The time-spectral (TS) method to numerically predict self-excited oscillation due to the fluid dynamics-- rigid body dynamics coupling is developed and validated through the comparison with the time-marching (TM) method. A residual of the TS equation of motion of a rigid body is found to be a useful indicator to realize limit-cycle oscillations. It is minimized by repeating the frequency update by the Newton iteration, where the gradient of the residual with respect to the frequency is obtained from the flow simulation, and the displace update by solving the TS equation of motion. The developed method is validated by two problems: one is an oscillating cylinder due to the Karman vortex, and another is a transonic, pitching wing due to the movement of the shock wave around the wing. In both problems, the TS methods quantitatively reproduce free oscillations by the TM method. The simulation time is shortened by a factor of 4 for the transonic wing problem.
This study explores the minimum-time attitude maneuver of satellites using Control Moment Gyros (CMG). The CMG system is able to generate high torque and run for longer term than other actuators. However, it is known that the singular input that cannot generate effective torque appears in the optimal control for the minimum-time maneuver of a rigid spacecraft with a pyramid type SGCMG system. In previous studies, a new system equipped with variable speed CMG (VSCMG) to the CMG where the singular input appeared has been proposed. It is shown that the new system can rotate faster than the normal pyramid type SGCMG system in the simulation based on the optimal control law. However, for applications in actual satellites, numerical optimization cannot be used due to the high calculation cost. The objective of this study is to make the new semi-optimal control law for the minimum time attitude maneuver of the satellite equipped with the VSCMG. The new control law is designed using a rule-based feedforward control combined with feedback control. The result by numerical simulation has shown that the proposed control law enables the satellite to achieve faster maneuver without iterative calculations.
In this paper, we propose two estimators to compensate the target's maneuver and uncertain vehicle dynamics including uncertain system lag; one is an extended state high-gain-observer-based estimator to estimate an uncertainty and disturbance term (UDT) which affects the line-of-sight (LOS) rate dynamics, and the other is a novel filter to estimate the uncertain system lag. Generally, a linearized system from its original system for the estimation of the uncertain system lag is unobservable, whereas, we can make the system observable with the filter. The effectiveness of those compensation methods are shown by conducting some representative numerical simulations and comparing with a conventional compensating method. The filter which estimates the uncertain system lag used in combination with the high-gain-observer-based estimator has made better performance than the one used in combination with the conventional method in terms of convergence time and resulting miss distance.
This paper is concerned with the control of the dual-spin turn (DST) of a spacecraft to regulate the spacecraft attitude. The DST is a method for attitude stabilization of a rotating spacecraft by transferring the angular momentum of the spacecraft to a single wheel. The proposed control law consists of feedforward (FF) and feedback (FB) control phases. The FF control is designed by optimizing the driving pattern of the wheel using the Differential Evolution (DE). In the FB control, the rate damping control and the attitude control around the wheel rotation axis are proposed based on the linearized error system around the stationary state of the spacecraft. By using the proposed control law, the DST is controlled step by step, and the spacecraft eventually becomes stationary at an arbitrary angle around the wheel rotation axis. The validity of the proposed method is verified by numerical simulations.
This paper proposes an optimal planning method of imaging multiple points on Earth from a spacecraft that is equipped with a pyramid type Control Moment Gyros (CMGs) as the attitude control actuators. The purpose of the planning is to maximize the number of cities to be imaged with better quality during multiple orbiting. The problem results in the optimization of selection of target cities and imaging orders under the constraints of the candidate cities, position of the spacecraft and the attitude maneuvering time. In order for better quality of the images, we consider minimization of the sum of the distance between the spacecraft and the target cities in the city selection procedure. Estimating the attitude maneuvering time with CMGs usually takes long due to the complexity, therefore, we also propose a faster estimation method of the maneuvering time by approximation. The proposed planning method is applied to the imaging of 292 cities around the world along 10 satellite paths, and its validity is evaluated through numerical simulations.
A neural network for prediction of discharge current, which shows nonlinearity and hysteresis dependent on coil current, has been developed to build auto control system of Hall thrusters. The prediction accuracy dependence on training data sets composed of operational parameters (previous work), 250 images of plume shape and both, operational parameters and images, are investigated. The network using only plume images can describe the non-linear mode hop jump and hysteresis that the network using only operational parameters cannot describe. The predicted discharge current, however, is fluctuated up and down, while that observed in experiment shows smooth curve. The prediction using both operating parameters and plume images as the training data, can describe mode hop jump and hysteresis with 0.8% difference between prediction current and that observed in experiment.