CDC2000 Computational Issues in Nonlinear Control

Computational Issues in Nonlinear 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	Computational Performance Analysis Of Nonlinear Dynamic Systems Using Semi-Infinite Programming Authors: Tor Arne Johansen, Volume: 1, Page 4436 Paper number 1409 Abstract: For nonlinear systems that satisfy certain regularity conditions it is shown that upper and lower bounds on the performance (cost function) can be computed using linear or quadratic programming. The performance conditions derived from Hamilton-Jacobi inequalities are formulated as linear inequalities defined pointwise by discretizing the state-space when assuming a linearly parameterized class of functions representing the candidate performance bounds. Uncertainty with respect to some system parameters can be incorporated by also gridding the parameter set. In addition to performance analysis, the method can also be used to compute Lyapunov functions that guarantees uniform exponential stability. CD001409.PDF (From Author) TOP Numerical Computation Of State Feedback Controllers For Systems With Persistent Outputs Authors: Peter M. Dower, Volume: 1, Page 4442 Paper number 1798 Abstract: In this paper, we consider the problem of computing a state feedback controller for a class of nonlinear plants without requiring asymptotic stability of the resulting closed loop system. A simple generalization of the L2-gain inequality which permits persistent outputs is used as the objective in the control design. By considering notions of dissipation and available storage, the controller can be computed by solving a Hamilton-Jacobi-Bellman-Isaac PDE. Although this PDE rarely admits analytical solutions, finite differences may be applied to compute an approximation to both the available storage and the desired state feedback controller. Due to problems with convergence of conventional Jacobi value space iterations, a mixed policy space / value space algorithm is applied. CD001798.PDF (From Author) TOP Approximate Inversion of Hysteresis: Theory and Numerical Results Authors: Ram Venkataraman, Perinkulam S. Krishnaprasad, Volume: 1, Page 4448 Paper number 2089 Abstract: In previous work, we had proposed a low (6) dimensional model for a thin magnetostrictive actuator that was suitable for real-time control. One of the main results of this modeling effort was the separation of the rate-independent hysteretic effects from the rate-dependent linear effects. The hysteresis phenomenon may also be captured by a (modified) Preisach operator with the average magnetic field as the input. If one can find an inverse for the Preisach operator, then the composite system can be approximately linearized. In this paper, we propose a new algorithm for computation of the inverse for the classical Preisach model. Prior approaches depended on the linearization of the operator at the operating point. As numerical differentiation is involved, this approach can cause divergence. Our algorithm does not linearize the Preisach operator, but makes use of its strictly incrementally increasing property. Convergence of the algorithm is proved using the contraction mapping principle. CD002089.PDF (From Author) TOP On the Simulation-Supported Design of Logic Controllers for Known Dynamic Systems Authors: Jure Medanic, Albert Pfleger, Volume: 1, Page 4455 Paper number 62 Abstract: The paper presents a methodological procedure for systematically exploiting the information on the dynamics of the response as observed through simulations to expand the region of attraction of a nominal design. A particular novelty is that an integral state is added to state feedback in each region of the partition to provide a mechanism so that the state is driven towards the desired equilibrium point at the origin. CD000062.PDF (Scanned) TOP A Time-Stepping Method For Relay Systems Authors: W.P.M.H. Heemels, M.K. Çamlibel, J.M. Schumacher, Volume: 1, Page 4461 Paper number 1653 Abstract: In this paper we will analyze a time-stepping method for the numerical simulation of dynamical systems containing Coulomb friction or relay characteristics. Time-stepping techniques replace the original dynamical system by a sequence of algebraic problems, that have to be solved for each time-step. For relay systems the one-step problem can be reformulated as a linear complementarity problem for which a wide range of solution algorithms already exists. As the event times at which the relay switches are ``overstepped,'' the consistency of the method in the sense of the convergence of a sequence of approximations to an actual solution of the relay system can be put into question. However, in this paper we show that the proposed method is consistent even in the case that the event times accumulate (Zeno behavior). By an example we will illustrate how the method deals with Zeno trajectories. CD001653.PDF (From Author) TOP A Computational Approach To Approximate Input/State Feedback Linearization Authors: Tor Arne Johansen, Kenneth J Hunt, Volume: 1, Page 4467 Paper number 1405 Abstract: We propose a novel computational approach to the approximate input/state feedback linearization problem by interpolating a finite number of local linear coordinate transforms and static state feedback designs. For a class of single-input nonlinear systems, the approximate approach allows the main assumptions underlying exact input/state feedback linearization (involutivity, smoothness and controllability everywhere) to be relaxed. Moreover, the present approach relies only on simple numeric linear algebraic computations, in strong constrast to the exact input/state feedback linearization approach that relies on the solution of a partial differential equation and other symbolic computations. In contrast to related approaches to approximation feedback linearization, the feedback design need not be restricted to a neighborhood of the equilibrium manifold. It is shown that the approximation error goes to zero uniformly as the resolution of the state space partitioning increases. Explicit expressions for the approximation error allows the accuracy and robustness of the design to be assessed. CD001405.PDF (From Author) TOP Shape Design Of Channel Flows For Steady, Incompressible Flows Authors: Max D. Gunzburger, Hong-Chul Kim, Sandro Manservisi, Volume: 1, Page 4473 Paper number 9 Abstract: A shape design problem for stationary, viscous, incompressible, two-dimensional channel flows is considered. The shape of part of the boundary is determined so that the viscous drag is minimized. The adjoint equation method is used to derive an optimality system and the shape gradient of the design functional. CD000009.PDF (From Author) TOP