Tethered Space Robot Research Articles

Learning-based data-driven optimal deployment control of tethered space robot

To avoid complex constraints of the traditional nonlinear method for tethered space robot (TSR) deployment, a data-driven optimal control framework with an improve deep learning based Koopman operator is proposed in this work. In consideration of nonlinearity of tethered space robot dynamics, its finite dimensional global linear representation called lifted linear system is derived with the Koopman operator theory. A deep learning scheme is adopted to find the embedding functions associate with Koopman operator. And an auxiliary neural network is developed to encode the nonlinear control term of finite dimensional lifted system. Then a controllability constraint is considered for learning a controllable lifted linear system. Besides two loss functions that relate to reconstruction and prediction ability of lifted linear system are designed for training the deep neural network. With the learned lifted linear dynamics, Linear Quadratic Regulator (LQR) is applied to derive the optimal control policy for the tethered space robot deployment. Finally, simulation results verify the effectiveness of proposed framework and show that it could deploy tethered space robot more quickly with less swing of in-plane angle.

Human-Assisted Regulation of the Deployment of a Tethered Space Robot via Feasibility Condition Optimization and Fast Logarithmic Sliding Mode

Human-Assisted Regulation of the Deployment of a Tethered Space Robot via Feasibility Condition Optimization and Fast Logarithmic Sliding Mode

A Learning-Based Scheme for Safe Deployment of Tethered Space Robot

A Learning-Based Scheme for Safe Deployment of Tethered Space Robot

An Energy-Based Saturated Controller for the Underactuated Tethered System

This article addresses the stabilization control issue for the postcapture tethered system by tethered space robot (TSR). Due to the physical characteristics of space tether by nature, there exists no control inputs on the in-plane/out-of-plane channels of the tether; therefore, the postcapture tethered system is a typical multiinput and multioutput underactuated system. In this article, we propose an energy-based controller for the underactuated system subject to input saturation and the nonnegativity constraint of the tether tension. First, we give the dynamic model of the postcapture tethered system, with consideration of the three attitude angles of the postcapture combination, the in-plane/out-of-plane angles, and the tether length. Second, we list the analysis process of the system’s equilibrium points. Third, we give the detailed controller design process, and verify the stability of the system by invoking the Lyapunov techniques and the extended Barbalat’s lemma. Finally, numerical simulations and comparison results with the hierarchical sliding mode controller are conducted to validate the performance improvement of the developed control strategy.

Learning-Based Sliding-Mode Control for Underactuated Deployment of Tethered Space Robot With Limited Input

This article proposes a learning-based adaptive sliding-mode control for the underactuted deployment of tethered space robot with limited input. The reduced-order system on the sliding surface is optimized by the critic neural network-based nearly optimal approximation algorithm, and both the linear and nonlinear situations are taken into account. To remove the assumption that the state-dependent disturbance is vanishing, the behavior of state synchronization on the sliding surface is revealed for the first time, and the nearly optimal solution of limited input for generating stable trajectory can be approximated by the actor neural network-based adaptive dynamic programming. The hyperbolic tangent of desired input is synthesized into the optimal value function, and it can be obtained by the actor-critic neural network-based reinforcement learning algorithm solving the corresponding Hamilton–Jacobi–Bellman equation. The numerical simulation takes the numerical example of the deployment of tethered space robot to verify the effectiveness of the proposed method.

Learning-Based Control for Deployment of Tethered Space Robot via Sliding Mode and Zero-Sum Game

The underactuated dynamics with input saturation due to limited tension is the greatest challenge of stabilizing the deployment of tethered space robot (TSR), and existing sliding mode methods rely on the assumptions of inherently bounded control command and vanishing state-dependent disturbance. This paper proposes a nearly optimal control law based on variable construct control and neural network technique, which can get rid of the assumptions. The new reduced-order system with synchronization states can be established by the nearly optimal reaching law based on the zero-sum game strategy, which is approximately solved by the actor-disturbance-critic neural network. Meanwhile, the terminal attractor is synthesized into the sliding surface to enhance fast convergence. A numerical simulation was conducted to verify the proposed analyses, and this study’s results show that the method works effectively to ensure a fast response of the underactuated dynamics under limited input and disturbance.

