State Space Model for Autopilot Design of Aerospace Vehicles

Abstract

This report is a follow on to the report given in DSTO-TN-0449 and considers the derivation of the mathematical model for aerospace vehicles and missile autopilots in state space form. The basic equations defining the airframe dynamics are non-linear, however, since the nonlinearities are structured (in the sense that the states are of quadratic form) a novel approach of expressing this non-linear dynamics in state space form is given. This should provide a useful way to implement the equations in a computer simulation program and possibly for future application of non-linear analysis and synthesis techniques, particularly for autopilot design of aerospace vehicles executing high g-maneuvers. This report also considers a locally linearized state space model that lends itself to better known linear techniques of the modern control theory. A coupled multi-input multi-output (MIMO) model is derived suitable for both the application of the modern control techniques as well as the classical time-domain and frequency domain techniques. The models developed are useful for further research on precision optimum guidance and control. It is hoped that the model will provide more accurate presentations of missile autopilot dynamics and will be used for adaptive and integrated guidance & control of agile missiles.

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Document Details

Document Type
Technical Report
Publication Date
Mar 01, 2007
Accession Number
ADA471578

Entities

People

  • Farhan A. Faruqi

Organizations

  • Defence Science and Technology Group

Tags

Communities of Interest

  • Air Platforms
  • Space
  • Weapons Technologies

DTIC Thesaurus Topics

  • Aerospace Craft
  • Airframes
  • Automatic Pilots
  • Computational Science
  • Computer Simulations
  • Control Surfaces
  • Control Systems
  • Control Theory
  • Equations
  • Frequency
  • Frequency Domain
  • Guided Weapons
  • Mathematical Models
  • Nonlinear Dynamics
  • Simulations
  • Vehicles
  • Weapons

Readers

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

Technology Areas

  • Space
  • Space - Spacecraft Maneuvers