CDC2000 Integrated Control and CPU Scheduling

Integrated Control and CPU Scheduling
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	An Introduction to Control and Scheduling Co-Design Authors: Karl-Erik Arzen, Anton Cervin, Johan Eker, Lui Sha, Volume: 1, Page 4865 Paper number 4301 Abstract: The paper presents the emerging field of integrated control and CPU-time scheduling, where more general scheduling models and methods that better suit the needs of control systems are developed. This creates possibilities for dynamic and flexible integrated control and scheduling frameworks, where the control design methodology takes the availability of computing resources into account during design and allows on-line trade-offs between control performance and computing resource utilization. CD004301.PDF (From Author) TOP Feedback Scheduling of Control Tasks Authors: Anton Cervin, Johan Eker, Volume: 1, Page 4871 Paper number 4302 Abstract: The paper presents a feedback scheduling mechanism in the context of co-design of the scheduler and the control tasks. We are particularly interested in controllers where the execution time may change abruptly between different modes, such as in hybrid controllers. The proposed solution attempts to keep the CPU utilization at a high level, avoid overload, and distribute the computing resources evenly among the tasks. The feedback scheduler is implemented as a periodic or sporadic task that assigns sampling periods to the controllers based on execution-time measurements. The controllers may also communicate feedforward mode-change information to the scheduler. As an example, we consider hybrid control of a set of double-tank processes. The system is evaluated, from both scheduling and control performance perspectives, by co-simulation of controllers, scheduler, and tanks. CD004302.PDF (From Author) TOP Online Control Optimization Using Load Driven Scheduling Authors: Lui Sha, Xue Liu, Marco Caccamo, Giorgio Buttazzo, Volume: 1, Page 4877 Paper number 4303 Abstract: In many real-time control applications, the task periods are typically fixed and worst-case execution times are used in schedulability analysis. With the advancement of robotics, flexible visual sensing using cameras becomes a popular alternative to the use of embedded sensors. Unfortunately, the execution time of visual tracking varies greatly. In this paper, we integrate load driven online scheduling with direct digital designs to optimize control performance as a function of varying workload. CD004303.PDF (From Author) TOP Adaptive Rate Control Through Elastic Scheduling Authors: Giorgio Buttazzo, Luca Abeni, Volume: 1, Page 4883 Paper number 4304 Abstract: In real-time computing systems, timing constraints imposed on application tasks are typically guaranteed off line using schedulability tests based on fixed parameters and worst-case execution times. However, a precise estimation of tasks' computation times is very hard to achieve, due to the non deterministic behavior of several low-level processor mechanisms, such as caching, prefetching, and DMA data transfer. The disadvantage of relying the guarantee test on a priori estimates is that an underestimation of computation times may jeopardize the correct behavior of the system, whereas an overestimation will certainly waste system resources and causes a performance degradation. In this paper, we propose a new methodology for automatically adapting the rates of a periodic task set without forcing the programmer to provide a priori estimates of tasks' computation times. Actual executions are monitored by a runtime mechanism and used as feedback signals for predicting the actual load and achieving rate adaptation. Load balancing is performed using an elastic task model, according to which tasks utilizations are treated as springs with given elastic coefficients. CD004304.PDF (From Author) TOP RT Control Scheduling To Reduce Control Performance Degrading Authors: Pedro Albertos, Alfons Crespo, Ismael Ripoll, Marina Vallés, Patricia Balbastre, Volume: 1, Page 4889 Paper number 4305 Abstract: In the framework of RT digital control, two fundamental parameters are defined, the control effort and the control action interval. The first one is related to the strength of the control that, due to the intersampling open-loop control, determines the degrading of performances under unexpected delays. The second one refers to the unavoidable delays in the multitasking environment due to interactions among the tasks. As a consequence, the scheduling policy should consider not only the tasks delays but also their influence in the control loop behavior, being calculated to minimize the overall degrading of performances. CD004305.PDF (From Author) TOP