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Application of Nonlinear Control Methods in Central Nervous System for Respiratory Organs

Shahnazari, Hadi | 2013

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 44347 (06)
  4. University: Sharif University of Technology
  5. Department: Chemical and Petroleum Engineering
  6. Advisor(s): Bozorgmehri, Ramin
  7. Abstract:
  8. Due to continuous improvements in manufacturing and the fact that modern technologies such as microprocessors, are becoming more efficient along the rapid growth of nonlinear control methods usage, the application of these two tools together has entered various fields of biomedical engineering, particularly neural prostheses. In this study, the methods of analysis and control of nonlinear systems were used to investigate and improve the behavior of the neural breathing system on the basis of Hodkgin-Huxley model as the original model of the neuron. Using the principles of differential geometry and robust control methods – based on combination of exact input-output linearization ideas, sliding mode and controller design via the Lyapunov function – a comprehensive robust control strategy to control the frequency and amplitude of neural models, specifically respiratory neural models, has been proposed. A non-linear Luenberger-like observer based on exact input-output linearization was used in order to estimate the states of the system. The behavior of the neural system controlling respiration while interacting with respiratory system has been investigated via an integrated model using artificial neural network with detail and complexity consistent with physiological data. The results of the application of robust control design for an integrated model of recovery, indicates improvement, based on respiratory rhythm, in the metabolic behavior of the respiratory system
  9. Keywords:
  10. Nervous System ; Respiratory System ; Robust Control ; Exact Linearization ; Input-Output Linearization ; Artificial Neural Network ; Hodkgin-Huxley Model

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