A System Designed for Modelling, Monitoring, and Control of Fermentation Processes, Powered by Metaheuristic Algorithms

This paper introduces an Interactive System for Education in Modelling and Control of Biotechnological Processes (InSEMCoBio) for biotechnologists, including students and researchers. The system integrates advanced optimisation algorithms for identifying models of nonlinear systems, along with algorithms for monitoring and controlling biotechnological processes. InSEMCoBio was developed in MATLAB R2017a, featuring a user-friendly graphical interface that bridges complex computational tasks. Three metaheuristics for model identification are built in: an evolutionary algorithm, a genetic algorithm, and a hybrid metaheuristic algorithm. The software allows users to execute integrated algorithms and obtain desired results through visualisation (graphical and tabular) of data, without requiring programming knowledge. The functions of the system are demonstrated through the operation of the algorithms on two biotechnological processes. The ability to compare results of different algorithms is shown. The embedded identification algorithms are applicable beyond biotechnology. This provides the developed system with potential for other interesting applications.