Feedback System Theory

Abstract

In Quantitative Feedback Synthesis, bounds on plant uncertainty and on the system performance are specified. The minimum feedback is used which satisfies the latter over the range of uncertainty. Quantitative design has been extended to linear time invariant systems: (1) with nonminimum-phase (nmp) unstable plants with gain uncertainty. In the optimum design the gain factor uncertainty is maximized for which the specifications are satisfied; (2) parallel nmp plants whose output can be individually measured and processed, to achieve a parallel combination which is minimum-phase over the range of uncertainty, or if not possible, which is less strongly nmp. (3) Cascade plants in which 'plant modification' is possible by means of internal feedback. An added constraint is that the increase in plant interval variable ci rms value equal to or less than LAMBDA sub i. Such internal feedback permits significant decrease in loop bandwidths and thereby the effect of sensor noise. (4) A problem heretofore intractable to Quantitative Synthesis has been the Multiple Input-Output (multivariable) system. This problem has now been solved for plants with significant uncertainty and interaction. A remarkable feature is that the design procedure involves the design of a number of distinct, separate single- loop problems with no need for iteration. Constraints on the plant are less stringent than in other synthesis techniques which cannot handle significant parameter uncertainty (Author)

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Nov 01, 1978
Accession Number
ADA064483

Entities

People

  • Isaac M. Horowitz

Organizations

  • University of Colorado Boulder

Tags

Communities of Interest

  • Air Platforms
  • C4I

DTIC Thesaurus Topics

  • Air Force
  • Banach Space
  • Closed Loop Systems
  • Colorado
  • Compensation
  • Control Systems Engineering
  • Dynamic Response
  • Electrical Engineering
  • Engineering
  • Engineers
  • Feedback
  • Frequency
  • Frequency Domain
  • Mathematics
  • Matrix Theory
  • Transfer Functions
  • Uncertainty

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Control Systems Engineering.