Adaptive Control of Nonlinear and Stochastic Systems

Abstract

Significant progress was made in a number of aspects of nonlinear and stochastic systems. An important problem in the adaptive estimation of a finite state Markov chain was solved, and significant progress was made on the corresponding, but much more difficult adaptive control problem. Problems of adaptive control with unknown disturbance distributions were solved in the case of incomplete state observations. A study of the adaptive control of bilinear ARMAX models was completed. Discretization procedures for adaptive Markov control processes were designed and analyzed, and problems of adaptive control with unknown disturbance distributions were solved in the case of incomplete state observations. In the area of nonlinear systems, the effect of sampling of linearization for continuous time systems was investigated. The smooth feedback stabilization of nonlinear systems was studied, and a model reference adaptive control scheme for pure-feedback nonlinear systems was developed and studied, and some problems in the linearization of discrete-time nonlinear systems were solved. In addition, some important problems in the areas of discrete event systems, robotics, and discrete time systems were solved.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Jan 14, 1991
Accession Number
ADA232996

Entities

People

  • Aristotle Arapostathis
  • Steven I Marcus

Organizations

  • University of Texas at Austin

Tags

Communities of Interest

  • Human Systems
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Algorithms
  • Classification
  • Control Systems
  • Differential Equations
  • Engineering
  • Equations
  • Feedback
  • Information Science
  • Linear Systems
  • Markov Chains
  • Markov Processes
  • Mathematical Analysis
  • Nonlinear Systems
  • Operations Research
  • Random Variables
  • Sampling
  • Stochastic Control

Fields of Study

  • Engineering

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.

Technology Areas

  • AI & ML
  • AI & ML - Autonomous Systems
  • AI & ML - Machine Learning Algorithms
  • Autonomy
  • Autonomy - Autonomous System Control