CDC2000 New Theories in Distributed Parameter Systems

New Theories in Distributed Parameter Systems
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	Spatially Localized Convolution Kernels For Feedback Control Of Transitional Flows Authors: Markus Högberg, Thomas R. Bewley, Volume: 1, Page 3278 Paper number 2008 Abstract: Optimal ((cal) H_2) linear feedback controllers are computed for the Orr--Sommerfeld/Squire equations for an array of wavenumber pairs k_x,k_z and then inverse-transformed to the physical domain, as recommended by Bewleyamp; Liu (JFM 365, 1998) and using the general method outlined therein. The feedback kernels so computed are effective at minimizing both transient energy growth and the relevant input-output transfer function norms in the controlled linear system representing small perturbations to a laminar channel flow. The important new result of the present paper is the demonstration that this calculation yields feedback convolution kernels with localized support in the physical domain. These localized kernels eventually decay exponentially with distance from the actuator location, allowing them to be truncated a finite distance from each actuator while retaining any desired degree of accuracy in the feedback computation. The truncated, spatially compact convolution kernels may then be used in decentralized control implementations on the distributed flow system. Spatial localization of (cal) H_2/(cal) H_(infinity) feedback for this type of system was predicted theoretically by Bamieh, Paganini,amp; Dahleh (IEEE TAC, submitted) and D'Andreaamp; Dullerud (IEEE TAC, submitted) in related work. Spatial localization provides the critical link which connects controllers designed for the (artificial) spatially periodic model system to application on physical systems, which are spatially evolving. Unfortunately, not all formulations of the present control problem lead to physical-space controllers with localized spatial support. The feedback convolution kernels so determined are then implemented in direct numerical simulations of transitional flows with both random and oblique finite-magnitude initial flow perturbations, per the cases of particular physical significance enumerated by Reddy et al. (JFM 365, 1998). The ability of the linear control feedback to stabilize the nonlinear flow system is demonstrated for finite initial flow perturbations with magnitudes well beyond the threshold which induces transition to turbulence in the uncontrolled system. CD002008.PDF (From Author) TOP Variable Sampling Integral Control Of Infinite Dimensional Systems Authors: Necati Özdemir, Stuart Townley, Volume: 1, Page 3284 Paper number 1689 Abstract: In this paper we present sampled-data low-gain I-control algorithms for infinite-dimensional systems in which the sampling period is not constant. The system is assumed to be exponentially stable with invertible steady state gain. The choice of the integrator gain is based on steady state gain information. In one algorithm the sampling time is divergent and in the other it increases adaptively. CD001689.PDF (From Author) TOP Robustness Of Closed-Loop Stability For Infinite Dimensional Systems Under Sample And Hold - Counterexamples Authors: Richard Rebarber, Stuart Townley, Volume: 1, Page 3290 Paper number 1977 Abstract: We consider continuous-time, linear control systems for which a static state feedback stabilizes the system. If we construct a sampled-data controller by applying an idealized sample-and-hold process to the continuous-time stabilizing feedback, it is known that if the state and control spaces are finite dimensional, then this sampled-data controller stabilizes the system for all sufficiently small sampling times. In this paper we show that this robustness with respect to sampling times is not true in general for infinite dimensional systems. We consider systems where the state space X and the control space U are Hilbert spaces, the system is of the form dx/dt = Ax + Bu, and A is the generator of a strongly continuous semigroup on X. Suppose that the continuous time feedback is u = Fx, where F is compact. Then it is known that if either B is bounded, or if A generates an analytic semigroup on X (in which case B s allowed to be unbounded in a general sense), then the sampled-data controller stabilizes the system for all sufficiently small sampling times. In this paper we show that the first condition is sharp in the following sense: we give a counterexample to show that this result is not true if B is barely unbounded, that is if B is unbounded but A^-(delta) B is bounded for all (delta) > 0. We also give an easy counterexample if F is not compact. CD001977.PDF (From Author) TOP Infinite Dimensional Models : Approximation and Realization Authors: Nicolas Guijarro, Laurent Lefèvre, Geneviève Dauphin-Tanguy, Volume: 1, Page 3295 Paper number 1897 Abstract: In this paper, we introduce a procedure to treat passive functional nodes in bond graphs. This procedure is carried out in three steps. First we approximate the initial infinite dimensional model by a finite one with huge dimension. Then we reduce it to a lower dimension model. Finally we realize this latter model by a lumped parameter electrical network. CD001897.PDF (From Author) TOP Nonlinear Analysis Of A High-Resolution Optical Wave-Front Control System Authors: Eric W. Justh, Perinkulam S. Krishnaprasad, Mikhail A. Vorontsov, Volume: 1, Page 3301 Paper number 1968 Abstract: A class of feedback systems for high-resolution optical wave-front control (or adaptive optic wave-front distortion suppression) is modeled and analyzed. Under certain conditions, the nonlinear dynamical system models obtained are shown to be gradient systems, with energy functions that also serve as Lyapunov functions. The approach taken here to a problem of nonlinear control system design and analysis might also be applicable to other problems involving high-resolution control of physical fields, particularly if the field sensing is performed optically. CD001968.PDF (From Author) TOP Automatic Tuning of Smith-Predictor Design Using Optimal Parameter Mismatch Authors: Jih-Jenn Huang, Daniel B. DeBra, Volume: 1, Page 3307 Paper number 1648 Abstract: The Smith-predictor is well known for its delay-free characteristic and suitable for regulating systems with an excessively long time delay. Previous studies have found that by introducing appropriate parametric or temporal mismatch can significantly improve system performance. In this paper, the previous theoretical results are summarized to form an automatic tuning procedure based on optimal values obtained from closed form integration solutions. The proposed procedure is verified experimentally on a fluid temperature control system of Stanford's quiet hydraulic precision lathe. Test results show good practical feasibility and deserve more real world applications. CD001648.PDF (From Author) TOP