Fuzzy Approximate Learning-Based Sliding Mode Control for Deploying Tethered Space Robot

This article proposes a hybrid control scheme synthesizing fuzzy approximate Q-iteration algorithm and discrete-time terminal-like sliding mode control for deploying tethered space robot, which is modeled as a deterministic Markov decision process. The existence of a switching condition allows FQ-iteration algorithm and terminal-like sliding surface constituting an optimal sliding mode control, and the fuzzy logic approximation is employed to improve the efficiency of optimization. Under arbitrary switching, the sliding mode reaching law works to compress the contraction of sliding surface variable. Simulation results verify the analyses on contraction of fuzzy approximate Q-iteration for optimal sliding mode control, the stability of reduced-order system yielded by the proposed discrete-time terminal-like sliding surface, and existence of switching condition.

Nonlinear Analysis of Discrete-Time Sliding Mode Prediction Deployment of Tethered Space Robot

This article proposes a discrete-time sliding mode prediction controller for deploying tethered space robot, and tension control strategy in deployment carries a limited input nature for the underactuated system. A linear component involving swinging angle and a fractional power component involving length combine to establish a novel discrete-time quasi-terminal sliding surface for underactuated dynamics. The corresponding reduced-order system is decoupled by using a hierarchical constrictive analysis methodology to generate an equivalent relationship between length and swinging angle, and the stability of the entire system is governed by multidelay system of length. The D-decomposition technique is employed to deduce that the steady-state error of length is ultimately uniformly bounded. The optimal reaching law is designed based on the sliding mode prediction algorithm, which can guarantee that the prediction correction converge to zero, and the sliding surface with a small boundary layer can hence be established in finite steps under the limited tension control with a modified input compensation sequence. Simulation results verify the correction of stability analyses on dynamics and the steady-state behavior of the sliding mode, and from the numerical results, the proposed method can save time for deploying tethered space robot by only using tension than normal discrete-time sliding mode control.

Reel-Based Tension Control of Tethered Space Robots

This article elaborates on the tension control design of tethered space robots for debris removal. The novel approach is to change the tether natural length via a reel. With only the tension sensing, we leverage a Kalman filter and a recursive least-squares algorithm to estimate the actual length and the debris mass, which are fed back to a model-predictive controller to generate the optimal tangential velocity of the reel. Simulations show that the stiff tether exhibits better tension-tracking performance which is robust to the tumbling debris.

Extracting and Matching Lines of Low-Textured Region in Close-Range Navigation for Tethered Space Robot

When dealing with lines in regions with sparse texture, such as satellite's brackets, some existing line matching methods do not work well due to the incorrect location of line endpoints and line fragments. In this paper, we study how to automatically match low-textured lines. The designed feature only uses their neighborhood appearance and there are no any other prior knowledge or constraints needed. We combine point and line features to propose a novel line matching method. It includes the following three main steps. First, line extraction based on pixel gradient is adopted and we design a mergence strategy to ensure continuity. Then, line-point invariant and center-symmetric local binary pattern descriptor are combined together to represent lines. Last, two corresponding criterions are designed to measure the similarities between each pair images. Extensive experiments on real and synthetic images show that our proposed method exceeds the reference methods in performance under scale, illumination, and dynamic cases.

Adaptive anti-windup control of post-capture combination via tethered space robot

Stabilization control is an essential mission for the tethered space robot-target combination during the post-capture phase of tethered space robot (TSR). With the consideration of the space tether and the three dimensional attitude of the post-capture combination, dynamic model of the combination is derived by using Lagrange method. Considering the unknown dynamic parameters (the tether attachment point, unknown target inertia parameters) of the post-capture combination, an adaptive anti-windup control approach is presented to overcome the problem of dynamic uncertainty and control input saturation. Complete stability and performance analyses are presented and illustrative simulation results of application to the post-capture combination system verify the effectiveness of the proposed algorithm.

