CDC2000 Applications of Estimation and Identification

Applications of Estimation and Identification
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	System Identification Using Nonlinear Filtering Methods with Applications to Medical Imaging Authors: Jing Yin, Vassilis L. Syrmos, David Y.Y. Yun, Volume: 1, Page 3313 Paper number 1721 Abstract: In this paper, we first review the concept of computational tomography (CT) and laser technique using the photon diffusion equation. The forward and the inverse problem are two key problems concerned with the diffusion equation, while the solution to the later one is the goal of research in optical CT. The inverse problem can be stated as follows: given the photon density measured from the detectors outside the tissue, we need to find the anomalies (benign or malignant) inside the tissue. We model the forward and the inverse problem using state-space equations and pose the inverse problem as a system identification problem. The nonlinear filtering techniques, namely the extended Kalman filter and the second order filter are proposed to solve the inverse problem. Comparisons are made through an example of a medical imaging problem. CD001721.PDF (From Author) TOP Coprime Factor Based Closed-Loop Model Validation Authors: Raymond A. de Callafon, Volume: 1, Page 3319 Paper number 9125 Abstract: In order to bridge the gap between models used in robust control synthesis and uncertainty models obtained from identification experiments, model validation techniques can be used. An uncertainty model needs to be validated or invalidated to ensure the quality of the model and the robustness of the controller being designed on the basis of the model. In this paper, a model validation approach is presented that (in)validates uncertainty models in view of a model based control design. This is done by considering a closed-loop model validation technique which generalizes the (in)validation of possibly unstable models on the basis of closed-loop experiments with a stabilizing, but possibly unstable, controller. The approach is presented in a robust control framework with an uncertainty model described by coprime factor perturbations. It is shown that this approach yields an affine expression of the uncertainty model in all possible transfer functions that can be measured via a closed-loop experiments. This property facilitates an affine optimization to solve the closed-loop model invalidation problem. CD009125.PDF (From Author) TOP On Algorithms For Attitude Estimation Using GPS Authors: Assaf Nadler, Itzhack Y. Bar-Itzhack, Haim Weiss, Volume: 1, Page 3321 Paper number 27 Abstract: This paper discusses algorithms for attitude determination using GPS differential phase measurements, assuming that the cycle integer ambiguities are known. The problem of attitude determination is posed as a parameter optimization problem where a new quaternion-based cost function is used. Unlike the cost function associated with the vectorized measurements, the new cost function is not a simple quadratic form and therefore Davenport's q-Method is not applicable in this case. Three algorithms for finding the optimal quaternion are derived, two of which are discrete. The third one is a continuous version of the Newton-Raphson algorithm. This continuous version is new and has a guaranteed exponential convergence to the closest local minimum located on the gradient direction in regions where the associated Hessian matrix is positive definite. The algorithms presented in this paper can handle cases of planar antenna arrays and thus cover a deficiency in earlier algorithms. The efficiency of the new algorithms is demonstrated through numerical examples. CD000027.PDF (From Author) TOP Wavelets And Variance Reduction In Non-Parametric Transfer Function Estimation Authors: Sippe G. Douma, Thomas J. de Hoog, Paul M.J. van den Hof, Volume: 1, Page 3327 Paper number 1120 Abstract: A variance reduction scheme is presented for non-parametric transfer function estimators based on the use of wavelets as an alternative to the traditional spectral windowing. The latter can be generalized into a variance reduction method based on thresholding (omitting or altering) the coefficients of an orthogonal series expansion of the estimator to be smoothed. Crucial is the choice of threshold level, distinguishing between coefficients related predominantly to estimation errors and those associated with the underlying true function. The standard wavelet threshold operation with a constant or level-dependent threshold can not be applied to wavelet coefficients of spectral density functions. The nonstationarity in the statistical properties of these estimators reveals itself in the wavelet domain as significant peaks. An efficient threshold level should follow the standard deviation of each wavelet coefficient. New exact expressions of the standard deviation are presented, using the fact that we are dealing with functions associated with linear time invariant systems. An estimator based on these expressions proves to provide an appropriate threshold level. CD001120.PDF (From Author) TOP 'Unobserved' Monte Carlo Method for Identification of Partially Observed Nonlinear State Space Systems, Part II: Counting Process Observations Authors: Victor Solo, Volume: 1, Page 3331 Paper number 1358 Abstract: We present a simple simulation method for generating an approximate likelihood function for fitting partially observed (with counting process observations) nonlinear stochastic differential equations. We also discuss use of the method to generate approximate maximum likelihood estimators. We also mention methods based on density evolution equations. CD001358.PDF (From Author) TOP Optimal Fault Tolerant Control of Flexure Jointed Hexapods for Applications Requiring Less than Six Degrees of Freedom Authors: Xiaochun Li, John E. McInroy, Jerry C. Hamann, Volume: 1, Page 3337 Paper number 1518 Abstract: When less than 6 degrees-of-freedom (DOF's) are required (in precision pointing tasks, for example), the kinematic redundancy of a Stewart platform (or hexapod) makes it possible to implement fault tolerant algorithms. When one or several of the platform legs (struts) fail, methods are presented in this paper for finding a new, reconfigured control to maintain performance. CD001518.PDF (From Author) TOP Random Spherical Uncertainty in Estimation and Robustness Authors: Boris T. Polyak, Pavel S. Shcherbakov, Volume: 1, Page 3339 Paper number 1113 Abstract: A theorem is formulated that gives an exact probability distribution for a linear function of a random vector uniformly distributed over a ball in n-dimensional space. This mathematical result is illustrated via applications to a number of important problems of estimation and robustness under spherical uncertainty. These include parameter estimation, characterization of attainability sets of dynamical systems, and robust stability of affine polynomial families. CD001113.PDF (From Author) TOP