Nonlinear H2/H∞ Constrained Feedback Control A Practical Design Approach Using Neural Networks /

• Main Authors: Abu-Khalaf, Murad (Author), Huang, Jie (Author), Lewis, Frank L. (Author)
• Corporate Author: SpringerLink (Online service)
• Format: Electronic eBook
• Language: English
• Published: London : Springer London, 2006.
• Series: Advances in Industrial Control,
• Subjects: Engineering.; Chemical engineering.; Artificial intelligence.; Automotive engineering.; Control engineering.; Industrial engineering.; Production engineering.; Electrical engineering.; Control.; Electrical Engineering.; Automotive Engineering.; Industrial and Production Engineering.; Artificial Intelligence (incl. Robotics).; Industrial Chemistry/Chemical Engineering.

Modern aerospace, automotive, nautical, industrial, microsystem-assembly and robotic systems are becoming more and more complex. High-performance vehicles no longer have built-in error safety margins, but are inherently unstable by design to allow for more flexible maneuvering options. With the push...

Table of Contents:

• Preliminaries and Introduction
• Policy Iterations and Nonlinear H 2 Constrained State Feedback Control
• Nearly H 2 Optimal Neural Network Control for Constrained-Input Systems
• Policy Iterations and Nonlinear H ? Constrained State Feedback Control
• Nearly H ? Optimal Neural Network Control for Constrained-Input Systems
• Taylor Series Approach to Solving HJI Equation
• An Algorithm to Solve Discrete HJI Equations Arising from Discrete Nonlinear H ? Control Problems
• H ? Static Output Feedback.