CDC2000 Model Reduction Applications

Model Reduction Applications
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	An Iterative Method For Simulation Of Large Scale Modular Systems Using Reduced Order Models Authors: Muruhan Rathinam, Linda R. Petzold, Volume: 1, Page 4630 Paper number 1738 Abstract: We describe a new iterative method for simulation of large scale modular systems using reduced order models that preserve the interconnection structure.Our technique essentially involves simulating in turn each subsystem connected to model reduced versions of the rest of the subsystems.The data from this simulation is then used to update the reduced model for that particular subsystem. We illustrate the method using a power grid example modelled by nonlinear swing equations. CD001738.PDF (From Author) TOP A Simplified Algorithm for Balanced Realization of Laguerre Network Models Authors: Quan-Gen Zhou, Edward J. Davison, Volume: 1, Page 4636 Paper number 2061 Abstract: In this paper, a simplified algorithm for constructing an internally balanced realization of a Laguerre network model is presented. Both continuous-time and discrete-time cases are treated in a unified framework. The algorithm does not require the computation of controllability and observability grammians, which makes it highly efficient, compared to existing procedures. An example is given to illustrate the method. CD002061.PDF (From Author) TOP Controllability And Stabilization Of Liquid Vibration In A Container During Transportation Authors: Stéphane Mottelet, Volume: 1, Page 4641 Paper number 11 Abstract: This paper deals with the modeling and the mathematical analysis of problems involving a rectangular container. The container is controlled via a longitudinal acceleration in order to move it from one location to another, and the key problem is the suppression of sloshing. Practical control problems involving this system have been studied, from a numerical and experimental point of view in a paper of Terashima, Schmidt and Nomura, but the mathematical analysis was not deep enough. Here we develop a suitable theoretical framework which allows us to show that approximate controllability in finite time does not hold. We also study the stability of the system when the elevation of the surface is measured at the right end of the container, and a static negative acceleration feedback is used. We show that strong stability holds (but with a non-uniform decay), although the perturbation caused by the feedback on the system operator is not dissipative in the natural topology. CD000011.PDF (From Author) TOP Large Signal Modeling of Quasi-Resonant Buck Converter Using Regulated Unified Model Authors: Che Tat Choi, Chi Kwong Li, Volume: 1, Page 4647 Paper number 1077 Abstract: This paper analyzes the large signal model of a quasi-resonant buck converter using a unified model. The internal resistance of each component in the basic quasi-resonant switch model (QRSW) is taken into consideration. The parameters can be predicted under varying supply voltage and load current. In other words, the variation of switching frequency, which is a controller parameter, can be determined while the output voltage keeps regulating. It is useful for designing an adaptive feedback controller. The power dissipation is analyzed so that the efficiency can be estimated. Moreover, the conduction loss of each component can be found. The critical component in power dissipation is known and the maximum efficiency can be predicted. CD001077.PDF (From Author) TOP A General Transform Theory Of Rational Orthonormal Basis Function Expansions Authors: Thomas J. de Hoog, Peter S.C. Heuberger, Paul M.J. van den Hof, Volume: 1, Page 4649 Paper number 1445 Abstract: In this paper a general transform theory is presented that underlies expansions of stable discrete-time transfer functions in terms of rational orthonormal bases. The types of bases considered are generated by cascade connections of stable all-pass functions. If the all-pass sections in such a network are all equal, this gives rise to the Hambo basis construction. In this paper a more general construction is studied in which the all-pass functions are allowed to be different, in terms of choice and number of poles that are incorporated in the all-pass functions. It is shown that many of the interesting properties of the so-called Hambo transform that underlies the Hambo basis expansion carry over to the general case. Especially the recently developed expressions for the computation of the Hambo transform on the basis of state-space expressions can be extended to the general basis case. This insight can for instance be applied for the derivation of a recursive algorithm for the computation of the expansion coefficients, which are then obtained as the impulse response coefficients of a linear time-varying system. CD001445.PDF (From Author) TOP