Control cells by a magnetic field with Model Predictive

This paper presents the Model Predictive Control (MPC) of magnetized Tetrahymena pyriformis (T. pyriformis) using a magnetic field. The magnetized T. pyriformis are generated by feeding spherical iron oxide particles into the cells. Using an external magnetic field, we change the movement direction of the cell, but the speed of the cell remains constant regardless of the strength of the external magnetic field. The contributions of this paper are threefold. First, the discrete-time plant model of the magnetized cell is generated using the least-squares method. Second, using the model of each cell, they are controlled to follow a reference track by an external magnetic field with MPC. Third, by using a predictor-like scheme to execute the plant input before the measurement of the cell position, we successfully solve the image-processing delay problem in the feedback system. In our results, we show three comparisons between different control schemes and an initial tracking to prove the effectiveness of the control approach.