This paper presents a new guidance and control system based on an adaptive backstepping method for a space transportation system. In recent years, many studies of flight control systems using feedback linearization combined with time-scale separation have been carried out. Since this type of control system does not depend on the design points along a predetermined trajectory, the designed system can be applied to an extensive flight region. However, in this method, control performance tends to deteriorate with changes in the control gains and parameters because it is difficult to guarantee the stability of the system. Additionally, since it is not easy to obtain prior knowledge about disturbances and aerodynamic characteristics, an estimation mechanism must be added to the system. To solve this problem, we propose an adaptive flight control system combining feedback linearization, the backstepping method, and disturbance observers. A disturbance observer is effective for estimating the effect of extraneous signals. In the proposed system, by appropriately redesigning the disturbance observer, it becomes possible to guarantee the stability of the entire system, including the estimation mechanism. Numerical simulations were performed to verify the effectiveness and robustness of the proposed system when applied to an automatic landing problem.

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Air surveillance using multiple aircraft is an efficient method for information gathering. Aircraft distributed in a wide area, gathering data at different points simultaneously, can provide a regional database with spatial and temporal expanses. The control of flight formation using multiple aircraft was conducted to realize such efficient air surveillance using a control with three kinds of local interaction among the aircraft, i.e. “attraction,” “repulsion,” and “parallel orientation.” The similarity between the shape of the interaction field and the formation shape realized efficient formation shape control by changing the shape of the interaction field of each aircraft without assigning the position of all vehicles. The local interaction parameters and PID control parameters were adjusted to satisfy the desirable performance of formation shape control. Consequently, the lateral expansion of the formation shape was controlled successfully with a convergence to the command value and a certain amount of robustness in formation shape control was confirmed.

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This paper discusses aerodynamic optimization of the high-wing configuration to explore fuselage-wing shapes for the high-wing configurations of near-future aircraft, in which it will be possible to install fuel-efficient, ultrahigh-bypass ratio engines, using computational fluid dynamics simulation and the Kriging surrogate-assisted genetic algorithm. First, optimization of the fuselage upper surface is performed, with exploration of the fairing shape suitable for the high-wing configuration. Second, the aircraft nose shape is also optimized, in addition to the fuselage upper surface, to confirm the possibility of generating higher lift by the fuselage itself. Finally, both the fuselage and the wing shape are optimized to improve the lift-to-drag ratio by alleviating the shock wave over the wing, while sustaining the high lift generation of the high-wing configuration. The final optimized configuration achieves not only a lift-to-drag ratio comparable to the DLR-F6, but also a C_L approximately 1.5 times higher than the DLR-F6. These results indicate the possibility of producing high-wing aircraft that not only employ fuel-efficient ultrahigh-bypass ratio engines, but also have much better aerodynamic performance than low-wing configurations.

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A numerical simulation of sound propagation around a blended wing body (BWB) aircraft with an open rotor engine is performed to understand the shielding effect of the engine noise. A boundary element method (BEM) code based on the Helmholtz equation is developed for this purpose. The effect of uniform flow and the surface impedance of the aircraft is analyzed in detail. The mean flow showed little effect on the amount of shielding since the approach speed is a relatively low Mach number. On the other hand, when a soft-surface condition is applied to the upper side of the aircraft, a larger amount of shielding is observed throughout the analyzed field when compared to a rigid surface case. Additionally, an effective area for applying the soft-surface condition is clarified in order to reduce the usage of such material.

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In this paper, uncertainty quantification approaches are applied to an aerodynamic uncertainty quantification problem with a far-field drag breakdown approach. Two uncertainty quantification approaches, a non-intrusive polynomial chaos approach and an inexpensive Monte-Carlo simulation approach on a response surface model are compared and investigated for more advanced aerodynamic uncertainty quantification. Using the drag breakdown approach, total drag of a body can be decomposed into three physical and one unphysical drag components: wave, viscous, induced and spurious drag components. The drag source distribution can also be visualized on the flowfield using this approach. An uncertainty quantification problem of two-dimensional airfoil with four uncertain input variables is analyzed with the drag breakdown approach to extract more aerodynamic design information about its uncertainty propagation.

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Proper orthogonal decomposition (POD) or dynamic mode decomposition (DMD) are useful analytical techniques for describing the behavior of a complicated flow by decomposing the flow into several components called modes. In POD analysis, the flow is most efficiently decomposed into orthonormal modes in terms of energy, so most of the flow energy can be extracted using a small number of modes. On the other hand, in DMD analysis, flow structures that have specific frequencies can be observed by managing the sequence of the given time series data. In this study, POD and DMD analyses were applied to the experimental and numerical results for velocity fields around a circular cylinder, and the analytical results were compared. As a result, flow structures of POD and DMD modes from the experimental results were mostly in agreement with those from the numerical results, but differences were seen in energy distribution. In the POD analysis, the rates of energy in the numerical results were clearly divided in each pair of POD modes, but in the experimental results, they were not clear except for the first and second POD modes.

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