T-S Fuzzy Algorithm Optimized by Genetic Algorithm for Dry Fermentation pH Control

Abstract

In the process of anaerobic dry fermentation to produce biogas, maintaining a suitable pH in the environment is more conducive to the degradation of crop straw. When the pH in the fermentation environment is too low, the process of anaerobic digestion by anaerobic bacteria is inhibited. Therefore, it is necessary to quickly adjust the pH. In this work, we studied the control technology of a pH regulation system and then constructed a T-S fuzzy controller. Upon simplifying the T-S fuzzy controller, the system delay time was reduced, and two genetic algorithms with different fitness performance indicators were used to optimize the T-S fuzzy control. The simulation experiment in this study was designed through simulation software, and the results show that the improved control method has a fast regulation ability. Finally, on-site experiments were conducted using the four control methods under the acidification conditions set in the experimental device. The results show that the control method used in this study to improve performance by integrating the error sum of squares has a short control time and small oscillation and overshoot, and it can better regulate the environmental pH to achieve appropriate conditions when acidification occurs during anaerobic dry fermentation.