Stochastic distribution control system design: a convex optimization approach

A recent development in SDC-related problems is the establishment of intelligent SDC models and the intensive use of LMI-based convex optimization methods.Within this theoretical framework, control parameter determination can be designed and stability and robustness of closed-loop systems can be analyzed. This book describes the new framework of SDC system design and provides a comprehensive description of the modelling of controller design tools and their real-time implementation. It starts with a review of current research on SDC and moves on to some basic techniques for modelling and controller design of SDC systems. This is followed by a description of controller design for fixed-control-structure SDC systems, PDF control for general input- and output-represented systems, filtering designs, and fault detection and diagnosis (FDD) for SDC systems. Many new LMI techniques being developed for SDC systems are shown to have independent theoretical significance for robust control and FDD problems. INDICE: Introduction.- Basic Stochastic Distribution Control Systems: Modelling and Controller Design Tools.- PDF Tracking Control with PID Structure for Non-Gaussian Continuous System.- PDF Tracking Control with PID Structure forNon-Gaussian Discrete-time Systems.- Statistic Tracking Control: A Multi-objective Optimization Algorithm.- Optimal Output Probability Density Function Control for Nonlinear ARMAX Stochastic Systems.- FDD for Non-Gaussian Continuous Systems Based on Output PDFs.- Optimal FDD for Non-Gaussian Time-delayed Systems Based on Output PDFs.- Optimal FDD for Non-Gaussian Discrete Systems Based on Output PDFs.- Entropy Optimization Filtering for Fault Isolation of Non-Gaussian Systems.- Conclusions.

• ISBN: 978-1-4471-2559-4
• Editorial: Springer
• Encuadernacion: Rústica
• Fecha Publicación: 01/07/2012
• Nº Volúmenes: 1
• Idioma: Inglés