The need for a high fidelity model for design, analysis and implementation of an unmanned helicopter system (UHS) in various emerging civil applications cannot be underestimated. However, going by a first principle approach based on physical laws governing the dynamics of the system, this task is noted to be highly challenging due to the complex nonlinear characteristics of the helicopter system. On the other hand, the problem of determining network architecture for optimal/sub-optimal performances has been one of the major challenges in the use of the nonparametric approach based on Nonlinear AutoRegressive with eXogenous inputs Network (NARX-network). The performance of the NARX network in terms of complexity and accuracy is largely dependent on the network architecture. The current approach in the literature has been largely based on trial and error, while most of the reported optimization approaches have limited the domain of the problem to a single objective problem. This study proposes a hybrid of conventional back propagation training algorithm for the NARX network and multiobjective differential evolution (MODE) algorithm for identification of a nonlinear model of an unmanned small scale helicopter from experimental flight data. The proposed hybrid algorithm was able to produce models with Pareto-optimal compromise between the design objectives. The performance of the proposed optimized model is benchmarked with one of the previously reported architectures for a similar system. The optimized model outperformed the previous model architecture with up to 55% performance improvement. Apart from the effectiveness of the optimized model, the proposed design algorithm is expected to facilitate timely development of the nonparametric model of the helicopter system.


    Zugriff

    Zugriff über TIB

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Nonlinear identification of a small scale unmanned helicopter using optimized NARX network with multiobjective differential evolution


    Beteiligte:
    Tijani, Ismaila B. (Autor:in) / Akmeliawati, Rini (Autor:in) / Legowo, Ari (Autor:in) / Budiyono, Agus (Autor:in)


    Erscheinungsdatum :

    2014


    Format / Umfang :

    17 Seiten, 48 Quellen




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Print


    Sprache :

    Englisch




    Nonlinear system identification of a small-scale unmanned helicopter

    Tang, Shuai / Zheng, Zhiqiang / Qian, Shaoke et al. | Tema Archiv | 2014


    Identification Modeling of a Small-Scale Unmanned Helicopter

    Zhiqiang, Bai / Jinhua, Wang / Peizhi, Liu | AIAA | 2009


    Optimization of an extended H-infinity controller for unmanned helicopter control using Multiobjective Differential Evolution (MODE)

    Tijani, Ismaila Bayo / Akmeliawati, Rini / Legowo, Ari et al. | Emerald Group Publishing | 2015


    Dynamical Model Identification for a Small-Scale Unmanned Helicopter Using an Integrated Approach

    Rui Ma / Li Ding / Kailei Liu et al. | DOAJ | 2019

    Freier Zugriff

    Robust flight control of small-scale unmanned helicopter

    Wang, Xiafu / Chen, You / Lu, Geng et al. | IEEE | 2013