Improved high order differential feedback control of quadrotor UAV based on improved extended state observer
Quadrotor unmanned aerial vehicle (QUAV) system is nonlinear, strongly coupled, and sensitive to unknown disturbances and uncertainties. The uncertainty, disturbance, and even unknown model function are the undesired force acting on the QUAV, so they must be totally estimated online. The ideal contr...
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Veröffentlicht in: | Journal of the Franklin Institute 2022-06, Vol.359 (9), p.4233-4259 |
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Sprache: | eng |
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Zusammenfassung: | Quadrotor unmanned aerial vehicle (QUAV) system is nonlinear, strongly coupled, and sensitive to unknown disturbances and uncertainties. The uncertainty, disturbance, and even unknown model function are the undesired force acting on the QUAV, so they must be totally estimated online. The ideal control scheme is that the total estimation is feedback in the opposite direction to the controller to compensate the model error or counteract the force caused by the unknown model and disturbance. An improved extended state observer (IESO), also called an improved high-order differentiator (IHOD), is designed to estimate the unknown model and disturbance of the QUAV. It is proved that the IESO is one type higher than the traditional ESO. Consequently, the estimation accuracy of IESO is higher than that of the ESO at the same bandwidth, and is verified through some typical functions. The IESO estimations for 2nd-order derivative of reference input and the total unknown model function are fed back to compensate the undesired force in opposite direction, and then an improved high-order differential feedback controller (IHODFC) is designed with the assigned closed-loop poles. The proof of the stability of the closed-loop system controlled by the IHODFC is given. The performance is verified by the tests using the Pixhawk-based DJI F450 frame experimental verification platform. The IHODFC superiority is demonstrated by comparing the classic model-free controller PID and active disturbance rejection control (ADRC). |
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ISSN: | 0016-0032 1879-2693 0016-0032 |
DOI: | 10.1016/j.jfranklin.2022.03.019 |