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Neural Network Adaptive Observer design for Nonlinear Systems with Partially and Completely Unknown Dynamics Subject to Variable Sampled and Delay Output Measurement

Published: 07 December 2023 Publication History
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  • Abstract

    This paper proposes a novel Neural Network Adaptive Observer (NNAO) for Nonlinear Systems with Partially and Completely Unknown Dynamics (NSPCUD), subject to variable sampled and delayed output. The method involves designing a neural network observer for partially unknown nonlinear systems with sampled and delayed outputs, using a radial basis function (RBF) neural network to approximate the system’s unknown part. A new weight update algorithm is proposed, along with a closed-loop output predictor for coping with variable samples, and a closed-loop integral compensation to handle variable delay. This approach is then extended to cover completely unknown systems as well. Numerical simulations and comparisons between the proposed method and previous methods on autonomous ground vehicle models were conducted to verify the effectiveness of the proposed NNAO.

    Highlights

    A neural network observer is proposed under variable sampled and delayed output.
    A new weight update law is designed to construct the neural network observer.
    The proposed observer is extended to more general nonlinear systems.
    It is proved that the system state and weight estimation is UUB.
    The effectiveness of the observer is demonstrated through AGV model by simulation.

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    Index Terms

    1. Neural Network Adaptive Observer design for Nonlinear Systems with Partially and Completely Unknown Dynamics Subject to Variable Sampled and Delay Output Measurement
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              Published In

              cover image Neurocomputing
              Neurocomputing  Volume 561, Issue C
              Dec 2023
              359 pages

              Publisher

              Elsevier Science Publishers B. V.

              Netherlands

              Publication History

              Published: 07 December 2023

              Author Tags

              1. Nonlinear observer
              2. RBF neural network
              3. Partial and complete unknown nonlinear system
              4. Variable sampled and delay measurement

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