For uncertain dynamical systems with actuator dynamics, this paper presents a new adaptive control architecture using expanded reference models. Specifically, the proposed approach allows the trajectories of an uncertain dynamical system to follow the trajectories of the expanded reference model. As compared to a well-known approach, it is shown that the expanded reference model trajectories remain predictably close to the trajectories of a given ideal reference model, which captures a desired closed-loop system performance. Furthermore, a command governor method is also developed along with the proposed expanded reference model to achieve asymptotic convergence of the expanded reference model trajectories to those of the ideal reference model such that the desired closed-loop system performance can be captured. To provide additional robustness for possible uncertainties in the actuator bandwidths, an estimation of the actuator bandwidth is incorporated into the proposed architecture. The stability of the current approach is analyzed using linear matrix inequalities and the Lyapunov theory, where a numerical example is also presented to illustrate the efficacy of the current contributions.


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    Titel :

    Expanded Reference Models for Adaptive Control of Uncertain Systems with Actuator Dynamics


    Beteiligte:

    Erschienen in:

    Erscheinungsdatum :

    2019-12-30


    Format / Umfang :

    15 pages




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch