Controllability and adaptation of linear time-invariant systems under irregular and Markovian sampling. (January 2016)

• Record Type: Journal Article
• Authors: Zhao, Ping; Wang, Le Yi; Yin, George
• Is Part Of: Automatica. Volume 63(2016)
• Page Start: 92
• Page End: 100
• Publication Date: 2016-01
• Subjects: Sampled system -- Irregular sampling -- Controllability -- Adaptation -- Stability; Automatic control -- Periodicals; Automation -- Periodicals; 629.805
• DOI: 10.1016/j.automatica.2015.10.022
• Languages: English
• ISSNs: 0005-1098

Abstract

Abstract: 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.