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Mean arterial pressure control system using model predictive control and particle swarm optimization

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Abstract

Linear controllers have been designed to regulate mean arterial pressure (MAP) in treating various cardiovascular diseases. For patients with hemodynamic fluctuations, the MAP control system must be able to provide more sensitive control. Therefore, in this paper, a model predictive control (MPC) approach is presented to improve the sensitivity of MAP control system. The MPC principle can effectively handle the dead times in nonlinear systems, and can also optimize the system responses when subjected to constraints of process states and control signals. Besides, particle swarm optimization (PSO) is employed to solve the optimization problem of MPC at each control interval. According to our simulations, the MAP control system with combined MPC–PSO approach is superior in control qualities to the MAP control system with conventional linear control method. The MPC–PSO MAP control system is possible to be realized through a field-programmable gate array.

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Authors and Affiliations

  1. Department of Electronic Engineering, National Kaohsiung University of Applied Sciences, Sanmin District, Kaohsiung, 80778, Taiwan

    Te-Jen Su, Shih-Ming Wang, Hong-Quan Vu & Jau-Ji Jou

  2. Department of Emergency Medicine, E-Da Hospital, I-Shou University, Yan-Chao District, Kaohsiung, 82445, Taiwan

    Cheuk-Kwan Sun

  3. Graduate Institute of Clinical Medicine, Kaohsiung Medical University, Sanmin District, Kaohsiung, 80708, Taiwan

    Te-Jen Su

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  1. Te-Jen Su
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  2. Shih-Ming Wang
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  3. Hong-Quan Vu
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  4. Jau-Ji Jou
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  5. Cheuk-Kwan Sun
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Correspondence to Jau-Ji Jou.

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Su, TJ., Wang, SM., Vu, HQ. et al. Mean arterial pressure control system using model predictive control and particle swarm optimization. Microsyst Technol 24, 147–153 (2018). https://doi.org/10.1007/s00542-016-3212-9

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  • DOI: https://doi.org/10.1007/s00542-016-3212-9

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