{'fraction_non_alphanumeric': 0.01810699588477366, 'fraction_numerical': 0.0, 'mean_word_length': 5.644808743169399, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
The design of controllers for batch bioreactors

The implementation of control algorithms to batch bioreactors is often complicated by variations in process dynamics that occur during the course of fermentation. Such a wide operating range often renders the performance of fixed gain proportional‐integral‐differential (PID) controllers unsatisfactory. In this work, detailed studies on the control of batch fermentations are per formed. Two simple controller designs are presented with the intent to compensate for changing process dynamics. One design incorporates the concepts of static feedforward‐feedback control. While this technique produces tighter control than feedback alone, it is not as successful as a controller based on gain scheduling. The gain‐scheduling controller, a subclass of adaptive controllers, uses the oxygen uptake rate as an auxiliary variable to fine‐tune the PID controller parameters. The control of oxygen tension in the bioreactor is used as a vehicle to convey the proposed ideas, analyses, and results. Simulation experiments indicate significant improvement in controller performance can be achieved by both of the proposed approaches even in the presence of measurement noise.