Discrete-Time Sliding Mode Control for Deployment of Tethered Space Robot With Only Length and Angle Measurement

This paper proposes a nonlinear discrete-time sliding mode based tension control for deployment of tethered space robot with only length and angle measurements. The discrete-time dynamics of deployment is uncovered based on discretization of Hamilton's principle. Taking into account the underactuated dynamics, the proposed discrete-time sliding surface can generate a specified reduced-order system, which can be regarded as an uncertain discrete-time system with multiple time delays, which is caused by a considerable sample interval, and the stability of a reduced-order system is well analyzed by combining a linear matrix inequation technique based on robust control theory and nonlinear discrete-time Lyapunov method. A novel input structure with the auxiliary variable sequence is presented to deal with the tension saturation, and the states can converge to the specified reduced-order system although the input saturation occurs. The proposed discrete-time method makes no appeal to velocity terms. It is cost-effective to use the proposed method for the information of length and angle are easily measured rather than that of velocity, and it conduces to low requirements for the measurement ability of sensors. Simulation results verify the stability analyses, and are coincident with the stability analyses.

Precise Angles-Only Navigation for Noncooperative Proximity Operation With Application to Tethered Space Robot

For microspacecraft that have limited payload capability, the potential use of vision sensors (e.g., cameras) has been already recognized in noncooperative proximity operation. However, vision-based relative navigation is difficult, because vision sensors have the limitation to accurately measure distance information. In this paper, we propose an angles-only navigation and control framework for noncooperative proximity operation. The framework is especially suitable for challenging long-range proximity operation, where only the line-of-sight angles of the target can be obtained. Within the proposed framework, the spacecraft not only estimates its current orbital position precisely with only angle measurements but also approaches to a noncooperative target by following desired attitude and orbital motions. The framework combines an off-line motion planning and an online navigation and control that is based on model predictive control (MPC) and time delay control (TDC). The study is with application to tethered space robot. Extensive simulations illustrate the effectiveness of the proposed framework.

Anti-tangle control of tethered space robots using linear motion of tether offset

Removal of uncooperative tumbling targets using tethered space robots is subject to the risk of tether tangling around the targets. A good anti-tangle control should be (1) fuel-saving, (2) implementation-friendly and (3) tether-libration-suppressing. The proposed strategy achieves these requirements by using a linear actuator to move the tether offset. However, the underactuation due to the input constraints and coupling arises as a main technical challenge. We address the issue from the system passivity perspective by constructing the potential energy in terms of the tension torque. This makes the most of the tether characteristic whereby we specify the control objective that steers the target's angular velocity to the tether direction. Then, an energy-based sliding mode motion controller is designed, the parameter of which is optimized using a model predictive controller to satisfy the motion constraint. The tangle-avoidance is further reinforced by adaptively tuning the weight of MPC. A RBF neural network and a extended Kalman filer are also used to render the controller robust to the uncertainties. Simulations with different tumbling rates validate the effectiveness of the method.

Optimal control of approaching target for tethered space robot based on non-singular terminal sliding mode method

In the tethered space robot approaching phase, the tether can provide attitude control torque and orbit control force, it can reduce the fuel consumption of the gripper, but there is operation coupling for the tether is not always pass through the centroid of the gripper. And the field of view of the camera is limited, the tracking error of attitude and position can make the target deviate from the camera view field. Aiming to above problems, a position and attitude coordinated control scheme based on non-singular terminal sliding mode method is designed for the approaching task. The dynamic model of tethered space robot based on lumped mass model and elastic rod model are established, respectively. Combining the dynamic model of tethered space robot based on elastic rod model with the relative motion model of the target, a Gaussian pseudo spectral motion planning model is established, the planning model takes into account the constraints of control input and the field of view of gripper. Solving the programming model, the optimal approaching trajectory of the tethered space robot is obtained. Then, a trajectory tracking controller is designed based on non-singular terminal sliding mode method. The simulation results show that the proposed control scheme can realize the accurate position and attitude tracking of the optimal trajectory.

