Tilt-rotor unmanned aerial vehicles combine the advantages of multirotor and fixed-wing aircraft, offering features like rapid takeoff and landing, extended endurance, and wide flight conditions. This article provides a summary of the design, modeling, and control of a composite tilt-rotor. During modeling process, aerodynamic modeling was performed on the tilting and non-tilting parts based on the subcomponent modeling method, and CFD simulation analysis was conducted on the entire unmanned aerial vehicle to obtain its accurate aerodynamic characteristics. In the process of modeling the motor propeller, the reduction of motor thrust and torque due to forward flow and tilt angle velocity is thoroughly examined, which is usually ignored in most tilt UAV propeller models. In the controller design, this paper proposes a fusion ADRC control strategy suitable for vertical takeoff and landing of this type of tiltrotor. The control system framework is built using Simulink, and the control algorithm’s efficiency has been verified through simulation testing. Through the proposed control scheme, it is possible for the composite tiltrotor unmanned aerial vehicle to smoothly transition between multirotor and fixed-wing flight modes.

A robust controller for the waypoint tracking of a quadrotor unmanned aerial vehicle (UAV) is proposed in this paper, in which position control and attitude control are effectively decoupled. Model predictive control (MPC) is employed in the position controller. The constraints of motors are imposed on the state and input variables of the optimization equation. This design effectively mitigates the nonlinearity of the attitude loop and enhances the planning efficiency of the position controller. The attitude controller is designed using a nonlinear and robust control law based on $SO(3)$ space, which enables continuous control on the $SO(3)$ manifold. By extending the differential flatness of the quadrotor-UAV to the angular acceleration level, the mapping of the control reference from the position controller to the attitude controller is achieved. Simulations are carried out to demonstrate the capability of the proposed controller. In the simulations, multiple aggressive flight trajectories and severe external disturbances are designed. The results show that the controller is robust, with superior accuracy in tracking aggressive trajectories.

This work presents a novel self-organizing control method for mega constellations to meet the continuous Earth observation requirements. In order to decrease the TT&C pressure caused by numerous satellites, constellation satellites are not controlled according to the designed configurations but are controlled with respect to intersatellite constraints. By analyzing the street-of-coverage (SOC) of coplanar constellation satellites, the continuous coverage constraint of the mega constellation is transformed into constraints of the right ascension of ascending node (RAAN) and relative motion bound between every two adjacent coplanar satellites. The proposed continuous coverage constraint can be satisfied by most ongoing or planned mega constellations. Artificial potential functions (APFs) are used to realize self-organizing control. The scale-independent relative orbital elements (SIROEs) are innovatively presented as the self-organizing control variables. Using the Gaussian equations and Lyapunov’s theory, the stability of the APF control in quadratic form is proven, from which it can be concluded that the APF control variables of the controlled satellite should have the same time derivative as the target satellite states under two-body Keplerian motion condition, and SIROEs are ideal choices. The proposed controllers and self-organizing rules are verified in the sub-constellation of the GW-2 mega constellation by simulation. The results demonstrate the goodness in control effect and ground coverage performance.

This paper proposes a full-size and free-flying humanoid robot named Taikobot that aims to assist astronauts in a space station and maintain spacecrafts between human visits. Taikobot adopts a compact and lightweight (∼25 kg) design to work in microgravity, which also reduces launch costs and improves safety during human–robot collaboration. Taikobot’s anthropomorphic dual arm system and zero-g legs allow it to share a set of intravehicular human–machine interfaces. Unlike ground-walking robots, Taikobot maneuvers in a novel push–flight–park (PFP) strategy as an equivalent astronaut in a space station to maximize workspace and flexibility. We propose a PFP motion planning and control method based on centroidal dynamics and multi-contact model. Based on the proposed method, we carried out extensive simulations and verified the feasibility and advantages of the novel locomotion strategy. We also developed a prototype of Taikobot and carried out several ground experiments on typical scenarios where the robot collaborates with human astronauts. The experiments show that Taikobot can do some simple and repetitive tasks along with astronauts and has the potential to help astronauts improve their onboard working efficiency.

In order to improve the safety of spacecraft, the research on artificial neural network and digital twin technology based on, to our best knowledge, a novel fiber Bragg grating (FBG) sensor array is proposed for intelligent sensing monitoring of spacecraft on-orbit collisions. Femtosecond FBG arrays were fabricated on the novel oxide-doped fiber by point-by-point writing technique. The femtosecond FBG is analyzed using the time-dependent perturbation theory of quantum mechanics. The FBG array can achieve high-temperature measurement of 1100 °C and large strain measurement of 15000 µε. The sensing arrays were deployed on the surface of the spacecraft. Constructed the multi-layer perceptron neural network structure and convolutional neural network structure. 1200 samples were trained. Conducted model accuracy testing. The accuracy rate is above 98%, and accuracy verification has been implemented. The digital twin model was designed based on various data such as strain and temperature of the spacecraft structure under impact monitored by FBG sensors. A precise mapping has been formed between the physical entities of spacecraft and digital twins. Empower spacecraft with functions such as self-monitoring, judgment, and response. To ensure the stable and safe operation of spacecraft.