This article develops and experimentally validates a distributed predictive control algorithm for closed-loop control of inkjet 3-D printing to handle constraints, e.g., droplet volume bounds, as well as the large-scale nature of the 3-D printing problem. The large number of decision variables, i.e., droplet volumes at each grid point, in high resolution inkjet 3-D printing makes centralized methods extremely time-consuming, thus, a distributed implementation of the controller is necessary. First, a graph-based height evolution model that captures the liquid spreading dynamics is described. Based on this model, a scalable closed-loop control algorithm using distributed model predictive control (MPC) that can reduce computation time significantly is designed and experimentally implemented. The performance and efficiency of the algorithm are shown to outperform open-loop printing and closed-loop printing with existing centralized MPC methods.

中文翻译：

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喷墨3-D打印的层到层预测控制

本文开发并实验验证了用于喷墨3-D打印的闭环控制的分布式预测控制算法，以处理约束（例如，墨滴体积界限）以及3-D打印问题的大规模性质。在高分辨率喷墨3-D打印中，大量的决策变量（即，每个网格点处的墨滴量）使集中式方法非常耗时，因此，需要控制器的分布式实现。首先，描述了一个基于图的高度演化模型，该模型捕获了液体扩散动力学。基于此模型，设计并实验实现了一种可扩展的闭环控制算法，该算法使用分布式模型预测控制（MPC）可以显着减少计算时间。