CDC2000 Physiological Control Systems

Physiological Control Systems
Home Full List of Titles 1: Proceedings of CDC2000 Discrete Event Systems Control in Communication Systems Optimal Control and Applications I Optimisation Approaches and Methods Model Predictive Control Advances in Linear Estimation Stochastic and Uncertain Systems Nonlinear Control and Applications Nonlinear Estimation and Filtering Formation Control and its Applications New Approaches to Fuzzy Control Manufacturing Systems Automotive Applications Stability Issues in Hybrid Control Recent Advances in Stochastic Networks Optimal Control and Applications II Robust Controller Design - mu, L1 and H2 Constrained and Receding Horizon Control Identification and Control around the World Markov Decision Processes Nonlinear Optimisation Observers for Nonlinear Systems Motion Planning Neural / Fuzzy Stability and Control Motor Control Control of Quantum Phenomena I Hybrid Systems Methods Control in Communication Networks Robustness and Optimisation Bumpless Transfer, Antiwindup and Saturation Adaptive Control: Linear Systems Estimation and Closed Loop Identification Control of Markov Processes Nonlinear Filtering and Control Modelling, Identification and Validation of Nonlinear Systems Differential Geometric Control Theory for Mechanical Systems Nonlinear Output Feedback Control Pneumatics and Compression Systems Control of Quantum Phenomena II Stability of Hybrid Systems Performance Analysis in Communication Networks Adaptive Control of Nonlinear Systems LMI Methods in Design Robust Control of Time Delay Systems Subspace Identification Methods Nonlinear Stochastic Filtering and Estimation Bifurcations, Chaos and Control I New Progress in Synthesis of Nonlinear Systems I Implementation Issues of Sliding Mode Control Theory Control of Mixing in Shear Flows Novel Neural Network Control Techniques for Industrial Motion Control Systems Physiological Control Systems Optimal Control of Hybrid Systems Stochastic Models for Communication Networks Control and Stabilisation of Nonlinear Systems New Directions in Robust Control Linear Systems Theory Advanced Topics in Systems Theory Estimation in Action Bifurcations, Chaos and Control II New Progress in Synthesis of Nonlinear Systems II Numerical Design and Analysis Techniques for Nonlinear Systems Analysis and Control of Underactuated Systems Sliding Mode Control I Challenges in the Application of Control to Computer Systems Estimation and Diagnosis of Discrete Event Systems Communications and Games Optimal Control Stochastic Systems Model Reduction Methodologies Identification and Subspace Methods Applications of Nonlinear Adaptive Control Advances in Nonlinear Output Feedback Design The Behavioural Approach to Systems and Control Vision Based Estimation and Control: Recent Advances and Open Problems Agile Control of Military Operations Sliding Mode Control II Model-based Fault Diagnosis of Industrial Processes Discrete Event Systems / Petri Nets System Identification and Confidence Estimation New Approaches to H-Infinity Control I Probabilistic Approaches to Robust Control Time Delay System Stabilisation Identification Methods Controlled Stochastic Processes Output Feedback of Nonlinear Systems Topics in Nonlinear Stabilisation Mobile Robots: Tracking Control Robust Control of Nonlinear Systems Power Systems Stabilisation and Control Disk Drive Control Hybrid Control Applications Discrete Time Systems New Approaches to H-Infinity Control II Linear Systems with Saturating Actuators New Theories in Distributed Parameter Systems Applications of Estimation and Identification Stochastic Control and Tuning Methodologies Control of Nonlinear Systems Iterative Learning and Control Coordinating Robot Systems Nonlinear Time Varying Systems Novel Applications of Neural Networks Aerospace Applications Switched Systems Implicit and Descriptor Systems LQG Periodic Systems and Disturbances New Horizons for Distributed Parameter Systems State Estimation Learning and Neuro-Control Nonlinear Control and Stabilisation I Tracking Vision Servoing Controllability of Nonlinear Systems Control of Flexible Systems Electro-Mechanical Systems Robust Control Methods and Applications Fault Detection and Diagnosis Optimisation and Applications Robust Stability Analysis Numerical Methods in Control Filtering in Continuous Time Stochastic Systems Interplay between Control and Signal Processing Fault Detection and Analysis Nonlinear Dynamical Systems Nonlinear Time Delay Systems Computational Issues in Nonlinear Control Disturbance Rejection Process Control Industry Applications Linear Parameter Varying Systems Linear Control Systems Dynamic and Nonlinear Programming Model Reduction Applications New Techniques for Control and Systems: Numerical Linear Algebra Estimation and Identification using Hidden Markov Models Applications of Stochastic Control Topics in Linear Design Nonlinear Control and Stabilisation II Ambulatory Robot Systems Chaotic and Oscillatory Systems Biomedical System Control Integrated Control and CPU Scheduling Linear Design Techniques Adaptive Disturbance / Noise Compensation Nonlinear Model Predictive Control Sensitivity Design, Analysis and Limitations Analysis of Linear Systems Linear Matrix Inequalities in Design Lyapunov's 2nd Method Robotics: Tracking Control Lagrangian and Hamiltonian Theory Variable Structure Control Machine Vision Signal Processing Methods in Control Applied Nonlinear Control Author Index A B C D E F G H I J K L M N O P Q R S T U V W X Y Z	Control of Arm Movement Using Population of Neurons Authors: Zoran Nenadić, Bijoy K. Ghosh, Volume: 