MPC-based anti-sway control of tethered space robots

Tether sway in debris towing removal perturbs the removal orbit due to the thrust-tether misalignment. Therefore, this paper proposes an anti-sway method using model predictive control (MPC). The method uses platform attitude maneuver to suppress the sway and track the orbit by orienting the platform thrust to the desired direction, which makes the system non-affine and underactuated. This necessitates a dual-loop control structure where the outer loop provides the desired attitude for the inner attitude control loop. For the outer loop, the attitude angular velocity is extracted as a virtual control input. A higher-order hierarchical sliding mode control (HSMC) and a super-twisting-algorithm (STA) based observer are used to obtain the equivalent law for sliding phase. The system states in controller are estimated by an extended kalman filter (EKF). For the inner loop, a MPC-based control torque forces the angular velocity to follow the equivalent law and steers the states to the sliding surface in an optimal manner. Simulation results show that the control objective is fulfilled by the bounded torque and the controller is robust to the estimation errors.

A review of space tether in new applications

Ever since the space tether was first proposed by Tsiolkovsky, it has been extensively utilized in space missions, for attitude stabilization, momentum exchange, and space elevators. Developments in engineering technology and changes in the space environment have diversified the current applications for the space tether. New applications for the space tether include the Tethered Space Robot, Tethered Space Net, and Tethered Spacecraft Formation. These are quickly being adapted for in-orbit maintenance such as fueling service, orbit maneuvering, and active space debris capture/removal. The flexibility and elasticity of the space tether lead to complex issues with tethered space systems, including the mechanics design, dynamics modeling and analysis, and control scheme design. In this paper, we review several new applications for the space tether during service in orbit, and research the on structure, dynamics, and control of each application. This review is conducted to provide an overall summary of the space tether for On-Orbit Servicing, and further the conversation regarding possible research interests in the future.

Approaching control for tethered space robot based on disturbance observer using super twisting law

Approaching control is a key mission for the tethered space robot to perform the task of removing space debris. But the uncertainties of the TSR such as the change of model parameter have an important effect on the approaching mission. Considering the space tether and the attitude of the gripper, the dynamic model of the TSR is derived using Lagrange method. Then a disturbance observer is designed to estimate the uncertainty based on STW control method. Using the disturbance observer, a controller is designed, and the performance is compared with the dynamic inverse controller which turns out that the proposed controller performs better. Numerical simulation validates the feasibility of the proposed controller on the position and attitude tracking of the TSR.

Observer-based control for the platform of a tethered space robot

This paper addresses the attitude control problem of a space tethered robot platform in the presence of unknown external disturbance caused by a connecting elastic tether. The tether-generated unknown disturbance leads to tremendous challenges for attitude control of the platform. In this work, the perturbed attitude dynamics of the platform are derived with a consideration of the libration of the elastic tether, and then with the purpose of compensating the unknown disturbance, major attention is dedicated to develop a nonlinear disturbance observer based on gyros measurements, after which, an adaptive attitude scheme is proposed by combining the disturbance observer with a sliding mode controller. Finally, benefits from the observer based on an adaptive controller are validated by series of numerical simulations.

Dynamic modeling and Super-Twisting Sliding Mode Control for Tethered Space Robot

Recent years, tethered space capturing systems have been considered as one of the most promising solutions for active space debris removal due to the increasing threat of space debris to spacecraft and astronauts. In this paper, one of the tethered space capturing systems, Tethered Space Robot (TSR), is investigated. TSR includes a space platform, a space tether, and a gripper as the terminal device. Based on the assumptions that the platform and the gripper are point masses and the tether is rigid, inextensible and remaining straight, the dynamic model of TSR is presented, in which the disturbances from space environment is considered. According to the previous study, the in-plane and out-of-plane angles of the tether oscillate periodically although the tether is released to the desired length. A super-twisting adaptive sliding mode control scheme is designed for TSR to eliminate the vibration of the tether to assure a successful capture in station-keeping phase. Both uncontrolled and controlled situations are simulated. The simulation results show that the proposed controller is effective. Additionally, after comparing with normal sliding mode control algorithm, it is verified that the proposed control scheme can avoid the chattering of normal sliding mode control and is robust for unknown boundary perturbations.