In industrial drives, electric motors are extensively utilized to impart motion control and induction motors are the most familiar drive at present due to its extensive performance characteristic similar with that of ...In industrial drives, electric motors are extensively utilized to impart motion control and induction motors are the most familiar drive at present due to its extensive performance characteristic similar with that of DC drives. Precise control of drives is the main attribute in industries to optimize the performance and to increase its production rate. In motion control, the major considerations are the torque and speed ripples. Design of controllers has become increasingly complex to such systems for better management of energy and raw materials to attain optimal performance. Meager parameter appraisal results are unsuitable, leading to unstable operation. The rapid intensification of digital computer revolutionizes to practice precise control and allows implementation of advanced control strategy to extremely multifaceted systems. To solve complex control problems, model predictive control is an authoritative scheme, which exploits an explicit model of the process to be controlled. This paper presents a predictive control strategy by a neural network predictive controller based single phase induction motor drive to minimize the speed and torque ripples. The proposed method exhibits better performance than the conventional controller and validity of the proposed method is verified by the simulation results using MATLAB software.展开更多
Investigation of a beach and its wave condi-tions is highly requisite for understanding the physicalprocesses in a coast. This study composes spatial andtemporal correlation between beach and nearshore pro-cesses alon...Investigation of a beach and its wave condi-tions is highly requisite for understanding the physicalprocesses in a coast. This study composes spatial andtemporal correlation between beach and nearshore pro-cesses along the extensive sandy beach of Nagapattinamcoast, southeast peninsular India. The data collectionincludes beach profile, wave data, and intertidal sedimentsamples for 2 years from January 2011 to January 2013.The field data revealed significant variability in beach andwave morphology during the northeast （NE） and southwest（SW） monsoon. However, the beach has been stabilized bythe reworking of sediment distribution during the calmperiod. The changes in grain sorting and longshoresediment transport serve as a clear evidence of thesediment migration that persevered between foreshoreand nearshore regions. The Empirical Orthogonal Function（EOF） analysis and Canonical Correlation Analysis （CCA）were utilized to investigate the spatial and temporallinkages between beach and nearshore criterions. Theoutcome of the multivariate analysis unveiled that theseasonal variations in the wave climate tends to influencethe bar - berm sediment transition that is discerned in thecoast.展开更多
文摘In industrial drives, electric motors are extensively utilized to impart motion control and induction motors are the most familiar drive at present due to its extensive performance characteristic similar with that of DC drives. Precise control of drives is the main attribute in industries to optimize the performance and to increase its production rate. In motion control, the major considerations are the torque and speed ripples. Design of controllers has become increasingly complex to such systems for better management of energy and raw materials to attain optimal performance. Meager parameter appraisal results are unsuitable, leading to unstable operation. The rapid intensification of digital computer revolutionizes to practice precise control and allows implementation of advanced control strategy to extremely multifaceted systems. To solve complex control problems, model predictive control is an authoritative scheme, which exploits an explicit model of the process to be controlled. This paper presents a predictive control strategy by a neural network predictive controller based single phase induction motor drive to minimize the speed and torque ripples. The proposed method exhibits better performance than the conventional controller and validity of the proposed method is verified by the simulation results using MATLAB software.
文摘Investigation of a beach and its wave condi-tions is highly requisite for understanding the physicalprocesses in a coast. This study composes spatial andtemporal correlation between beach and nearshore pro-cesses along the extensive sandy beach of Nagapattinamcoast, southeast peninsular India. The data collectionincludes beach profile, wave data, and intertidal sedimentsamples for 2 years from January 2011 to January 2013.The field data revealed significant variability in beach andwave morphology during the northeast （NE） and southwest（SW） monsoon. However, the beach has been stabilized bythe reworking of sediment distribution during the calmperiod. The changes in grain sorting and longshoresediment transport serve as a clear evidence of thesediment migration that persevered between foreshoreand nearshore regions. The Empirical Orthogonal Function（EOF） analysis and Canonical Correlation Analysis （CCA）were utilized to investigate the spatial and temporallinkages between beach and nearshore criterions. Theoutcome of the multivariate analysis unveiled that theseasonal variations in the wave climate tends to influencethe bar - berm sediment transition that is discerned in thecoast.
