The design of reliable control systems to maintain feasible optimal conditions and intensify bioprocesses is a requirement to achieve high product yields and cost-efficient process operations. Micro-aeration is an approach to increase bioprocess product yield. However, standard control strategies may present unsatisfactory performance under oxygen supply constraints. In this paper, a novel framework using process operability and biomimetic control algorithms is proposed to define a control strategy for improved micro-aerated batch process fermentations. In particular, process operability is employed to characterize the ideal operating regions. Then, the Biologically-Inspired Optimal Control Strategy (BIOCS) is implemented to take the process to the optimal path by manipulating the inlet gas flow rate and controlling the metabolic cell state. By employing the developed framework, an optimal operating region is successfully obtained for the controller to maintain the desired metabolic state. Specific scenarios of measurement noise, plant-model mismatch, and step disturbance rejection are successfully addressed in the BIO-CS implementations, while a proportional-integral controller presented noisy control actions under the same conditions. This developed control framework is a novel step towards Industry 4.0 concepts associated with bioprocess systems engineering and could also be implemented to improve other oxygen-limited processes.

设计可靠的控制系统以保持可行的最佳条件并加强生物过程是实现高产品产量和具有成本效益的过程操作的必要条件。微曝气是一种提高生物过程产品产量的方法。然而，标准控制策略在氧气供应限制下可能表现出不令人满意的性能。在本文中，提出了一种使用过程可操作性和仿生控制算法的新框架来定义改进的微曝气批量过程发酵的控制策略。特别是，过程可操作性被用来表征理想的操作区域。然后，实施生物启发优化控制策略（BIOCS），通过操纵入口气体流速和控制代谢细胞状态将过程带到最佳路径。通过采用开发的框架，控制器成功获得了最佳操作区域，以维持所需的代谢状态。在 BIO-CS 实现中成功解决了测量噪声、设备模型失配和阶跃干扰抑制的特定场景，而比例积分控制器在相同条件下呈现了噪声控制动作。这种开发的控制框架是朝着与生物过程系统工程相关的工业 4.0 概念迈出的新一步，也可以实施以改进其他限氧过程。和阶跃干扰抑制在 BIO-CS 实现中成功解决，而比例积分控制器在相同条件下呈现噪声控制动作。这种开发的控制框架是朝着与生物过程系统工程相关的工业 4.0 概念迈出的新一步，也可以实施以改进其他限氧过程。和阶跃干扰抑制在 BIO-CS 实现中成功解决，而比例积分控制器在相同条件下呈现噪声控制动作。这种开发的控制框架是朝着与生物过程系统工程相关的工业 4.0 概念迈出的新一步，也可以实施以改进其他限氧过程。