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Structural Robust Gain-Scheduled PID Control and Application on a Morphing Wing UAV
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摘要
Further research based on the author's past work in [1] is performed in this paper. A structural robust gain-scheduled(GS) PID control method is proposed and applied to control the pitch angle for a morphing wing UAV(MUAV) in its transient process. Firstly, the author gives the robust static output feedback(SOF) control method for LPV system and shows that PID control is equivalent to SOF control, thus the robust GS PID control design is derived via SOF. Secondly, the author introduces a structural matrix to structuralize the robust GS PID control, then a structural robust GS PI(D) control design method is derived. The controller is in the same form of PID controller used in practice, which has a more simple structure than the result in [10] and other existing results. At last, the proposed method is applied to control the pitch angle of a MUAV based on a LPV model developed by a Jacobian Linearization method. Linear analysis and nonlinear Monte-Carlo simulation were performed and the results showed that the proposed solution were applicable with satisfactory robustness and performance.
Further research based on the author's past work in [1] is performed in this paper. A structural robust gain-scheduled(GS) PID control method is proposed and applied to control the pitch angle for a morphing wing UAV(MUAV) in its transient process. Firstly, the author gives the robust static output feedback(SOF) control method for LPV system and shows that PID control is equivalent to SOF control, thus the robust GS PID control design is derived via SOF. Secondly, the author introduces a structural matrix to structuralize the robust GS PID control, then a structural robust GS PI(D) control design method is derived. The controller is in the same form of PID controller used in practice, which has a more simple structure than the result in [10] and other existing results. At last, the proposed method is applied to control the pitch angle of a MUAV based on a LPV model developed by a Jacobian Linearization method. Linear analysis and nonlinear Monte-Carlo simulation were performed and the results showed that the proposed solution were applicable with satisfactory robustness and performance.
引文
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