Artificial intelligence as a tool for automatic state estimation and control of bioreactors

Abstract

Microbial fermentations in real situa

Artificial Neural Networks in Membrane Bioreactors: A Comprehensive Review—Overcoming Challenges and Future Perspectives

“…ANNs represent an interesting strategy, with the capability to identify complex dynamic relationships between inputs and outputs in MBRs using different architectures such as feedforward, recurrent, (i) Hybrid models combining neural networks with other AI techniques An intriguing strategy for future research involves developing hybrid models that can combine neural networks with other AI algorithms, including model predictive control, fuzzy logic, and genetic algorithms. These hybrid models have the potential to demonstrate higher accuracy, robustness, and improved interpretability than ANNs by combining the advantages of all the AI technologies used [13,42,46]. For instance, genetic algorithms can optimize the architecture of ANNs or control and operating parameters to achieve target goals such as avoiding membrane fouling or minimizing pollutants.…”

“…Given the complexity of these systems, identifying each malfunction to design countermeasures is not an easy task, even for well-trained operators and engineers. ANNs could take on the role of fault diagnosis, knowing the patterns and behaviors of different components or conditions of the systems such as membrane fouling, aeration failure, or low nutrient concentration [45,46]. Through a comparison of the learned data with real-time measurements, ANN diagnosis algorithms can isolate the problem, providing valuable information for troubleshooting and maintenance of the system [45,46].…”

Opportunities for artificial intelligence and synthetic biology in designing living drug delivery systems

“…Moreover, robust large-scale biomanufacturing with minimal batch-to-batch variability may be difficult to execute, especially considering the selective pressures against engineered gene circuits [ 252 , 264 ]. Efforts are already underway to introduce AI methods into bioprocess engineering, but this is still an early area of development [ 265 - 268 ]. In addition, the delivery of living drug delivery vehicles from production facilities to patient end-users will be another critical challenge.…”

Design and real-time implementation of a TS fuzzy observer for anaerobic wastewater treatment plants

“…The extended Kalman filter [5] and the horizon moving observer [6] offer good estimations but the calculus time is very long, moreover numerical errors could be induced. In the last years fuzzy and intelligent algorithms have been used to design observers for bioprocess as shown in [7] - [9]. The advantages of fuzzy observers are the possibility to employ the empirical knowledge of the wastewater processes operators and in general these types of observers are easy to design.…”