Used for industrial process with different degree of nonlinearity, the two predictive control algorithms presented in this paper are based on Least Squares Support Vector Machines (LS-SVM) model. For the weakly nonlin...Used for industrial process with different degree of nonlinearity, the two predictive control algorithms presented in this paper are based on Least Squares Support Vector Machines (LS-SVM) model. For the weakly nonlinear system, the system model is built by using LS-SVM with linear kernel function, and then the obtained linear LS-SVM model is transformed into linear input-output relation of the controlled system. However, for the strongly nonlinear system, the off-line model of the controlled system is built by using LS-SVM with Radial Basis Function (RBF) kernel. The obtained nonlinear LS-SVM model is linearized at each sampling instant of system running, after which the on-line linear input-output model of the system is built. Based on the obtained linear input-output model, the Generalized Predictive Control (GPC) algorithm is employed to implement predictive control for the controlled plant in both algorithms. The simulation results after the presented algorithms were implemented in two different industrial processes model; respectively revealed the effectiveness and merit of both algorithms.展开更多
A curriculum is a complex system that includes a set of core competencies, objectives, contents, methodological and evaluation criteria, regulation among other things. In order to represent a curriculum as a piece of ...A curriculum is a complex system that includes a set of core competencies, objectives, contents, methodological and evaluation criteria, regulation among other things. In order to represent a curriculum as a piece of software the common tools used are databases, trees and lists of courses. However, none of these tools can capture the deep and complex relationships among the elements of a curriculum. To avoid this problem, a more complete representation of an engineering curriculum using ontologies has been developed. This paper presents the construction of an ontology for undergraduate electrical engineering curriculum domain at Universidad Nacional de Colombia, which aims to represent, organize, formalize and standardize the knowledge of this domain, so that it can be shared and reused by different groups of people in the field of education and engineering. The ontology includes four curriculum aspects： knowledge in electrical engineering, skills in engineering, electrical engineering curriculum and regulation. For the ontology development, Methontology was selected as methodology and Protege as implementation tool. In addition, there is a proposal of documentation for this methodology, based on principles of quality management systems. This ontology is designed in order to be used in any field of engineering.展开更多
基金Project supported by the National Outstanding Youth ScienceFoundation of China (No. 60025308) and the Teach and ResearchAward Program for Outstanding Young Teachers in Higher EducationInstitutions of MOE, China
文摘Used for industrial process with different degree of nonlinearity, the two predictive control algorithms presented in this paper are based on Least Squares Support Vector Machines (LS-SVM) model. For the weakly nonlinear system, the system model is built by using LS-SVM with linear kernel function, and then the obtained linear LS-SVM model is transformed into linear input-output relation of the controlled system. However, for the strongly nonlinear system, the off-line model of the controlled system is built by using LS-SVM with Radial Basis Function (RBF) kernel. The obtained nonlinear LS-SVM model is linearized at each sampling instant of system running, after which the on-line linear input-output model of the system is built. Based on the obtained linear input-output model, the Generalized Predictive Control (GPC) algorithm is employed to implement predictive control for the controlled plant in both algorithms. The simulation results after the presented algorithms were implemented in two different industrial processes model; respectively revealed the effectiveness and merit of both algorithms.
文摘A curriculum is a complex system that includes a set of core competencies, objectives, contents, methodological and evaluation criteria, regulation among other things. In order to represent a curriculum as a piece of software the common tools used are databases, trees and lists of courses. However, none of these tools can capture the deep and complex relationships among the elements of a curriculum. To avoid this problem, a more complete representation of an engineering curriculum using ontologies has been developed. This paper presents the construction of an ontology for undergraduate electrical engineering curriculum domain at Universidad Nacional de Colombia, which aims to represent, organize, formalize and standardize the knowledge of this domain, so that it can be shared and reused by different groups of people in the field of education and engineering. The ontology includes four curriculum aspects： knowledge in electrical engineering, skills in engineering, electrical engineering curriculum and regulation. For the ontology development, Methontology was selected as methodology and Protege as implementation tool. In addition, there is a proposal of documentation for this methodology, based on principles of quality management systems. This ontology is designed in order to be used in any field of engineering.
