Model Development and Model-Based Control Design for High Performance Nonlinear Smart Systems

Abstract

We have developed a unified energy-based framework for quantifying hysteresis and constitutive nonlinearities inherent to piezoelectric, magnetic, and shape memory compounds which is amenable to inversion and subsequent use as an inverse filter for linear control designs. We have also developed stochastic modeling techniques which quantify the highly complex stiffness properties of ionic polymers in a manner which facilitates design in applications ranging from biological/chemical detection to robotic design for aerospace structures. The control component has focused on the development of robust linear designs exploiting nonlinear filters and fully nonlinear algorithms which incorporate modeled physics directly into the control design. Open loop control experiments have been performed and present investigations are focused on closed loop experimental validation of the control theories.

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Document Details

Document Type
Technical Report
Publication Date
Nov 20, 2007
Accession Number
ADA476681

Entities

People

  • Ralph C. Smith

Organizations

  • North Carolina State University

Tags

Communities of Interest

  • Advanced Electronics
  • Sensors
  • Space

DTIC Thesaurus Topics

  • Accuracy
  • Actuators
  • Air Force
  • Algorithms
  • Detectors
  • Electric Fields
  • Ferromagnetic Materials
  • Field Programmable Gate Arrays
  • Films
  • Frequency
  • Magnetic Materials
  • Materials
  • Mathematics
  • Nonlinear Dynamics
  • Shape Memory Alloys
  • Students
  • Thin Films

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Materials Science and Engineering.
  • Robotics and Automation.

Technology Areas

  • AI & ML
  • AI & ML - Machine Learning Algorithms
  • Autonomy
  • Autonomy - Autonomous System Control
  • Space
  • Space - Spacecraft Maneuvers