A Real-Time Multi-Processor for Adaptive Control Experiments

Abstract

The objective of this project was to acquire instrumentation that will advance the state of the art in real time control and enhance the transition of new adaptive control techniques to DoD laboratories and industry. The instrumentation is portable in order to permit travel to DoD laboratories and industry to implement innovative controllers on their experimental testbeds. The key instrumentation is a special purpose multiprocessor configuration based on 4 Texas Instruments TMS320C40 60 MHz DSP processors and 4 DEC Alpha AXP 21164 500 MHz processors with 32 input channels and 32 output channels. The performance of this instrumentation extends the state of the art in real time computing for feedback control applications. A unique feature of this instrumentation is the fact that it is self contained and fully transportable to allow on Site research in DoD laboratories and industry. The principal instrumentation was supplied by dSPACE, Inc., a vendor of real time control processors. Of critical importance is their software interface to the Matlab real time C code generator as well as their convenient diagnostic and interface software. Their multiprocessor architecture allows real time computing capability for feedback control beyond anything else currently available.

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Document Details

Document Type
Technical Report
Publication Date
May 17, 1999
Accession Number
ADA365561

Entities

People

  • Dennis S. Bernstein

Organizations

  • University of Michigan

Tags

Communities of Interest

  • Sensors
  • Space

DTIC Thesaurus Topics

  • Actuators
  • Air Force
  • Air Force Research Laboratories
  • Aircrafts
  • Algorithms
  • Aspect Ratio
  • Computational Fluid Dynamics
  • Control Systems
  • Engineering
  • Feedback
  • Frequency
  • Frequency Bands
  • Instrumentation
  • Noise
  • Spacecraft
  • Three Dimensional
  • Transfer Functions

Fields of Study

  • Computer science

Readers

  • Computer Science/Computer Engineering/Data Science/Digital Signal Processing.
  • Parallel and Distributed Computing.
  • Robotics and Automation.