| After 50 years'R&D, the rotary artificial heart blood pumps have achieved many progresses, a lot of clinical requirements have been satisfied such as blood compatibility, implantability and durability, thus the comfortability of the receiptor with a heart pump becomes more and more important in the future. The key technology to achieve this purpose is to improve the sensitivity of flow rate changing after the pressure head variation in the pump, so as to maintain the flow rate balance between the left ventricular assist pump and the right ventricle. Due to limited self-modulation property of impeller pump, however, it is difficult to do so automatically. Therefore, it is necessary to find a way to solve this problem from pump control system.Three bionic control methods were designed:A,Manual control method. This control method is an experimental approach that designed mainly in order to obtain the control relation equations between head changes and voltage compensation. The blood pump was performed by the control system used in constant voltage control mode, some voltage compensation for control system was given manually during adjusting the head variation, to achieve the sensitivity requirements of flow rate change after the pressure head variation, the relation between the head variation and voltage compensation was recorded and diagramed, then exhibited with the function. In this control method, the head and flow rate were measured by adjusting the control system manually, they should be the ideal values of the bionic control system, would be used for comparative analysis with other bionic control systems.B,Bionic control system based on sensor feedback parameters of the blood pump. This control system determined the control strategy by input voltage compensation method, to improve the sensitivity of flow change with head variation, after analyzing the relationships of the blood pump head, flow rate and the input voltage, followed by designing the hardware and software of control system. ATmegal6 microcontroller was used as control chip of system, and sensors MPXV5050GP was used to feedback the import and export pressure of blood pump, the head of blood pump was then calculated. According to head changes, a control equation from control method A was used to calculate the voltage compensation, the bionic control was achieve by controlling voltage changes. C,Bionic control system based on blood pump parameters detected by neural network automatically. The control strategy of this system is same as the control method B, with difference that the pressure head was obtained by converting the motor's parameters by the neural network automatically. A neural network model was established in this measuring method according to the relationship of the pressure head of the blood pump with motor power and speed by neural network software Neuroshell2. A lot of data were studied for the neural network model by selecting the appropriate activation function, the parameters of network model was adjusted, the stability of neural network was increased, the error of the neural network measuring values and the sensor measuring values ??was within 5%. Then, the weights and bias of neural network after learning were got by the software neuroshell2, written neural network program according to activation function, achieved the prediction function of network. The hardware and software were designed based on control strategy, the monolithic integrated controller ML4425 made by Microlinear Company was designated as the drive chip for the artificial heart to drive blood pump's motor, ARM Cortex-M3 series MCU STM32F103C8T6 was used as single-chip microcomputer control system, achieved the automatically detection function of network. According to head changes, a control equation from control method A was used to calculate the voltage compensation, controlled voltage changes to achieve bionic control.Finally, the data of control method C were compared with those of control method B and the ideal data of manual control method by control method A, the error and the causes of the error were analyzed, then compared also with the data of constant voltage and constant speed control system. The results show that the bionic control system designed based on blood pump parameters automatically detected by neural network greatly increased the sensitivity of the flow rate with the head changes, from 1L/min corresponding 10mmHg in constant voltage mode and constant speed mode, to 1L/min corresponding 2mmHg, close to the natural heart 1L/min corresponding 1mmHg. It concludes that clinical requirement for flow balance between the patient's right ventricle and the left ventricular assist heart pump can be reached by this bionic control system.
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