CDC2000 Stochastic Systems

Stochastic 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	Stability Preserving Mappings For Stochastic Dynamical Systems Authors: Ling Hou, Anthony N. Michel, Volume: 1, Page 2335 Paper number 1143 Abstract: In the present paper we first formulate a general model for stochastic dynamical systems that is suitable in the stability analysis of invariant sets. This model is sufficiently general to include as special cases most of the stochastic systems considered in the literature. We then adapt several existing stability concepts to this model and we introduce the notion of stability preserving mapping of stochastic dynamical systems. Next, we establish a result which ensure that a function is a stability preserving mapping, and we use this result in proving a Comparison Stability Theorem for general stochastic dynamical systems. We apply the Comparison Stability Theorem in the stability analysis of dynamical systems determined by Ito differential equations. CD001143.PDF (From Author) TOP A Remark On The Design Of Time--Varying Stabilizers For Stochastic Differential Systems Without Unforced Dynamics Authors: Patrick A. Florchinger, Volume: 1, Page 2341 Paper number 9017 Abstract: The purpose of this paper is to extend to stochastic differential systems without unforced dynamics the stabilization techniques for controllable driftless systems developed by Pomet. CD009017.PDF (From Author) TOP Moment Stability Of Pulse-Width-Modulated Feedback Systems Subjected To Random Disturbances Authors: Ling Hou, Anthony N. Michel, Volume: 1, Page 2343 Paper number 1059 Abstract: We study the stability properties of pulse-width-modulated (PWM) feedback systems with stable plants, subjected to multiplicative and additive random disturbances (modeled by the derivative of a Wiener process). We show that when the parameters of the pulse-width modulator are within a computable range and the random disturbances are sufficiently small, then the PWM feedback system is globally asymptotically stable in the pth mean. We also show that in the presence of additive disturbances, such PWM feedback systems are bounded in the pth mean for arbitrarily large disturbances. CD001059.PDF (From Author) TOP Lyapunov Coupled Equations for Infinite Jump Linear Systems Authors: Marcelo D. Fragoso, Jack Baczynski, Volume: 1, Page 2349 Paper number 1673 Abstract: This paper deals with Lyapunov equations for continuous-time Markov jump linear systems (MJLS). Out of the bent which wends most of the literature on MJLS, we focus here on the case in which the Markov chain has a countably infinite state space. It is shown that the infinite MJLS is stochastically stabilizable (SS) if and only if the associated countably infinite coupled Lyapunov equations have a unique norm bounded strictly positive definite solution. It is worth mentioning here that this result do not hold for mean square stabilizability (MSS), since SS and MSS are no longer equivalent in our set up. To some extent,tools from operator theory in Banach space and, in particular, from semigroup theory are the very technical underpinning of the paper. CD001673.PDF (From Author) TOP On the Detectability and Observability of Discrete-Time Markov Jump Linear Systems Authors: Eduardo F. Costa, João B.R. do Val, Volume: 1, Page 2355 Paper number 1942 Abstract: This paper presents a new detectability concept for discrete-time Markov jump linear systems with finite Markov state, which generalizes the MS-detectability concept found in the literature. The new sense of detectability can similarly assure that the solution of the coupled algebraic Riccati equation associated to the quadratic control problem is a stabilizing solution. In addition, the paper introduces a related observability concept which also generalizes previous concepts. Tests for detectability or observability are derived from the corresponding definitions, that can be performed in a finite number of steps. An illustrative example is included to show that a system may be detectable in the new sense but not in the MS sense. CD001942.PDF (From Author) CD001942.PDF (Scanned) TOP A Unified Approach for Mean Square Stability of Continuous-Time Markovian Jumping Linear Systems with Additive Disturbances Authors: Marcelo D. Fragoso, Oswaldo L.V. Costa, Volume: 1, Page 2361 Paper number 2013 Abstract: Necessary and sufficient conditions for mean square stability(MSS) of continuous-time linear systems subject to Markovian jumps in the parameters and additive disturbances are established. We consider two scenarios regarding the additive disturbances: the one in which the system is driven by a Wiener process, and the one characterized by functions in L2, which is the usual scenario for the H-Infinity approach. For both cases it is shown that MSS is equivalent to asymptotic wide sense stationarity (AWSS), to the spectrum of an augmented matrix lying in the open left half plane, and to the existence of a solution for a certain Lyapunov equation. Furthermore, it is proved that the Lyapunov equation can be written down in two equivalent forms with each one providing an easier-to-check sufficient condition. It is also shown that MSS is equivalent to the state x(t) belonging to L2 whenever the disturbances are in L-2. These results provide, inter alia, a flexible theory, in a unified basis, for MSS of continuous-time Markovian jump linear systems. CD002013.PDF (From Author) TOP