Nonlinear Robust Control Theory and Applications

Abstract

Model based control methods are commonly used in the design of large, complex systems. Specifically, a mathematical model of the system is constructed, utilizing, for example, first principles analysis and experimental data, which is then used for subsequent control system design and analysis. For the purposes of feedback control highly accurate models are desired. However, such accuracy often requires that complicated high order models be used, which in turn lead to more difficult control design problems from both an engineering and a computational perspective. The emphasis of this research is on the development of methods for reducing the size and complexity of the model while retaining the essential features of the system description. The main goal of these methods is to find a simplified system model which describes the physical system accurately enough so that controllers designed based on this simplified model perform well when implemented on the real system. Directly related to the topic of model reduction are the realization theory concepts of minimality and its converse reducibility, which are also addressed in detail in this thesis.

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Document Details

Document Type
Technical Report
Publication Date
Jan 18, 1997
Accession Number
ADA336238

Entities

People

  • John Doyle

Organizations

  • California Institute of Technology

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Air Force
  • Air Force Facilities
  • Algorithms
  • Classification
  • Complex Systems
  • Computational Science
  • Control Systems
  • Control Theory
  • Convex Programming
  • Electrical Engineering
  • Engineering
  • Errors
  • Mathematical Models
  • Models
  • Power Series
  • Standards
  • Uncertainty

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  • Applied Combinatorial Optimization and Logic Circuit Design.
  • Robotics and Automation.
  • Theoretical Analysis.