CDC2000 Tracking

Tracking
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	A Fake Algebraic Riccati Technique For Tracking Superimposed Signals Authors: Garry A. Einicke, Langford B. White, Robert R. Bitmead, Volume: 1, Page 3887 Paper number 1538 Abstract: This paper describes an adaptive nonlinear filter for tracking superimposed signals. The filter gain is selected via a fake algebraic Riccati equation. A passivity approach is applied to deduce stability conditions for the filter error system. The performance is compared with an extended Kalman filter for tracking multiple frequency modulated signals. CD001538.PDF (From Author) TOP Auxiliary Particle Filters for Tracking a Maneuvering Target Authors: Rickard Karlsson, Niclas Bergman, Volume: 1, Page 3891 Paper number 1642 Abstract: We consider the recursive state estimation of a highly maneuverable target. In contrast to standard target tracking literature we do not rely on linearized motion models and measurement relations, or on any Gaussian assumptions. Instead, we apply optimal recursive Bayesian filters directly to the nonlinear target model. We present novel sequential simulation based algorithms developed explicitly for the maneuvering target tracking problem. These Monte Carlo filters perform optimal inference by simulating a large number of tracks, or particles. Each particle is assigned a probability weight determined by its likelihood. The main advantage of our approach is that linearizations and Gaussian assumptions need not be considered. Instead, a nonlinear model is directly used during the prediction and likelihood update. Detailed nonlinear dynamics models and non-Gaussian sensors can therefore be utilized in an optimal manner resulting in high performance gains. In a simulation comparison with current state-of-the-art tracking algorithms we show that our approach yields performance improvements. Moreover, incorporation of physical constraints with sustained optimal performance is straightforward, which is virtually impossible to incorporate for linear Gaussian filters. With the particle filtering approach we advocate these constraints are easily introduced and improve the results. CD001642.PDF (From Author) TOP Stability of the Modified Probabilistic Data Association Filter: Lyapunov Function Based Analysis Authors: Yong Shik Kim, Keum Shik Hong, Volume: 1, Page 3896 Paper number 1580 Abstract: The probabilistic data association filter (PDAF) is known to provide better tracking performance than the standard Kalman filter (KF) in a cluttered environment. In this paper, the stability of the modified PDAF of Fortmann et al. [7], in the presence of uncertainties with regard to the origin of a measurement, is investigated. The modified Riccati equation derived by approximating two random terms with their expectations is used to prove the stability of the modified PDAF. A new Lyapunov function based approach, which is different from the quantitative evaluation of Li and Bar-Shalom [17], is pursued. With the assumption that the system and observation noises are bounded, specific tracking error bounds are established. CD001580.PDF (From Author) TOP Synthesis of Reduced Order Multivariable Feedback Tracking Controllers Using the Q-Parameterization Authors: Matthew Bement, Suhada Jayasuriya, Volume: 1, Page 3902 Paper number 1046 Abstract: In this paper we consider the problem of multivariable tracking for stable plants. Specifically, a new method is proposed for constructing a feedback controller which, for certain cases, is of lower order than the controller constructed via the classical robust servomechanism method. Viewed from a tracking standpoint, the servomechanism method results in what may be considered an overdesign. For example, in a two input, two output system, where the first reference input is a step and the second reference input is a sinusoid of a known frequency, w, the controller obtained via the classical robust servomechanism method allows each output to track a reference input which is of the form A+B sin(wt). For many applications, this may not be necessary. As will be shown, the reduced order controller, which is obtained by carefully designing the Q-parameter, does not exhibit this behavior. An example of a two input, two output system is given to illustrate the method. CD001046.PDF (From Author) TOP Control Of Waveforms And Detection Thresholds For Optimal Target Tracking In Clutter Authors: Sun-Mog Hong, Robin J. Evans, Han-Seop Shin, Volume: 1, Page 3906 Paper number 1030 Abstract: An optimization problem is formulated to obtain the combined sequence of waveform parameters (pulse amplitudes and lengths, and FM sweep rates) and detection thresholds for optimal target tracking in clutter. The optimal combined sequence minimizes a tracking performance index that is a function of the probability of track loss and the estimation accuracy. A measurement model is also developed based on the resolution cell in the delay-Doppler plane for a Gaussian pulse. CD001030.PDF (From Author) TOP Optimal Tracking With Fixed Order Controllers Authors: Mark E. Halpern, Boris T. Polyak, Volume: 1, Page 3908 Paper number 1572 Abstract: For discrete-time scalar systems, we propose an approach for designing feedback controllers of fixed order to minimize an upper bound on the peak magnitude of the tracking error to a given command input. The work makes use of linear programming to design over a class of closed-loop systems recently proposed for the rejection of non-zero initial conditions and bounded disturbances. Performance robustness in the form of a guaranteed upper bound on the peak magnitude of the tracking error under plant uncertainty is incorporated into the formulation. CD001572.PDF (From Author) TOP LMI-Based Reliable Robust Tracking Control Against Actuator Faults with Application to Flight Control Authors: Fang Liao, Jian Liang Wang, Guang-Hong Yang, Volume: 1, Page 3914 Paper number 1403 Abstract: In this paper, we consider the reliable robust tracking controller design problem against actuator faults and control surface damages for a LTI system with input disturbance. First, models of actuator faults and control surface damages are presented. Then a reliable tracking controller design method is developed, which guarantees the closed-loop system stability, optimizes the tracking performance of the system in normal operations, and maintains an acceptable low-level tracking performance of the system in the event of actuator faults and/or control surface damages. This method is based on LQ/H-infinity tracking performance indices and multi-objective optimization in terms of linear matrix inequalities. A numerical example of an F-16 aircraft model and its simulation results are given. CD001403.PDF (From Author) TOP