Model predictive control: theory and practice—a survey
Automatica (Journal of IFAC)
Robust adaptive control
Information Sciences—Informatics and Computer Science: An International Journal
Pattern Recognition and Machine Learning (Information Science and Statistics)
Pattern Recognition and Machine Learning (Information Science and Statistics)
International Journal of Robotics Research
Harnessing bacterial power in microscale actuation
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
Micromanipulation using artificial bacterial flagella
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
The active geometric shape model: A new robust deformable shape model and its applications
Computer Vision and Image Understanding
Closed-loop control of magnetotactic bacteria
International Journal of Robotics Research
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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.