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- W1530348526 abstract "A rotorcraft-based unmanned aerial vehicle exhibits more complex properties compared to its full-size counterparts due to its increased sensitivity to control inputs and disturbances and higher bandwidth of its dynamics. As an aerial vehicle with vertical take-off and landing capability, the helicopter specifically poses a difficult problem of transition between forward flight and unstable hover and vice versa. The most traditional approach for solving this nonlinear problem is by linearizing the vehicle dynamics over a set of operating points where a gain scheduling mechanism is then applied. The drawback of this approach is that the control design based on the linearized dynamics might not perform well or worse guarantee stability when it is applied beyond the vicinity of equilibrium. In contrast to this approach, the LPV control technique explicitly takes into account the change in performance due to the real-time parameter variations. The technique therefore theoretically guarantees the performance and robustness over the entire operating envelope. In one of many robust control approaches, one can conduct numerical linearizations of the dynamics of the nonlinear helicopter model made for varying forward speed. This set of linear models is then used to construct an LFT representation of the system by element-wise interpolation of the stability and control derivatives matrices. Despite its guaranteed performance, this approach however is unnecessarily conservative since the LFT does not consider the rate of parameter variation. In this study, we investigate a new approach implementing model identification for use in the LPV control framework. The identification scheme employs recursive least square technique implemented on the LPV system represented by dynamics of helicopter during a transition. The airspeed as the scheduling of parameter trajectory is not assumed to vary slowly. The exclusion of slow parameter change requirement allows for the application of the algorithm for aggressive maneuvering capability without the need of expensive computation. The technique is tested numerically and will be validated in the autonomous flight of a small scale helicopter." @default.
- W1530348526 created "2016-06-24" @default.
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- W1530348526 date "2008-06-25" @default.
- W1530348526 modified "2023-09-27" @default.
- W1530348526 title "Linear Parameter Varying Model Identification for Control of Rotorcraft-based UAV" @default.
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