- مبلغ: ۸۶,۰۰۰ تومان
- مبلغ: ۹۱,۰۰۰ تومان
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.
Mean arterial pressure (MAP) is the average blood pressure (BP) over a cardiac cycle and is determined by the cardiac output (CO), systemic vascular resistance (SVR) and central venous pressure (CVP). The stable control of MAP is important in the prevention of acute life-threatening condition such as hemorrhagic stroke and the deterioration of chronic hypertension-associated morbidities. Previous studies have shown that MAP is more accurate than systolic BP, diastolic BP and pulse pressure in predicting future metabolic syndrome among the normotensive elderly population (Hsu et al. 2015). According to that research, an MAP higher than the cutoff value indicates an elevated risk of developing metabolic syndrome. For the patients following cardiac arrest, hypoxic-ischemic brain injury is the major cause of death (Padmanabhan et al. 2015). While an MAP below the auto-regulatory threshold leads to additional ischemia and further brain injury, an elevated MAP above the auto-regulatory threshold causes excessive brain perfusion that may result in increased cerebral edema and worsening the pre-existing brain injury (Sekhon et al. 2016).
The MPC–PSO approach has been used to design our MAP control system. The results showed that the substantial delay between drug infusion and change in blood pressure posed a real challenge for PID controller design in the MAP control system. In contrast, the MPC–PSO controller effectively handled the delay and the limitation of control signal. The simulation results clearly depicted the better performance of the MPC–PSO MAP control system compared to that of the conventional PID MAP control system. Further studies are needed to deal with the variation of the model parameters and the disturbance from environments. The MPC–PSO MAP controller will be also able to design as a chip through a FPGA.