Control Simulation of Left Ventricular Assist Device using Artificial Neural Network

인공신경망을 이용한 좌심실보조장치의 제어 시뮬레이션

  • 김상현 (연세대학교 심혈관연구소) ;
  • 정성택 (성균관대학교 대학원) ;
  • 김훈모 (성균관대학교 기계공학부)
  • Published : 1998.02.01

Abstract

In this paper, we present a neural network identification and a control of highly complicated nonlinear left ventricular assist device(LVAD) system with a pneumatically driven mock circulation system. Generally, the LVAD system needs to compensate for nonlinearities. It is necessary to apply high performance control techniques. Fortunately, the neural network can be applied to control of a nonlinear dynamic system by learning capability. In this study, we identify the LVAD system with neural network identification(NNI). Once the NNI has learned the dynamic model of the LVAD system, the other network, called neural network controller(NNC), is designed for a control of the LVAD system. The ability and effectiveness of identifying and controlling the LVAD system using the proposed algorithm will be demonstrated by computer simulation.

본 연구에서 복잡한 비선형적 특성을 갖는 공압식 좌심실보조장치의 모델링과 제어에 인공신경망을 제안하였다. 일반적으로 좌심실보조장치는 비선형이 보상되어야 하는데 인공신경망은 학습능력에 의해 비선형 동적 시스템의 제어에 적용될 수 있다. 인공신경망 모델링을 통해 좌심실 보조장치의 동적 모델을 모델링하고 이를 기반으로 하여 인공신경망 제어기가 설계되었다. 제안된 알고리즘을 이용한 좌심실보조장치의 모델링과 제어성능 및 유효성은 컴퓨터 시뮬레이션에 의해 증명되었다.

Keywords

References

  1. a registry report. J. Heart & Lung Transplant v.11 Summart of the clinical use of the Symbion total artifical heart K. E. Johnson;M. Presto;L. D. Joyce;M. Pritzker;R.W. Emery
  2. J. Heart & Lung Transplant. v.9 Thoratec VAD system as a bridge to heart transplantation D. J. Farra;J. H. Lawson;P. Litwak;G. Cederwall
  3. J. Thorac. Cariovasc. Surg. v.102 Clinical experience with the Novacor ventricular assist system P. M. McCarthy;P. M. Portner;H. G. Tobler;V. A. Starnes;N. Ramasamy;P. E. Oyer
  4. IEEE Engineering in Medicine and Biology Control modes of clinical ventricular assist device D. J. Farrer;P. G. Compton;J. H. Lawson;J. J. Hershon;J. D. Hill
  5. Circulatory Sytem Dynamics A, Noodergraaf
  6. IEEE Trans. Biomed. Eng. v.BME-32 Time-varying mechanical properties of the left ventricle a computer simulation G. Avanzolini;P. Barbini;A. Cappello;G. Cevenini
  7. Int. J. Biomed. Computer v.22 CADCS Sinlation of the closed-loop cardiovascular system G. Avanzolini;P. Barbini;A. Cappello;G. Cevenini
  8. Japanese J. Artif. Organs. v.18 no.2 Development of a non-invasive and continuous monitoring of natural heart output during left ventricular assit device(LVAD) pumping H. Sekii;H. Takano;Y. Taenak;T. Takatani;H. Noda;M. Kinoshita;E. Tatsumi;A. Yagura;T. Akutsu
  9. IEEE Trans. Biomed. Eng. v.18 Theoretical analysis of a left ventricular pumping model based on the systolic time-varying pressure/volume ratio H. Suga
  10. Med. Biol. Eng. no.2 An Eletrical analogue of the entire human circulatory system L. Pater;De Van Berg
  11. IEEE Trans. Biomedical Engineering v.40 Real-time cardiac output estimation of the circulatory system under left ventricular Assistance M. Yoshizawa
  12. IEEE Trans. Biomed. Eng. v.39 An automatic control algoritm for the optimal driving of the vetricular-assist device M. Yoshizawa
  13. IEEE Fronteers of Engineering in Health Care Adaptive control system for the artificial heart B. C. McInnis;J. C. Wang
  14. Artificial organs v.15 no.2 Investigation of parameter estimation & adaptive controller for assist pump by computer simulation T. Shimooka;Y. Mitamura;T. Yuhta
  15. IEEE Engineering in Medicine and Biology Assessing cardiovascular dynamics during ventricular assistance M. Yoshizawa;H. Takeda;T. Yanke;S. Nitta
  16. Proc. 28th CDC(Tampa, FL) Adaptive identification and control of dynamic systems using neural networks K. S. Narendra;K. Parthasarathy
  17. IEEE Trans. Neural Networks v.1 Identification and control of dynamic systems using neural networks K. S. Narendra;K. Parthasarathy
  18. Proc. 1990 Americam Control Conf. Use of neural nets for dynamic modeling and control of chemical process systems M. Bhat;T. J. McAvoy
  19. IEEE control syst. Magazine Modeling chemical process systems via neural computation M Bhat;P.Minderman;T. J. McAvoy;N.S. Wang
  20. Int. J. Contr. v.51 no.6 Nonlinear system identification using neural networks S. Chen;S. A. Billing;P. M. Grant
  21. 18th Annual International Conference of the IEEE Engineering in Medicine and Biology Society 4.1.3-1 Adaptively trained artificial neural network identification of left ventricular assit device H. M. Kim;S. H. Kim;J. W. Ryu