Modeling and Optimizing Control of Particle Quality for Drug Fluidized Bed Granulation Process

This paper presents an optimization control strategy of particle quality for drug fluidized bed granulation process. Firstly, a predictive model of average particle size is established to construct the optimization model. However, this quality optimization will be hampered by model uncertainty. The batch-to-batch optimization based on ILC method is utilized to overcome model uncertainty and the integrated optimization method that combines batch-to-batch optimization and optimization in the batch is proposed to increase the convergence rate and eliminate or reduce the adverse effect of process disturbance. The effectiveness of proposed method is validated by simulations.