1, Page 1776 Paper number 2401 Abstract: Movements of human arm in a horizontal plane are very stereotyped in the sense that the corresponding paths are mainly straight lines and the velocity profiles are ``bell-shaped like'' functions. A dynamics of two link model of the human arm has been studied with the goal of synthesizing the torques which accomplish the desired transfer. For that purpose a set of parameters which describes the desired transition (initial position, final position, peak velocity, etc.) is chosen randomly according to a certain distribution. The parameters of the desired trajectory as well as the system variables (angles and angular velocities) are encoded using populations of different number of neurons, usually 100-150. The underlying mathematics including integration, differentiation and other algebraic relationships, has been done at the level of neuronal activity. Finally, the driving torques are generated from the corresponding activities using an optimal decoding rule. CD002401.PDF (From Author) TOP Optimal Vaccination Strategies for the Control of Epidemics in Highly Mobile Populations Authors: Petter Ögren, Clyde F. Martin, Volume: 1, Page 1782 Paper number 2503 Abstract: Our goal is to calculate optimal vaccination patterns for a rapidly spreading disease in an urbanized highly mobile population. The goal being to determine if vaccination can effect a disease for which there is low immunity in the population. Different types of structured SIR models are investigated. We construct a model appropriate for a traveling urbanized population and introduce a control in terms of a vaccination program. Linear constraints, a quadratic cost on the control and a linear cost on the number of infected are imposed. In this setting we calculate optimal vaccination patterns using the maximum principle of Pontryagin. CD002503.PDF (From Author) TOP A Hybrid Approach to Stress Analysis in Skeletal Systems Authors: Alan Barhorst, Lawrence Schovanec, Volume: 1, Page 1788 Paper number 2501 Abstract: This paper provides a continuum analysis of skeletal elastic structures in which loading conditions are derived from neural-musculotendon dynamics. Forward dynamic simulations of human motion are based on an ensemble of articulating segments controlled by Hill-type musculotendon actuators. The joint torques and reaction forces as predicted by this analysis determine loading conditions for the stress analysis of the segmental links which are modeled as hybrid parameter systems. This approach accounts for both the rigid body motions of the articulating links and the elastic deformations that represent the continuum effects in the bone. Although the methods in this paper are readily extended to general multi-link segmental models, simulations for the arm-shoulder complex are presented in order to illustrate the method. CD002501.PDF (From Author) TOP Control of Pursuit Eye Movement Authors: Manjula S. Sugathadasa, Wijesuriya P. Dayawansa, Clyde F. Martin, Volume: 1, Page 1793 Paper number 2404 Abstract: A dynamic model representing the pursuit eye movement is studied here. It is known that feedback control is used in this type of eye movement. A representative feedback control law is designed and simulations are carried out to demonstrate its effectiveness. CD002404.PDF (From Author) CD002404.PDF (Scanned) TOP Minimally Invasive Identification of Ventricular Recovery Index for Weaning Patient From Artificial Heart Support Authors: Yih-Choung Yu, J. Robert Boston, Marwan A. Simaan, James F. Antaki, Volume: 1, Page 1799 Paper number 2504 Abstract: Maximum ventricular elastance, E_MAX, is a reliable quantitative index of the contractial state of the ventricle. It is a strong candidate to determine the healthy status of the patient's heart. However, estimating E_MAX usually requires invasive pressure and flow sensors, which only can be performed under certain clinical facility. If an indirect index of E_MAX can be identified using measurements from a ventricular assist device (VAD) without any indwelling sensor, this would facilitate an effective way to monitor the healthy condition of the patient's heart while the patient is under VAD support. This index can also be used to control the VAD to gradually wean the patient from the mechanical circulatory support. In this paper, three possible indices, systemic vascular resistance, maximum VAD inflow acceleration rate, and the maximum VAD inflow acceleration rate during heart ejection, were evaluated as a representation of E_MAX using Novacor VAD volume and mean arterial pressure measurements from a computer simulation. The maximum VAD inflow acceleration rate during heart systole showed a strong correlation to the E_MAX regardless the variation of native heart rate, and thus can be used as an E_MAX index. CD002504.PDF (From Author) TOP Classification of Electrocardiographic P-Wave Morphology Authors: Jonas Carlson, Rolf Johansson, S. Bertil Olsson, Volume: 1, Page 1804 Paper number 2505 Abstract: The atrial activity of the human heart is normally visible in the ECG as a P-wave. In patients with intermittent atrial fibrillation, a different P-wave morphology can sometimes be seen, indicating atrial conduction defects. The purpose of this study was to develop a method to discriminate between such P-waves and normal ones. 20 recordings of each type were used in a classification which, based on impulse response analysis of the P-wave and linear discrimination between various parameters, produced a correct classification in 37 of the 40 recordings (sensitivity 95%, specificity 90%). CD002505.PDF (From Author) TOP