Cuff Dynamics System Analysis and Modeling

This thesis investigates the properties of the cuff dynamics system. The approach used has been to first build up a linear model for the cuff dynamics system. Analysis of the results shows that the linear model can only hold over a very small operating range, the conclusion is drawn that the cuff dynamics system exhibits strong non-linearity. An artificial neural network then is proposed to model the non-linear cuff dynamics system. Mathematical analysis of the results shows that the model structure provides a better representation of the system dynamics. Two experiments are designed to capture the non-linearity of the cuff dynamics system using a NNARX neural network model. The single operating point of cuff dynamics approximation and the multiple operating point cuff dynamics approximation. A second order with one zero model is chosen as the best representation. The result of the simulations shows that it is not appropriate to use the cuff as sensor in the blood pressure measurement without considering the behaviour of the cuff. The cuff dynamics shows strongly non-linear properties, which contribute a lot to the whole blood pressure measurement.

Cuff Dynamics System Analysis and Modeling

This thesis investigates the properties of the cuff dynamics system. The approach used has been to first build up a linear model for the cuff dynamics system. Analysis of the results shows that the linear model can only hold over a very small operating range, the conclusion is drawn that the cuff dynamics system exhibits strong non-linearity. An artificial neural network then is proposed to model the non-linear cuff dynamics system. Mathematical analysis of the results shows that the model structure provides a better representation of the system dynamics. Two experiments are designed to capture the non-linearity of the cuff dynamics system using a NNARX neural network model. The single operating point of cuff dynamics approximation and the multiple operating point cuff dynamics approximation. A second order with one zero model is chosen as the best representation. The result of the simulations shows that it is not appropriate to use the cuff as sensor in the blood pressure measurement without considering the behaviour of the cuff. The cuff dynamics shows strongly non-linear properties, which contribute a lot to the whole blood pressure measurement.

An Adaptive Fuzzy H∞ Synergetic Approach to Robust Control

Robust control often requires some adaptive approach in evaluating systems dynamics to handle parameters variations and external disturbances. Therefore, an error due to dynamics approximation is inevitably added to uncertainties already present in the model. This issue is addressed in this paper, through the combination of two robust techniques, Hinf and synergetic control. These latter are used to ensure reducing tracking error in the overall closed-loop system while guaranteeing stability via Lyapunov synthesis. With the aim of handling parameters variations, an indirect adaptive fuzzy scheme is used to elaborate system model. Simulation studies are conducted to assess the proposed approach on two practical systems, and the results are compared to a sliding mode proportional integral (PI)-based technique. It is to be noted that a large class of systems depicted as control affine systems will be considered in this paper. An induction motor and an inverted pendulum representing, respectively, a linear and a nonlinear system are utilized in this study showing improvement due to the suggested approach, in overall performance over its sliding mode control counterpart.

The Mean Air Flow as Lagrangian Dynamics Approximation and Its Application to Moist Convection

This paper introduces the Mean Airflow as Lagrangian Dynamics Approximation (MAFALDA), a new method designed to extract thermodynamic cycles from numerical simulations of turbulent atmospheric flows. This approach relies on two key steps. First, mean trajectories are obtained by computing the mean circulation using height and equivalent potential temperature as coordinates. Second, thermodynamic properties along these trajectories are approximated by using their conditionally averaged values at the same height and θe. This yields a complete description of the properties of air parcels that undergo a set of idealized thermodynamic cycles. MAFALDA is applied to analyze the behavior of an atmosphere in radiative–convective equilibrium. The convective overturning is decomposed into 20 thermodynamic cycles, each accounting for 5% of the total mass transport. The work done by each cycle can be expressed as the difference between the maximum work that would have been done by an equivalent Carnot cycle and a penalty that arises from the injection and removal of water at different values of its Gibbs free energy. The analysis indicates that the Gibbs penalty reduces the work done by all thermodynamic cycles by about 55%. The cycles are also compared with those obtained for doubling the atmospheric carbon dioxide, which in the model used here leads to an increase in surface temperature of about 3.4 K. It is shown that warming greatly increases both the energy transport and work done per unit mass of air circulated. As a result, the ratio of the kinetic energy generation to the convective mass flux increases by about 20% in the simulations.