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Design of a joint adaptive observer for a class of affine nonlinear sampled‐output system with unknown states and parameters

Abstract : In this article, a joint adaptive observer design method is proposed for a class of affine nonlinear systems subject to sampled output data measurements. The considered class of system contains nonlinear terms which depend on unknown parameters. The considered unknown parameters enter the system in both the output and the system states equations which render the design of the sampled data observer for the affine nonlinear system more difficult to conceive. To solve this problem, and based on a new method of decoupling parameter estimation and state observation, a new online output sampling joint adaptive observer is proposed in this article, which can simultaneously guarantees the exponential convergence of the estimation of unknown state and parameter. The structure of the proposed observer has been extended to the case of sampled and delayed data measurements. To illustrate the performance of the proposed observer, a comparison is made with another observer with an output predictor on a satellite navigation system. And the observer proposed in this article is applied to the model‐free control of ultra‐local models.
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https://hal-normandie-univ.archives-ouvertes.fr/hal-03518686
Contributor : SOFIANE AHMED ALI Connect in order to contact the contributor
Submitted on : Monday, January 10, 2022 - 9:50:16 AM
Last modification on : Monday, January 10, 2022 - 9:50:16 AM

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Xincheng Zhuang, Haoping Wang, Sofiane Ahmed‐ali, Yang Tian. Design of a joint adaptive observer for a class of affine nonlinear sampled‐output system with unknown states and parameters. International Journal of Adaptive Control and Signal Processing, Wiley, 2021, ⟨10.1002/acs.3355⟩. ⟨hal-03518686⟩

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