Automatic control technology in fermentation engineering: a review

Fermentation engineering is a cornerstone of modern biotechnology, playing a pivotal role in the production of pharmaceuticals, biofuels, food additives, and industrial enzymes. The escalating demand for high yields, consistent product quality, and enhanced process efficiency has rendered the integration of advanced automatic control theory indispensable. This technical Mini Review shifts focus from mature data acquisition hardware to advanced control strategies, emphasizing soft sensors as algorithmic bridges for intelligent control, and expanding technical analysis of modern architectures tailored to the non-linear and time-variant nature of biological systems. It addresses key advanced control technologies including fuzzy logic, inverse neural networks (INN), cloud computing, digital twins, evolutive algorithms, and control vector parameterization (CVP), while clarifying the research gap in automated control of organoleptic profiles to ensure final sensory quality. Supported by recent and foundational studies (including recommended citations), this review integrates and analyzes the latest advancements in advanced control for fermentation, equipping researchers and industry professionals with comprehensive insights to foster the intelligent upgrading of fermentation processes. It also discusses challenges in industrial scalability and solutions such as coupling computational fluid dynamics (CFD) with fermentation kinetics. By filling a critical knowledge integration gap within this interdisciplinary domain, it aims to equip researchers and industry professionals with comprehensive insights to foster the intelligent upgrading of fermentation processes.