CDC2000 New Techniques for Control and Systems: Numerical Linear Algebra

New Techniques for Control and Systems: Numerical Linear Algebra
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	Robust Pole Assignment Techniques Via State Feedback Authors: Andras Varga, Volume: 1, Page 4655 Paper number 4201 Abstract: We present a unifying computational framework to solve robust pole assignment problems for linear systems using state feedback. The new framework uses Sylvester equation based parametrizations of the pole assignment problems. The non-uniqueness of solutions is exploited by minimizing additionally sensitivity of closed-loop eigenvalues and the norm of the corresponding state feedback matrix. The solution methods rely on using gradient search based minimization techniques on suitably defined cost functions. The discussion of main functional and numerical aspects reveals many desirable features of the underlying algorithms which recommend them to serve as bases for robust numerical software implementations. CD004201.PDF (From Author) TOP Multi-Input Partial Pole Placement for Distributed Parameter Gyroscopic Systems Authors: Biswa Datta, Yitshak Ram, Daniil Sarkissian, Volume: 1, Page 4661 Paper number 4203 Abstract: This paper presents a novel solution to the partial eigenvalue assignment problem of a an undamped gyroscopic distributed parameters system. The partial eigenvalue assignment problem is the problem of reassigning by feedback a few bad eigenvalues of the open-loop operator pencil while leaving the remaining infinite number of eigenvalues unchanged. The distinctive practical features of our solution are (i) it requires solution of only a small finite dimensional linear algebraic system and knowledge of only a small finite number of eigenvalues and eigenvectors of the infinite dimensional open-loop operator pencil, (ii) no spill-over occurs; that is, the remaining infinite number of eigenvalues and eigenvectors that are required to remain invariant will remain in their places and, (iii) it is obtained completely in distributed parameter setting and no discretization to second-order system of differential equations is invoked so that vital inherent properties of the original system are fully preserved. Because of the above mentioned practical features, the proposed solution is readily applicable to stabilize or to combat the effects of dangerous vibrations in a large structure. CD004203.PDF (From Author) TOP State-Space Estimation with Uncertain Data: Finite and Infinite-Horizon Results Authors: Ali H. Sayed, Volume: 1, Page 4666 Paper number 4204 Abstract: This paper develops a robust estimation procedure for state-space models with parametric uncertainties. Compared with existing robust filters, the proposed filter performs data regularization rather than de-regularization. It is shown that, under certain stabilizability and detectability conditions, the steady-state filter is stable and that, for quadratically-stable models, it guarantees a bounded error variance. CD004204.PDF (From Author) TOP Riccati Equation-Based Stabilization of Large Scale Dynamical Systems Authors: Xiang Rao, Kyle A. Gallivan, Paul van Dooren, Volume: 1, Page 4672 Paper number 4205 Abstract: In this paper we discuss the stabilization of large scale linear time invariant dynamical systems via feedback. Efficient schemes based on the Discrete Riccati Difference Equation are presented. CD004205.PDF (From Author) TOP