Accession Number:

ADA453881

Title:

Robust Stochastic Adaptive Control

Descriptive Note:

Final rept. 1 Sep 1982-31 Dec 1987

Corporate Author:

MASSACHUSETTS INST OF TECH CAMBRIDGE LAB FOR INFORMATION AND DECISION SYSTEMS

Personal Author(s):

Report Date:

1988-01-28

Pagination or Media Count:

16.0

Abstract:

In this final report we summarize the activities of the MYFLIDS research group for the time period 1 September 1982 to 31 December 1987. The research, funded by ONR contract N00014-82-K-0582, deals with fundamental issues in robust adaptive control systems, and the potential application of advanced control system design methodologies to the multivariable control of submarines. The research conducted was highly successful, and had significant and controversial impact upon the theory of adaptive control. The research of Rohrs, Valavani, Athans and Stein pointed out potential instabilities of then existing adaptive control algorithms caused by the presence of unmeasurable output disturbances and high frequency unmodeled dynamics. The publications of Rohrs et al were instrumental for defining new research directions in the adaptive control field, and the topic of Robust Adaptive Control became a new area for worldwide research. The research of Krause et al provided the first direction for the use of what is now called Averaging Theory for the analysis of adaptive control algorithms in the presence of disturbances and unmodeled dynamics. The research of Orlicki et al provided the first set of adaptive algorithms that actively employ real-time signal processing to compute frequency domain parameters which can be used to safeguard the stability of Model Reference Adaptive schemes that employ Intermittent Adaptation. The research of LaMaire et al deals with novel formulation of Hybrid Robust Identification algorithms which identify in real-time both time-domain models of the unknown plant and modeling error bounds in the frequency domain. The research of Milich et al develops theory and methodologies for designing robust compensators, with guaranteed performance in the presence of large structured and unstructured plant uncertainties. This complements the research conducted which helped streamline the LQGLTR design methodology for non-adaptive feedback systems.

Subject Categories:

  • Numerical Mathematics
  • Theoretical Mathematics
  • Miscellaneous Detection and Detectors

Distribution Statement:

APPROVED FOR PUBLIC RELEASE