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

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) ap...

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Bibliographic Details
Published in:Microsystem technologies : sensors, actuators, systems integration actuators, systems integration, 2018, Vol.24 (1), p.147-153
Main Authors: Su, Te-Jen, Wang, Shih-Ming, Vu, Hong-Quan, Jou, Jau-Ji, Sun, Cheuk-Kwan
Format: Article
Language:English
Subjects:
Electronics and Microelectronics
Engineering
Instrumentation
Mechanical Engineering
Nanotechnology
Technical Paper
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Summary: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.
ISSN:0946-7076
1432-1858
DOI:10.1007/s00542-016-3212-9