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Experimental Nonlinear Control for Flutter Suppression in a Nonlinear Aeroelastic System / Shakir Jiffri, Sebastiano Fichera, John E. Mottershead, Andrea Da Ronch
Journal of Guidance, Control, and Dynamics, Volume: 40, Issue: 8, Pages: 1925 - 1938
Swansea University Author: Shakir Jiffri
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Experimental implementation of input–output feedback linearization in controlling the dynamics of a nonlinear pitch–plunge aeroelastic system is presented. The control objective is to linearize the system dynamics and assign the poles of the pitch mode of the resulting linear system. The implementat...
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Experimental implementation of input–output feedback linearization in controlling the dynamics of a nonlinear pitch–plunge aeroelastic system is presented. The control objective is to linearize the system dynamics and assign the poles of the pitch mode of the resulting linear system. The implementation 1) addresses experimentally the general case where feedback linearization-based control is applied using as the output a degree of freedom other than that where the physical nonlinearity is located, using a single trailing-edge control surface, to stabilize the entire system; 2) includes the unsteady effects of the airfoil’s aerodynamic behavior; 3) includes the embedding of a tuned numerical model of the aeroelastic system into the control scheme in real time; and 4) uses pole placement as the linear control objective, providing the user with flexibility in determining the nature of the controlled response. When implemented experimentally, the controller is capable of not only delaying the onset of limit-cycle oscillation but also successfully eliminating a previously established limit-cycle oscillation. The assignment of higher levels of damping results in notable reductions in limit-cycle oscillation decay times in the closed-loop response, indicating good controllability of the aeroelastic system and effectiveness of the pole-placement objective. The closed-loop response is further improved by incorporating adaptation so that assumed system parameters are updated with time. The use of an optimum adaptation parameter results in reduced response decay times.
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