Abstract
Model-based optimization (MBO) has been widely applied for quality control of batch processes, however, it is not easy to obtain globally effective and accurate quality model with affordable effort. Instead of building a quality model, model-free optimization (MFO) uses process data directly, which is more efficient and economic for quality control of batch process. Considering the complex nonlinearity and dynamics in batch process, a quality control scheme using natural gradient based dynamic optimization is proposed in this paper. Optimization algorithm is developed from the aspect of manifold in non-Euclidean space. An approximation method is derived for the calculation of the natural gradient, and a multivariate iterative sensitivity matrix based on Riemannian geodesic distance is proposed to obtain a novel adaptive stepping strategy. The proposed quality control scheme has been verified in injection molding process. A set of comparison tests are presented to demonstrate the feasibility and effectiveness of the proposed method.
Published Version
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