CDC2000 State Estimation

State Estimation
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	The Problem of Optimal Robust Sensor Scheduling Authors: Andrey V. Savkin, Robin J. Evans, Efstratios Skafidas, Volume: 1, Page 3791 Paper number 1250 Abstract: This paper considers the sensor scheduling problem which consists of estimating the state of an uncertain process based on measurements obtained by switching a given set of noisy sensors. The noise and uncertainty models considered in this paper are assumed to be unknown deterministic functions which satisfy an energy type constraint known as an integral quadratic constraint. The problem of optimal robust sensor scheduling is formulated and solution to this problem is given in terms of the existence of suitable solutions to a Riccati differential equation of the game type and a dynamic programming equation. Furthermore,a real time implementable method for sensor scheduling is also presented. CD001250.PDF (From Author) CD001250.PDF (Scanned) TOP Observability For Linear Systems With Unknown Inputs Authors: Cyrille Aboky, Jean-Claude Vivalda, Volume: 1, Page 3797 Paper number 9026 Abstract: In this note we give a characterization of observability for a class of linear systems with unknown inputs. CD009026.PDF (From Author) TOP Analysis Of Recursive MAP Algorithm For State Estimation Of Bilinear Systems Authors: Vikram Krishnamurthy, George Yin, Volume: 1, Page 3799 Paper number 1797 Abstract: This paper derives and analyses a recursive algorithm for maximum aposteriori (MAP) state estimation of partially observed bilinear systems. The recursive algorithm is based on cross-coupling two Kalman filters, one for each component of the bilinear system. CD001797.PDF (From Author) TOP Stability of Receding Horizon Kalman Filter in State Estimation of Linear Time-Varying Systems Authors: João B.R. do Val, Eduardo F. Costa, Volume: 1, Page 3801 Paper number 1950 Abstract: The paper presents a state predictor for linear time-varying systems using Kalman filter with the receding horizon strategy. It can be seen as a standard Kalman filter which takes into account the most recent data, those included in a moving data window of fixed length. The main purpose here is to assure stability for this type of filter. Under standard conditions we can establish a minimum horizon length for which the closed-loop filter with the receding horizon gain is exponentially stable. The approach makes no direct reference to the properties of the underlying Riccati equation, which allow us to address more general problems that can not be coined in terms of Riccati equations. CD001950.PDF (From Author) CD001950.PDF (Scanned) TOP Optimal and Self-Tuning State Estimation for Singular Stochastic Systems: A Polynomial Equation Approach Authors: Huanshui Zhang, Lihua Xie, Yeng Chai Soh, Volume: 1, Page 3807 Paper number 1537 Abstract: This paper is concerned with the optimal steady-state estimation for singular stochastic discrete-time systems using a polynomial equation approach. The key to the optimal estimation is to calculate an optimal estimator gain matrix. The main contribution of the paper is to present a simple method for computing the gain matrix. Our method involves solving one simple polynomial equation which is derived based on the uniqueness of the ARMA innovation model. The approach covers the prediction, filtering and smoothing problems. Further, when the noise statistics of model are not available, self-tuning estimation is performed by identifying one ARMA innovation model. CD001537.PDF (From Author) TOP Robust Kalman Filter Design Authors: Xing Zhu, Yeng Chai Soh, Lihua Xie, Volume: 1, Page 3813 Paper number 1392 Abstract: In this paper, the problem of finite and infinite horizon robust Kalman filtering for uncertain discrete-time systems is studied. The system under consideration is subject to time-varying norm-bounded parameter uncertainty in both the state and output matrices. The problem addressed is the design of linear filters having an error variance with a guaranteed upper bound for any allowed uncertainty. A novel technique is developed for robust filter design. This technique gives necessary and sufficient conditions to the design of robust filters over finite and infinite horizon. CD001392.PDF (From Author) TOP Analysis of Least-Squares State Estimators for a Harmonic Oscillator Authors: Michael P Bask, Alexander Medvedev, Volume: 1, Page 3819 Paper number 1870 Abstract: The concept of least-squares observer is revisited. Robustness properties of this class of observers with respect to norm-bounded measurement noise are investigated and shown to be very much dependent on the operator chosen for the observer implementation. For the case of a harmonic oscillator, an explicit observer parameterization in terms of the implementation operator and the oscillator frequency is obtained, observer's existence conditions are proven and analyzed. CD001870.PDF (From Author) TOP