Design of Multi-Cell Cooperative Control Algorithm Based on Fuzzy Brain Emotional Learning

Abstract

Multi-cell cooperative control can be competent for the current increasingly complex biomedical experiments, greatly improving the efficiency of cell manipulation experiments. At present, this kind of multi-cell cooperative control algorithm is becoming more and more important. In this study, holographic optical tweezers are used to capture multiple cells, and a cell manipulation controller is designed based on the Fuzzy Brain Emotional Learning (FBEL) neural network. Firstly, the dynamic model of trapping yeast cells by optical tweezers is analyzed. The distance between the trap position and the cell position is constrained to avoid cell detachment due to the trap moving too fast. Then, the design cell manipulation controller is relied upon to realize single transport trajectory tracking control. Finally, a multi-cell cooperative control algorithm is designed, and combined with the cell manipulation controller, a multi-cell cooperative controller based on the FBEL neural network is formed. The error between the cell position and the desired trajectory is the input of the multi-cell cooperative controller. The output of the multi-cell cooperative controller is the optical trap position, which is used to realize the cooperative control of multiple cells by holographic optical tweezers. The simulation results showed that the multi-cell cooperative controller based on the FBEL neural network can effectively control multiple yeast cells and quickly converge the cell formation, while ensuring a higher control accuracy than other traditional cell manipulation controllers. It provides a new solution for the efficient and precise automatic manipulation of multiple cells.