Earth observation satellites can improve the flexibility of observation sites by having “maneuverability,” and low-thrust obtained by ion thruster will be a promising method for orbital change for micro-satellites. Designing low-thrust trajectories for these satellites is a multi-revolution and multi-objective (time/fuel-optimal) optimization problem, which usually requires high computational cost to solve numerically. This paper derives an analytical and approximate optimal orbit change strategy between two circular orbits with the same semi-major axis and different local time of ascending node, and proposes a graph-based method to optimize the multi-objective criteria. The optimal control problem results in a problem to search a switching point on the proposed graph, and mission designers can design an approximate switching point on this graph, by using two heuristic and reasonable assumptions that 1) the optimal thrust direction should be tangential to orbit and 2) the optimal thrust magnitude should be bang-bang control with an intermediate coast. Finally, numerical simulation with feedback control algorithm taking thrust margin demonstrates that the proposed method can be applicable in the presence of deterministic and stochastic fluctuation of aerodynamic disturbances.
Recently, turbulence is becoming one of the main causes of air traffic accidents. Among them, Clear Air Turbulence (CAT) is difficult to forecast by current onboard systems. The onboard LIDAR developed by JAXA allows the aircraft to notice CAT in advance, but its sight range is limited. Therefore, real time path generation is required to use the LIDAR information for turbulence avoidance. Previous researches has focused on the path generation algorithm, but did not consider the limited amount of the observation. In this paper, we proposed a new method of predicting turbulent areas from limited observations, and combined it with a previous path generation algorithm. The proposed algorithm of prediction is done by a time-efficient Gaussian interpolation method, and the whole system is quick enough to refresh the optimal path in the idea of the Receding Horizon method. The performance and time-efficiency of the combined method is shown by a numerical example.
This paper describes a method of spillage drag measurement with aid of CFD at supersonic speeds. In a wind tunnel testing, the number of pressure data points is limited and is not enough to capture pressure distribution needed for an accurate calculation of spillage drag. In this method, a wind tunnel testing provides pressure data at twenty points, by which a CFD analysis is validated. Then, the pressure data obtained by the wind tunnel testing is corrected based on pressure distribution obtained by the CFD analysis. The spillage drag is calculated using corrected data. When the intake is at the supercritical condition, the spillage drag does not exist. The present method correctly shows the spillage drag of nearly zero at the supercritical condition, while the spillage drag calculated only by wind tunnel data is negative. In addition, the spillage drag obtained by the present method is increased as the intake mass flow ratio is decreased, which agrees with the general trend. These results support the effectiveness of the present method.
This paper describes the post-flight evaluation results of the guidance and control system flown in D-SEND#2 2nd drop test. The guidance law comprises on-line trajectory generation to cope with varying separation conditions and real-time trajectory prediction to adapt various modelling errors and uncertainties. The control law was developed by use of the hierarchy-structured dynamic inversion to accommodate a broad flight envelope. The 2nd drop test was successfully conducted on July 24th in 2015 at Esrange Space Center in Sweden, and all the flight data were acquired via telemetry. It was concluded that both the flight requirements and the measurement requirements were satisfied and that the guidance and control law worked accurately as designed. However, it was also concluded that there was a significant amount of aerodynamic error especially with respect to the drag coefficient. The estimated aerodynamic errors and atmospheric conditions during the flight were then incorporated into a numerical simulation and the actual flight behavior was to a large extent reproduced.
When designing a system, its stability is one of very important information. When the object is a nonlinear system, there are few evaluation methods and it is mainly evaluated based on the skill of the designer. Region of attraction (RoA) is employed as a reasonable index for evaluating the stability of a nonlinear system, however, it is rarely used for control design because of the high computational load. Recently, a method with a comparatively small expense of calculation combined with the Monte Carlo method and the dichotomy method was proposed. By using this method, it is expected to give some kind of guide for trial and error in control design to the designer, and reduce the burden on the designer. This paper describes control design of a Quad Tilt Wing (QTW) Unmanned Aerial Vehicle (UAV) which is a type of vertical take-off and landing UAV as an example of applying the method to control design.