CDC2000 Advances in Linear Estimation

Advances in Linear 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	H_2/H_(infinity) Signal Reconstruction in Noisy Filter Bank Systems Authors: Jingxin Zhang, Cishen Zhang, Volume: 1, Page 181 Paper number 9054 Abstract: This paper investigates signal reconstruction in the multirate filter bank systems with noisy subband paths. It casts the problem of signal reconstruction into a problem of mixed H_2/H_(infinity) control, and uses the standard results of mixed H_2/H_(infinity) synthesis to design an IIR synthesis filter bank. CD009054.PDF (From Author) TOP The Benefits Of Implicit Modelling For Predictive Control Authors: John Anthony Rossiter, Basil Kouvaritakis, L Huaccho Huatuco, Volume: 1, Page 183 Paper number 8018 Abstract: Traditionally, predictive control is understood to rely on accurate predictions in order to give good control. Here it is shown that in fact one can bypass the prediction model altogether and go straight to an implicit model which represents the parameters of the objective function to be minimised. This is demonstrated to have significant advantages. CD008018.PDF (From Author) TOP Spectral Analysis Of Segmented Data Authors: Stijn de Waele, Piet M.T. Broersen, Volume: 1, Page 189 Paper number 1110 Abstract: Time series analysis is reformulated to allow processing of segmented data. This involves the reformulation of parameter estimation and order selection. Parameter estimation for autoregressive (AR) models is done by fitting a single model to all segments simultaneously. Parameter estimation for moving average (MA) and the combined ARMA models can be derived entirely from long autoregressive models. The finite sample theory required for order selection of AR models has be generalized to segments of data. The resulting algorithm can also deal effectively with segments of unequal length. CD001110.PDF (From Author) TOP A Closed Form Solution to the Single Degree of Freedom Simultaneous Localisation and Map Building (SLAM) Problem Authors: Peter W. Gibbens, Gamini M.W.M. Dissanayake, Hugh F. Durrant-Whyte, Volume: 1, Page 191 Paper number 2152 Abstract: This paper presents a closed form solution to the estimation-theoretic simultaneous localisation and map building (SLAM) problem. The solution is obtained by explicit solution of the differential Riccati equation associated with the n-landmark SLAM problem. The solution describes and explains the many experimental and theoretical results obtained so far in the study of the SLAM problem. Further, the solution, for the first time, allows a precise means of analysing the performance of different SLAM algorithms and enables the design of efficient SLAM systems. CD002152.PDF (From Author) TOP Estimation Of Parameters In State Equations Via Multiple Observers Authors: Eiichi Muramatsu, Masao Ikeda, Volume: 1, Page 197 Paper number 2074 Abstract: A parameter estimation problem is considered for state equations of linear time-invariant systems. Under a certain condition, it is shown that the output of the system can be asymptotically described by a linear combination of output estimates which are generated by suitable multiple observers. An identification scheme for the weights of the linear combination is proposed. The obtained weights determine the parameter values to be estimated. CD002074.PDF (From Author) TOP An Iterative Method For Identification Of ARX Models From Incomplete Data Authors: Ragnar Wallin, Alf J. Isaksson, Lennart Ljung, Volume: 1, Page 203 Paper number 1856 Abstract: Identification experiments are costly for the process industry. Time when saleable products could have been manufactured is ``wasted'' on experiments. Having to discard an incomplete data set collected for identification and do a new experiment is not necessarily an acceptable option. This paper describes a very simple and intuitive algorithm to estimate parameters of ARX models from incomplete data sets. An iterative scheme involving two least squares steps and a bias correction is all that is needed. CD001856.PDF (From Author) TOP Inner Ellipsoidal Approximation of Membership Set: A Fast Recursive Algorithm Authors: Fabrizio Dabbene, Paolo Gay, Boris T. Polyak, Volume: 1, Page 209 Paper number 1066 Abstract: In robust system identification the measurement errors are usually assumed to be unknown but bounded, leading to a description of the model parameters in terms of membership set. Due to the difficulty to obtain an exact description of this set, in the past several methods have been proposed for its approximation. In this paper a fast recursive algorithm for the determination of an inner ellipsoidal approximation of the membership set is presented. CD001066.PDF (From Author) TOP