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Application of Nonlinear Predictive Control Based on RBF Network Predictive Model in MCFC Plant
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作者 陈跃华 曹广益 朱新坚 《Journal of Shanghai Jiaotong university(Science)》 EI 2007年第1期42-46,52,共6页
This paper described a nonlinear model predictive controller for regulating a molten carbonate fuel cell (MCFC). A detailed mechanism model of output voltage of a MCFC was presented at first. However, this model was t... This paper described a nonlinear model predictive controller for regulating a molten carbonate fuel cell (MCFC). A detailed mechanism model of output voltage of a MCFC was presented at first. However, this model was too complicated to be used in a control system. Consequently, an off line radial basis function (RBF) network was introduced to build a nonlinear predictive model. And then, the optimal control sequences were obtained by applying golden mean method. The models and controller have been realized in the MATLAB environment. Simulation results indicate the proposed algorithm exhibits satisfying control effect even when the current densities vary largely. 展开更多
关键词 molten carbonate fuel cell (MCFC) radial basis function (RBF)neural network model nonlinear model predictive control (NMPC) golden mean method
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CFD-based hull optimization in calm water using adaptive grid deformation method 被引量:1
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作者 Shuguang Wang Yonghwan Kim 《Journal of Hydrodynamics》 SCIE EI CSCD 2024年第2期241-262,共22页
This paper presents an adaptive grid deformation technique for optimizing ship hull forms using computational fluid dynamics(CFD).The proposed method enables accurate and smooth updates of the hull surface and 3-D CFD... This paper presents an adaptive grid deformation technique for optimizing ship hull forms using computational fluid dynamics(CFD).The proposed method enables accurate and smooth updates of the hull surface and 3-D CFD grids in response to design variables.This technique incorporates a two-level point-transformation approach to move the grid points by a few design points.Initially,generic B-splines are utilized to transform grid points according to the displacements of the control points within a defined control box.This ensures surface modification accuracy and smoothness,similar to those provided by non-uniform rational B-splines.Subsequently,radial basis functions are used to interpolate the movements of the control points with a limited set of design points.The developed method effectively maintains the mesh quality and simulation efficiency.By applying this method to surface and grid adaptation,a regression model is proposed in the form of a second-order polynomial to represent the relationship between the geometric parameters and design variables.This polynomial is then used to introduce geometric constraints.Furthermore,a radial basis function surrogate model for the calm-water resistance is constructed to approximate the objective function.An enhanced optimization framework is proposed for CFD–based hull optimization and applied to KVLCC2 to validate its feasibility and efficiency. 展开更多
关键词 Hull-form optimization adaptive grid deformation ship resistance OPENFOAM radial basis function(RBF)surrogate model
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