Stochastic distribution control system design : a convex optimization approach
Author(s)
Bibliographic Information
Stochastic distribution control system design : a convex optimization approach
（Advances in industrial control）
Springer, c2010
- : hardcover
Available at 1 libraries
Note
Includes bibliographical references and index
Description and Table of Contents
Description
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.
Table of Contents
Developments in Stochastic Distribution Control Systems.- Developments in Stochastic Distribution Control Systems.- Structural Controller Design for Stochastic Distribution Control Systems.- Proportional Integral Derivative Control for Continuous-time Stochastic Systems.- Constrained Continuous-time Proportional Integral Derivative Control Based on Convex Algorithms.- Constrained Discrete-time Proportional Integral Control Based on Convex Algorithms.- Two-step Intelligent Optimization Modeling and Control for Stochastic Distribution Control Systems.- Adaptive Tracking Stochastic Distribution Control for Two-step Neural Network Models.- Constrained Adaptive Proportional Integral Tracking Control for Two-step Neural Network Models with Delays.- Constrained Proportional Integral Tracking Control for Takagi-Sugeno Fuzzy Model.- Statistical Tracking Control - Driven by Output Statistical Information Set.- Multiple-objective Statistical Tracking Control Based on Linear Matrix Inequalities.- Adaptive Statistical Tracking Control Based on Two-step Neural Networks with Time Delays.- Fault Detection and Diagnosis for Stochastic Distribution Control Systems.- Optimal Continuous-time Fault Detection Filtering.- Optimal Discrete-time Fault Detection and Diagnosis Filtering.- Conclusions.- Summary and Potential Applications.
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