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• W3201832107 abstract "This paper proposes a learning control based attitude tracking control method for a small size unmanned helicopter. The helicopter is subject to uncertain system parameters, unmodeling dynamics, and unknown external disturbances. To improve the flight control performance, a new learning based nonlinear robust control strategy is designed to let the helicopter track a desired attitude trajectory. The proposed controller accounts for the structural and unstructural uncertain dynamics via the iterative learning strategy. In order to solve the problem that iterative learning can not completely compensate for external disturbances, a sliding mode controller is also utilized to reduce the effects of unknown disturbances. The output strictly passive feature of the closed-loop system is proven by considering an iterative learning control input combined with sliding mode algorithm. Then, an adaptive update law, based on iterative learning control, is developed to guarantee the convergence of the tracking error. The asymptotic convergence of the attitude tracking errors is also proved. Numerical simulation results are presented to validate the control performance of the proposed control algorithm." @default.
• W3201832107 created "2021-10-11" @default.
• W3201832107 creator A5014687668 @default.
• W3201832107 creator A5082727992 @default.
• W3201832107 date "2021-07-26" @default.
• W3201832107 modified "2023-09-27" @default.
• W3201832107 title "Attitude Control for an Unmanned Helicopter Using Passivity-Based Iterative Learning" @default.
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• W3201832107 doi "https://doi.org/10.23919/ccc52363.2021.9549889" @default.
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