Compared with conventional aircrafts, the dynamics of morphing aircraft exhibit significant nonlinearity and high uncertainty posing substantial challenges to the controller design. This paper proposed an incremental ...
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Compared with conventional aircrafts, the dynamics of morphing aircraft exhibit significant nonlinearity and high uncertainty posing substantial challenges to the controller design. This paper proposed an incremental model predictive control (IMPC) approach for a morphing aircraft with the varying wingspan and sweep angle. The proposed method, formulated as the constrained optimal control problems (OCPs), is robust to dynamic uncertainties and capable of handling input and state constraints such as mechanical limits and angle of attack. Firstly, we establish a nonlinear affine model of the morphing aircraft according to the aircraft's dynamic model. Subsequently, a time-scale separation (TSS) method is introduced according to the aircraft's characteristics, dividing the system into fast and slow subsystems. Each subsystem is approximated as an incremental system, reducing dependency on the nominal model. In addition, the constrained OCP is cast into a quadratic programing (QP) problem using the incrementalmodel, resulting in a linear MPC. Finally, several simulations are performed to validate the effectiveness of the IMPC method, in terms of stability, robustness, and computational efficiency.
Solar furnaces are devices employed in high temperature material stress tests that use concentrated solar energy. This process has a nonlinear dynamics caused by a fourth power temperature term and by the nonlinear be...
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Solar furnaces are devices employed in high temperature material stress tests that use concentrated solar energy. This process has a nonlinear dynamics caused by a fourth power temperature term and by the nonlinear behavior of the shutter. Sun power variability due to weather conditions may affect the operation of a solar furnace if it is not compensated by adjusting the shutter aperture. The contribution of this paper is to explore and to evaluate the application of modelpredictivecontrol with integral action to a nonlinear process. Off-line identification is employed to characterize the temperature dynamics. This methodology avoids the use of online adaptation mechanisms that may cause stability problems during temperature stress tests that may melt the material sample. The aim is to design a controller with a good performance, able to track the temperature cycling profile without overshooting to avoid melting the material sample. Active cooling is also explored to improve the temperature tracking during the decrease of the temperature profile. Experimental results obtained from the closed loop control of the plant are presented. (C) 2016, IFAC (International Federation of Automatic control) Hosting by Elsevier Ltd. All rights reserved.
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