Interval Method for Analysis and Design of Hybrid Uncertain Systems

Abstract

Most practical dynamical systems are formulated by hybrid uncertain delayed systems that consist of mixed continuous and discrete uncertain subsystems with state and/or input delays. For improving the performance of the delayed hybrid systems, well-established control theory and design methods are available in the continuous-time domain to find analog controllers. The resulting analog controller is required to be replaced by a digital controller for better reliability lower cost, smaller size, more flexibility and better performance. In this research, we have successfully accomplished the following research subjects: (1) Digital/analog model conversions of linear hybrid interval systems with unknown-but-bounded uncertain parameters; (2) Digital modeling and control of linear continuous-time systems with state, input and output delays; (3) Development of digital redesign techniques for digital control of cascaded linear hybrid interval systems; (4) Development of PAM (Pulse-Amplitude-Modulated) and PWM (Pulse-Width-Modulated) digital controllers for linear hybrid interval systems; (5) Design of digital PAM tracker for nominal chaotic orbits; (6) Interval Kalman filtering for linear stochastic uncertain systems; (7) Fuzzy-model-based self-tuning controller for nominal chaotic systems; (8) Model conversions and optimal control of 2D (2 Dimensional) nominal systems; (9) GA (Genetic Algorithm)-based optimal digital controllers for linear hybrid interval systems.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 2000
Accession Number
ADA398312

Entities

People

  • Chen Guanrong
  • Lueang-san Shieh

Organizations

  • University of Houston

Tags

Communities of Interest

  • Space

DTIC Thesaurus Topics

  • Algorithms
  • Control Systems
  • Control Systems Engineering
  • Control Theory
  • Conversion
  • Electrical Engineering
  • Engineering
  • Genetic Algorithms
  • Hybrid Systems
  • Information Science
  • Reliability
  • Scientists
  • Signal Processing
  • Students
  • Systems Science
  • Time Domain
  • Two Dimensional

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Computer Science/Computer Engineering/Data Science/Digital Signal Processing.
  • Control Systems Engineering.

Technology Areas

  • AI & ML
  • AI & ML - Autonomous Systems
  • AI & ML - Bayesian Inference
  • AI & ML - Machine Learning Algorithms
  • Biotechnology
  • Space
  • Space - Spacecraft Maneuvers