Auxiliary particle filter-model predictive control of the vacuum arc remelting process

[摘要] Solidification control is required for the suppression of segregation defects in vacuum arc remelting of superalloys. In recent years, process controllers for the VAR process have been proposed based on linear models, which are known to be inaccurate in highly-dynamic conditions, e.g. start-up, hot-top and melt rate perturbations. A novel controller is proposed using auxiliary particle filter-model predictive control based on a nonlinear stochastic model. The auxiliary particle filter approximates the probability of the state, which is fed to a model predictive controller that returns an optimal control signal. For simplicity, the estimation and control problems are solved using Sequential Monte Carlo (SMC) methods. The validity of this approach is verified for a 430 mm (17 in) diameter Alloy 718 electrode melted into a 510 mm (20 in) diameter ingot. Simulation shows a more accurate and smoother performance than the one obtained with an earlier version of the controller.

[发布机构] Department of Mechanical Engineering, University of Texas at Austin, Austin; TX; 78705, United States^1

[效力级别] 金属工艺学 [学科分类] 材料科学（综合）

[关键词] Auxiliary particle filter;Control problems;Dynamic condition;Model predictive controllers;Nonlinear stochastic model;Process controllers;Sequential Monte Carlo methods;Vacuum-arc remelting process