicability of the presented method.
基金Project(20050248007) supported by the Specialized Research Fund for the Doctoral Program of Higher Education of China
文摘In order to continuously simulate multi-pass plate rolling process,a 3-D elastic hollow-roll model was proposed and an auto mesh-refining module with data passing was developed and integrated with FE software,Marc.The hollow-roll model has equivalent stiffness of bending resistance and deformation to the real solid and much less meshes,so the computational time is greatly reduced.Based on these,the factors influencing plate profile,such as the roll-bending force,initial crown,thermal crown and heat transfer during rolling and inter-pass cooling can be taken into account in the simulation.The auto mesh-refining module with data passing can automatically refine and re-number elements and transfer the nodal and elemental results to the new meshes.Furthermore,the 3-D modeling routine is parametrically developed and can be run independently of Marc pre-processing program.A seven-pass industrial hot rolling process was continuously simulated to validate the accuracy of model.By comparison of the calculated results with the industrial measured data,the rolling force,temperature and plate profile are in good accordance with the measured ones.
基金Project(2007AA04Z162) supported by the National High-Tech Research and Development Program of ChinaProjects(2006T089, 2009T062) supported by the University Innovation Team in the Educational Department of Liaoning Province, China
文摘In order to obtain accurate prediction model and compensate for the influence of model mismatch on the control performance of the system and avoid solving nonlinear programming problem,an adaptive fuzzy predictive functional control(AFPFC) scheme for multivariable nonlinear systems was proposed.Firstly,multivariable nonlinear systems were described based on Takagi-Sugeno(T-S) fuzzy models;assuming that the antecedent parameters of T-S models were kept,the consequent parameters were identified on-line by using the weighted recursive least square(WRLS) method.Secondly,the identified T-S models were linearized to be time-varying state space model at each sampling instant.Finally,by using linear predictive control technique the analysis solution of the optimal control law of AFPFC was established.The application results for pH neutralization process show that the absolute error between the identified T-S model output and the process output is smaller than 0.015;the tracking ability of the proposed AFPFC is superior to that of non-AFPFC(NAFPFC) for pH process without disturbances,the overshoot of the effluent pH value of AFPFC with disturbances is decreased by 50% compared with that of NAFPFC;when the process parameters of AFPFC vary with time the integrated absolute error(IAE) performance index still retains to be less than 200 compared with that of NAFPFC.
