Leveraging the benefits of the multiobjective particle swarm optimization (PSO) technique, we introduce a new concept of adaptive strictly negative imaginary (SNI) controllers. The proposed adaptive control systems are specifically designed to minimize a certain performance index, representing the objective of our control design, which is to obtain a stable, robust, and responsive 3-D tracking of the AR.Drone drone in the face of wind gusts. We compare the performance of our proposed adaptive controllers with respect to the performance of PSO-PID control systems and the traditional Ziegler–Nichols PID controllers, not only in simulated flights but also in real flight tests. We also present a stability analysis of the closed-loop control system using the SNI system theory.


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    Titel :

    Adaptive Trajectory Tracking for Quadrotor Systems in Unknown Wind Environments Using Particle Swarm Optimization-Based Strictly Negative Imaginary Controllers


    Beteiligte:
    Tran, Vu Phi (Autor:in) / Santoso, Fendy (Autor:in) / Garratt, Matthew A. (Autor:in)


    Erscheinungsdatum :

    01.06.2021


    Format / Umfang :

    5146369 byte




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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