CDC2000 The Behavioural Approach to Systems and Control

The Behavioural Approach to Systems and Control
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	Sequential Continuous Time Adaptive Control: A Behavioral Approach Authors: Jan Willem Polderman, Volume: 1, Page 2484 Paper number 3501 Abstract: We want to design a compensator for a behavior through an appropriate behavioral interconnection. The problem is that the behavior that we want to control is not known. All that is given is a desired interconnected behavior and the prior information that this desired behavior can indeed be achieved by means of regular interconnection. This problem calls for an adaptive flavored strategy. The strategy that we propose is as follows. Measurements are taken during successive time intervals of unit length. Each time a measurement is taken the Most Powerful Unfalsified Model of that measurement and the desired behavior is determined. Since this model contains the desired behavior it is possible to find additional constraints such that the desired behavior is achieved. Moreover these additional constraints can be chosen such that the corresponding interconnection is regular relative to the true unknown behavior. This regularity property makes it possible to invoke the additional constraints in the next time interval by incorporating a transient period. The new measurement therefore satisfies these additional constraints. The procedure is repeated for the new measurement and so on. The main result is that within a finite, though unknown, number of measurements the new measurements are constrained to the desired behavior. CD003501.PDF (From Author) TOP Behavioral Interpolation For Coding And Control Authors: Margreta Kuijper, Volume: 1, Page 2488 Paper number 3502 Abstract: It is well known that classical decoding of Reed-Solomon error-correcting block codes is equivalent to system-theoretic minimal partial realization. In the first part of the paper we show how this type of decoding can also be formulated as minimal polynomial interpolation. We compare this type of interpolation with system-theoretic interpolation techniques that are used for control applications. We then present a procedure that achieves minimal polynomial interpolation by iteratively constructing a row reduced representation of an interpolating behavior. Motivated by the need for improved decoding techniques, in particular soft-decision decoding, we turn to ``list decoding'' in the second part of the paper. Here the aim is to construct a list of all codewords that are within a pre-specified Hamming distance from the received word. A connection is made with recent work in the coding-theoretic literature that performs list decoding by using bivariate interpolating polynomials. We point out that this new development opens up yet another connection between coding theory and system theory, namely the connection between list decoding and minimal multivariable interpolation. CD003502.PDF (From Author) TOP On The Relationship Between Two-Dimensional Behaviors Decompositions And The Factor Skew-Primeness Property Authors: Mauro Bisiacco, Maria Elena Valcher, Volume: 1, Page 2494 Paper number 3503 Abstract: In the last decade, the behavioral approach to dynamic systems has been fruitfully applied to the multidimensional, in particular two-dimensional (2D), context. Within the behavioral setting, several classic results that hold true for 2D state space models have found a natural generalization, among them, the autonomous/controllable decomposition, that holds true for every (linear shift-invariant) complete 2D behavior. This decomposition constitutes the straightforward, even though nontrivial, extension of the well-known "free evolution"/"forced evolution" decomposition, that holds true for every trajectory of a (linear and shift-invariant) 2D state space model. The relevance of this decomposition, which has been intensively investigated also in the context of 1D behaviors, is immediately apparent. However, while in the 1D case it is always possible to express a behavior B as a direct sum of its (uniquely determined) controllable part and of some autonomous behavior, in the two-dimensional case this is not always feasible. Nevertheless, it is always possible to obtain a decomposition in which the autonomous part has a finite-dimensional intersection with the controllable one. The aim of this paper is that of extending these results, and, in particular, those presented in a recent paper and concerned with the direct sum decomposition, to a more general setting. In fact, given a 2D complete behavior B and one of its sub-behaviors B1 we aim to investigate under what conditions a further complete behavior B2 can be found, such that B is the direct sum of B1 and B2, and the intersection of B1 and B2 is finite-dimensional autonomous. This constitutes a complete generalization of the decomposition theorem, as it represents a decomposition with "minimal intersection", in which one of the two terms is a priori fixed. Significantly enough, the possibility of obtaining such a decomposition is related to the algebraic properties of certain matrix pairs, involved in the kernel description of B and B1. CD003503.PDF (From Author) TOP Dissipative Distributed Systems Authors: Harish K. Pillai, Jan C. Willems, Volume: 1, Page 2500 Paper number 3504 Abstract: This paper deals with systems described by constant coefficient linear partial differential equations. We define dissipativity with respect to a quadratic differential form, i.e., a quadratic functional in the system variables and their partial derivatives. The main result states the equivalence of dissipativity and the existence of a storage function or of a dissipation rate. CD003504.PDF (From Author) TOP A Two-Variable Approach To Solve The Polynomial Lyapunov Equation Authors: Ralf Peeters, Paolo Rapisarda, Volume: 1, Page 2504 Paper number 3505 Abstract: A two-variable polynomial approach to solve the one-variable polynomial Lyapunov equation is put forward. Such approach yields an iterative solution method based on the method of Faddeev for the computation of matrix resolvents. The resulting algorithm is especially suitable for applications requiring symbolic or exact computation. CD003505.PDF (From Author) TOP All Unmixed Solutions of the Algebraic Riccati Equation Using Pick Matrices Authors: Harry L. Trentelman, Paolo Rapisarda, Volume: 1, Page 2510 Paper number 3506 Abstract: In this short paper we study the existence of positive and negative semidefinite solutions of the algebraic Riccati equation corresponding to linear quadratic problems with an indefinite cost functional. An important role is played by certain two-variable polynomial matrices associated with the algebraic Riccati equation. We characterize all unmixed solutions in terms of the Pick matrices associated with these two-variable polynomial matrices. As a corollary it turns out that the signatures of the extremal solutions are determined by the signatures of particular Pick matrices. CD003506.PDF (From Author) TOP