Ships can be operated more efficiently by utilizing intelligent decision support integrated with onboard data collection systems.In this study,a Bayesian optimization-based decision support system,which uti-lizes ship...Ships can be operated more efficiently by utilizing intelligent decision support integrated with onboard data collection systems.In this study,a Bayesian optimization-based decision support system,which uti-lizes ship performance models built by machine learning methods,is proposed to help determine the operational set-points of two engines for double-ended ferries.By optimizing the ferries’power alloca-tion between the stern and bow engines,the Decision Support System(DSS)will simultaneously attempt to keep the ETA of the ferry fixed under a set of operational constraints using the Bayesian optimization.Its objective is to minimize fuel consumption along individual trips.Based on simulation environment,the DSS can reduce at maximum 40%fuel consumption with no significant change of the ETA.Final full-scale experiments of a double-ended ferry demonstrated an average of 15%,where at least half of this saving was achieved by the optimized power allocation between bow and stern engines.展开更多
A layered modeling method is proposed to resolve the problems resulting from the complexity of the error model of a multi-axis motion control system. In this model, a low level layer can be used as a virtual axis by t...A layered modeling method is proposed to resolve the problems resulting from the complexity of the error model of a multi-axis motion control system. In this model, a low level layer can be used as a virtual axis by the high level layer. The first advantage of this model is that the complex error model of a four-axis motion control system can be divided into several simple layers and each layer has different coupling strength to match the real control system. The second advantage lies in the fact that the controller in each layer can be designed specifically for a certain purpose. In this research, a three-layered cross coupling scheme in a four-axis motion control system is proposed to compensate the contouring error of the motion control system. Simulation results show that the maximum contouring error is reduced from 0.208 mm to 0.022 mm and the integration of absolute error is reduced from 0.108 mm to 0.015 mm, which are respectively better than 0.027 mm and 0.037 mm by the traditional method. And in the bottom layer the proposed method also has remarkable ability to achieve high contouring accuracy.展开更多
基金support from the Swedish Foundation for International Cooperation in Research and Higher Education(CH2016–6673).
文摘Ships can be operated more efficiently by utilizing intelligent decision support integrated with onboard data collection systems.In this study,a Bayesian optimization-based decision support system,which uti-lizes ship performance models built by machine learning methods,is proposed to help determine the operational set-points of two engines for double-ended ferries.By optimizing the ferries’power alloca-tion between the stern and bow engines,the Decision Support System(DSS)will simultaneously attempt to keep the ETA of the ferry fixed under a set of operational constraints using the Bayesian optimization.Its objective is to minimize fuel consumption along individual trips.Based on simulation environment,the DSS can reduce at maximum 40%fuel consumption with no significant change of the ETA.Final full-scale experiments of a double-ended ferry demonstrated an average of 15%,where at least half of this saving was achieved by the optimized power allocation between bow and stern engines.
基金Project(51005086)supported by the National Natural Science Foundation of ChinaProject(2010MS085)supported by the Fundamental Research Funds for the Central Universities,ChinaProject(DMETKF2013008)supported by the Open Project of the State Key Laboratory of Digital Manufacturing Equipment and Technology,China
文摘A layered modeling method is proposed to resolve the problems resulting from the complexity of the error model of a multi-axis motion control system. In this model, a low level layer can be used as a virtual axis by the high level layer. The first advantage of this model is that the complex error model of a four-axis motion control system can be divided into several simple layers and each layer has different coupling strength to match the real control system. The second advantage lies in the fact that the controller in each layer can be designed specifically for a certain purpose. In this research, a three-layered cross coupling scheme in a four-axis motion control system is proposed to compensate the contouring error of the motion control system. Simulation results show that the maximum contouring error is reduced from 0.208 mm to 0.022 mm and the integration of absolute error is reduced from 0.108 mm to 0.015 mm, which are respectively better than 0.027 mm and 0.037 mm by the traditional method. And in the bottom layer the proposed method also has remarkable ability to achieve high contouring accuracy.
