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Rendezvous and docking (RVD) with a tumbling target is challenging. In this paper, a novel control scheme based on motion planning and pose (position and attitude) tracking is proposed to solve the pose control of a chaser docking with a tumbling target in the phase of close range rendezvous. Firstly, the current desired motion of the chaser is planned according to the motion of the target. In planning the desired motion, the “approach path constraint” is considered to avoid collisions between the chaser and the target, and the “field-of-view constraint” is considered to make sure the vision sensors on the chaser to obtain tight relative pose knowledge of the target with respect to the chaser. Then, the difference between the chaser’s motion and the desired motion is gradually reduced by a pose tracking controller. This controller is based on the non-singular terminal sliding mode (NTSM) method to make the tracking error converge to zero in finite time. Since the chaser nearly moves along the desired motion and the motion is reasonable, (1) it could safely arrive at the docking port of the target with a suitable relative attitude, (2) it will be always suitably oriented to observe the target well, and (3) the magnitude of the needed control inputs are less than that in existing literatures. The numerical results demonstrate the above three advantages of the proposed method.

This paper studies the pose tracking control problem for satellite proximity operations between a target and a chaser satellite, by which we mean that the chaser is required to track a desired time-varying trajectory given in advance with respect to the target. Firstly, by consulting an adaptive sliding-mode control method in literature developed for a class of nonlinear uncertain systems, an effective pose tracking controller is obtained. This controller requires no information about the mass and inertia matrix of the chaser, and takes into account the gravitational acceleration, the gravity-gradient torque, the J2 perturbing acceleration, and unknown bounded disturbance forces and torques. Then, an updated controller is proposed by combining the aforementioned controller and the unscented Kalman filter (UKF). This updated controller estimates the inertial parameters of the chaser through UKF, so it is of better adaptive ability to the initial estimation of the inertial parameters. Finally, numerical simulations are given to demonstrate the effectiveness of the proposed controllers. The simulation results show that the updated controller is more accurate.

With the development of aerospace technology, the maneuverability of various types of aircraft continues to improve, and these aircraft experience an overload environment with high acceleration and high acceleration rate. Due to the special influence brought by the high acceleration rate, the dynamic centrifugal test technology, which is different from the traditional steady-state centrifugal test technology, came into being. The steady-state centrifuge has only one rotor, while the dynamic centrifuge has multiple rotors; so, the relationship between the acceleration of the control point and the motion parameters of the rotors is more complicated. Therefore, a key issue of the dynamic centrifugal test technology is the inverse kinematics of the dynamic centrifuge, which is to calculate the kinematic parameters of the dynamic centrifuge according to the expected acceleration environment that needs to be simulated on the centrifuge. After the kinematic parameters is calculated, the control target of each rotor of the dynamic centrifuge could be known, then the expected acceleration environment could be produced. In this paper, 1) on the basis of the predecessors, the equation for solving the angular velocity of the main arm of the centrifuge is improved; 2) and then a time step adaptive method is proposed, which takes into account the calculation accuracy and efficiency. As a result, an inverse kinematics algorithm that is more accurate and adaptable to various acceleration history curve is obtained. Finally, the inverse kinematics algorithm in this paper is verified through experiments and numerical simulations.

Capturing an uncontrolled space target is a tremendously challenging research topic. Target capture by a space robot can be well planned according to predicted motion of the target. In this paper, motion prediction of an uncontrolled space target is studied and a motion prediction algorithm is proposed. In the proposed algorithm, firstly a method for identifying the parameters of motion state and inertial property of the target is established; and then through substituting the identified parameters into the dynamic equations of the target, the motion of the target can be predicted as the solution of the equations. In the identification of the parameters, the unscented Kalman filter (UKF) is applied. In order to support the UKF, a method for estimating noise level of the observation data is developed, so our motion prediction algorithm is noise adaptive. A practical convergent criterion is also designed to determine the time when the estimated result of the UKF is accurate enough, such that the predicted motion is credible enough. After that, the accuracy of the prediction is further improved by an optimization method. In the end of this paper, numerical simulations are done to verify the validity of the proposed motion prediction algorithm. Simulation results indicate that the proposed algorithm is able to predict the motion of the target precisely.

Capturing a non-cooperative space target is a tremendously challenging research topic. Effective acquisition of motion information of the space target is the premise to realize target capture. In this paper, motion prediction of a free-floating non-cooperative target in space is studied and a motion prediction algorithm is proposed. In order to predict the motion of the free-floating non-cooperative target, dynamic parameters of the target must be firstly identified (estimated), such as inertia, angular momentum and kinetic energy and so on; then the predicted motion of the target can be acquired by substituting these identified parameters into the Euler’s equations of the target. Accurate prediction needs precise identification. This paper presents an effective method to identify these dynamic parameters of a free-floating non-cooperative target. This method is based on two steps, (1) the rough estimation of the parameters is computed using the motion observation data to the target, and (2) the best estimation of the parameters is found by an optimization method. In the optimization problem, the objective function is based on the difference between the observed and the predicted motion, and the interior-point method (IPM) is chosen as the optimization algorithm, which starts at the rough estimate obtained in the first step and finds a global minimum to the objective function with the guidance of objective function’s gradient. So the speed of IPM searching for the global minimum is fast, and an accurate identification can be obtained in time. The numerical results show that the proposed motion prediction algorithm is able to predict the motion of the target.