Abstract
This paper proposes a learning based attitude tracking control method for unmanned helicopters. Because of the influences of uncertain system parameters, unmodeled dynamics and external disturbances, a control scheme based on repetitive learning is designed to realize the precise attitude control of the helicopter for a periodic desired attitude trajectory. The helicopter dynamics system is divided into periodic part and aperiodic part, and the feed-forward component based on repetitive learning is used to compensate for the periodic part, and the high gain component is used to restrain the aperiodic part. The proposed controller compensates for the structural and unstructural uncertain dynamics and account for the disturbances via repetitive learning process. The asymptotic convergence of helicopters attitude tracking error is proved via Lyapunov-based stability analysis. The results of simulation experiment verify the availability of the proposed algorithm.
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Zhang, X., Xian, B. (2022). Nonlinear Asymptotic Attitude Tracking Control for an Unmanned Helicopter Using Repetitive Learning. In: Yan, L., Duan, H., Yu, X. (eds) Advances in Guidance, Navigation and Control . Lecture Notes in Electrical Engineering, vol 644. Springer, Singapore. https://doi.org/10.1007/978-981-15-8155-7_107
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DOI: https://doi.org/10.1007/978-981-15-8155-7_107
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