Abstract
In this paper, a filtered sliding mode control (FSMC) scheme based on fuzzy uncertainty observer (FUO) for trajectory tracking control of a quadrotor unmanned aerial vehicle (QUAV) is proposed. To be specific, the dynamics model of QUAV is decomposed into three subsystems. By virtue of the cascaded structure, sliding-mode-based virtual control laws can be recursively designed. In order to remove the smoothness requirements on intermediate signals, a series of first-order filters are employed to reconstruct sliding mode control signals together with their first derivatives. Moreover, fuzzy uncertainty observers are employed to indirectly estimate lumped unknown nonlinearities including system uncertainties and external disturbances and make compensation for the QUAV system. Stability analysis and uniformly ultimately bounded tracking errors and states can be guaranteed by the Lyapunov approach. Simulation studies demonstrate the effectiveness and superiority of the proposed tracking control scheme.
N. Wang—This work is supported by the National Natural Science Foundation of P.R. China (under Grants 51009017 and 51379002), Applied Basic Research Funds from Ministry of Transport of P.R. China (under Grant 2012-329-225-060), China Postdoctoral Science Foundation (under Grant 2012M520629), the Fund for Dalian Distinguished Young Scholars (under Grant 2016RJ10), the Innovation Support Plan for Dalian High-level Talents (under Grant 2015R065), and the Fundamental Research Funds for the Central Universities (under Grant 3132016314).
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Wang, Y., Wang, N., Lv, S., Yin, J., Er, M.J. (2017). Fuzzy Uncertainty Observer Based Filtered Sliding Mode Trajectory Tracking Control of the Quadrotor. In: Cong, F., Leung, A., Wei, Q. (eds) Advances in Neural Networks - ISNN 2017. ISNN 2017. Lecture Notes in Computer Science(), vol 10262. Springer, Cham. https://doi.org/10.1007/978-3-319-59081-3_17
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