Controllability and adaptation of linear time-invariant systems under irregular and Markovian sampling

• Ping Zhao ^[2] ; Le Yi Wang ^[1] ; George Yin ^[1]
  1. [1] Wayne State University

     Wayne State University

     City of Detroit, Estados Unidos

     
  2. [2] University of Jinan,China
• Localización: Automatica: A journal of IFAC the International Federation of Automatic Control, ISSN 0005-1098, Vol. 63, 2016, págs. 92-100
• Idioma: inglés
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• Resumen

  • This paper investigates controllability for linear time-invariant systems under irregular and random sampling, and develops adaptive control algorithms with respect to sampling intervals. Using block erasure channels as the main motivating communication platform, it first establishes a sufficient condition on sampling density that ensures controllability of sampled systems, which is necessary for feedback design and adaptation. Then, it continues with causal adaptive feedback algorithms to accommodate time-varying sampling intervals. Implementation of such algorithms encounters technical challenges because future sampling intervals are uncertain or random. Under deterministic slowly-varying and stochastic infrequent Markovian jumping sampling intervals, overall system stability is established. Simulation results are used to illustrate the algorithms and their effectiveness.