Control System Analysis and Synthesis via Linear Matrix Inequalities

Abstract

A wide variety of problems in systems and control theory can be cast or recast as convex problems that involve linear matrix inequalities (LMIs). For a few very special cases there are "analytical solutions" to these problems, but in general they can be solved numerically very efficiently. In many cases the inequalities have the form of simultaneous Lyapunov or algebraic Riccati inequalities; such problems can be solved in a time that is comparable to the time required to solve the same number of Lyapunov or Algebraic Riccati equations. Therefore the computational cost of extending current control theory that is based on the solution of algebraic Riccati equations to a theory based on the solution of (multiple, simultaneous) Lyapunov or Riccati inequalities is modest. Examples include: multicriterion LQG, synthesis of linear state feedback for multiple or nonlinear plants ("multi-model control"), optimal transfer matrix realization, norm scaling, synthesis of multipliers for Popov-like analysis of systems with unknown gains, and many others.

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Document Details

Document Type
Technical Report
Publication Date
Jun 01, 1993
Accession Number
ADA640062

Entities

People

  • E. Feron
  • L. Elghaoui
  • S. Boyd
  • V. Balakrishnan

Organizations

  • Stanford University

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Algorithms
  • Closed Loop Systems
  • Control Systems
  • Control Systems Engineering
  • Control Theory
  • Eigenvalues
  • Engineering
  • Equations
  • Feedback
  • Frequency Response
  • Inequalities
  • Lyapunov Functions
  • Noise
  • Optimization
  • Riccati Equation

Fields of Study

  • Mathematics

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Operations Research