Control of Randomly Sampled Robotic Systems

Abstract

This paper studies control problems of sampled data systems which are subject to random sample rate variations and delays. Due to the rapid growth of the use of computers more and more systems are controlled digitally. Complex systems as space telerobotic systems require the integration of a number of sub-systems at different hierarchical levels. While many sub-systems may run on a single processor, some sub-systems require their own processor or processors. The sub-systems are integrated into functioning systems through communications. Communication between processes sharing a single processor are also subject to random delays due to memory management and interrupt latency. Communications between processors involve random delays due to network access and to data collisions. Furthermore, all control processes involve delays due to causal factors in measuring devices and to signal processing. Traditionally, sampling rates are chosen to meet the worst case communication delay. Such a strategy is wasteful as the processors are then idle a great proportion of the time; sample rates are not as high as possible resulting in poor performance or in the over specification of control processors; there is the possibility of missing data no matter how low the sample rate is picked. Keywords: Statistical analysis.

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Document Details

Document Type
Technical Report
Publication Date
May 01, 1989
Accession Number
ADA218948

Entities

People

  • Hiroaki Kobayashi
  • Richard P. Paul
  • Xiaoping Yun

Organizations

  • University of Pennsylvania

Tags

Communities of Interest

  • Autonomy
  • C4I
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Algorithms
  • Bernoulli Distribution
  • Complex Systems
  • Computer Programs
  • Computers
  • Control Systems
  • Control Systems Engineering
  • Differential Equations
  • Equations
  • Information Science
  • Linear Systems
  • Probability
  • Probability Density Functions
  • Random Variables
  • Signal Processing
  • Statistical Sampling
  • Stochastic Processes

Fields of Study

  • Engineering

Readers

  • Parallel and Distributed Computing.
  • Regression Analysis.
  • Robotics and Automation.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference
  • AI & ML - DoD AI Strategy
  • Autonomy
  • Space