This paper introduces a hybrid dynamical system methodology for managing impulsive control in spacecraft rendezvous and proximity operations under the Hill-Clohessy-Wiltshire model. We address the control design problem by isolating the out-of-plane from the in-plane dynamics and present a feedback control law for each of them. This law is based on a Lyapunov function tailored to each of the dynamics, capable of addressing thruster saturation and also a minimum impulse bit. These Lyapunov functions were found by reformulating the system's dynamics into coordinates that more intuitively represent their physical behavior. The effectiveness of our control laws is then shown through numerical simulation. This is an extended version of an ECC24 article of the same name, which includes the proofs omitted for lack of space.
In this paper, we consider the classical spacecraft rendezvous problem in which the so-called active spacecraft has to approach the target spacecraft which is moving in an elliptical orbit around a planet by using the minimum possible amount of fuel. Instead of using standard convex optimization tools which can be computationally expensive, we use modified versions of the Iteratively Reweighted Least Squares (IRLS) algorithm from compressive sensing to compute sparse optimal control sequences which minimize the fuel consumption for both thrust vectoring and orthogonal vectoring (active) spacec…
We propose a method to compute approximate solutions to the minimum-fuel far-field rendezvous problem for thrust-vectoring spacecraft. It is well-known that the use of linearized spacecraft rendezvous equations may not give sufficiently accurate results for far-field rendezvous. In particular, as the distance between the active and the target spacecraft becomes significantly greater than the distance between the target spacecraft and the center of gravity of the planet, the accuracy of linearization-based control design approaches may decline substantially. In this paper, we use a nonlinear st…
This paper presents a computationally efficient optimization algorithm for solving nonconvex optimal control problems that involve discrete logic constraints. Traditional solution methods for these constraints require binary variables and mixed-integer programming, which is prohibitively slow and computationally expensive. This paper targets a fast solution that is capable of real-time implementation onboard spacecraft. To do so, a novel algorithm is developed that blends sequential convex programming and numerical continuation into a single iterative solution process. Inside the algorithm, di…
Geometric Conditions for Lossless Convexification in Linear Optimal Control with Discrete-Valued Inputs: Real-Time Implementation for Spacecraft Rendezvous
Convex MPC and Thrust Allocation with Deadband for Spacecraft Rendezvous
Instituto Superior Técnico（高等技术学院）；University of Lisbon（里斯本大学）；Institute for Systems and Robotics（系统与机器人研究所）；School of Science and Technology from the NOVA University of Lisbon（里斯本新大学科学与技术学院）；Lusófona University（卢索福纳大学）；GMV（GMV公司）
Lightweight Model Predictive Control for Spacecraft Rendezvous Attitude Synchronization
Space Applications Group, e:fs TechHub GmbH（e:fs技术中心空间应用组）；Faculty of Electrical Engineering and Information Technology, Ingolstadt University of Applied Sciences（应用科学大学英戈尔施塔特电气工程与信息技术学院）
Imitation learning-based spacecraft rendezvous and docking method with Expert Demonstration
Department of Control Science and Engineering, Harbin Institute of Technology（控制科学与工程系，哈尔滨工业大学）；Department of Mechanical and Automation Engineering, The Chinese University of Hong Kong（机械与自动化工程系，香港中文大学）
Certifiable Explicit Model Predictive Control for Spacecraft Rendezvous under Bounded Disturbances
NOVA University of Lisbon（诺瓦大学）；Center for Technology and Systems (CTS)（技术与系统中心）；Institute for Systems and Robotics, Instituto Superior Técnico, University of Lisbon（里斯本大学高等技术学院系统与机器人研究所）
The paper considers autonomous rendezvous maneuver and proximity operations of two spacecraft in presence of obstacles. A strategy that combines guidance and control algorithms is analyzed. The proposed closed-loop system is able to guarantee a safe path in a real environment, as well as robustness with respect to external disturbances and dynamic obstacles. The guidance strategy exploits a suitably designed Artificial Potential Field (APF), while the controller relies on Sliding Mode Control (SMC), for both position and attitude tracking of the spacecraft. As for the position control, two dif…
This paper addresses the spacecraft relative orbit reconfiguration problem of minimizing the delta-v cost of impulsive control actions while achieving a desired state in fixed time. The problem is posed in relative orbit element (ROE) space, which yields insight into relative motion geometry and allows for the straightforward inclusion of perturbations in linear time-variant form. Reachable set theory is used to translate the cost-minimization problem into a geometric path-planning problem and formulate the reachable delta-v minimum, a new metric to assess optimality and quantify reachability …
Neural-Rendezvous: Provably Robust Guidance and Control to Encounter Interstellar Objects
Jet Propulsion Laboratory（喷气推进实验室）；California Institute of Technology（加州理工学院）；National Aeronautics and Space Administration（美国国家航空航天局）；University of Illinois at Urbana-Champaign（伊利诺伊大学厄巴纳-香槟分校）
An Equivariant Filter for Spacecraft Nonlinear Relative Navigation with Range and Bearing Measurements
Institute for Systems and Robotics, Laboratory of Robotics and Engineering Systems, Instituto Superior Técnico, University of Lisbon（里斯本大学技术学院系统与机器人研究所机器人与系统工程实验室）；CTS/Uninova and LASI, School of Science and Technology, NOVA University Lisbon（新里斯本大学理学院科学和技术中心/创新研究所激光与智能系统研究所）；GNC Division, Flight Segment and Robotics, GMV（GMV公司飞行段与机器人部门制导导航与控制分部）
Model predictive control (MPC) is an optimal control strategy where control input calculation is based on minimizing the predicted tracking error over a finite horizon that moves with time. This strategy has an advantage over conventional state feedback and output feedback controllers because it predicts the response of the system, rather than simply reacting to it. Therefore, MPC can offer improved performance in the presence of input and output constraints. Many implementations of MPC on aerospace vehicles appear in literature [1]. Some of these include spacecraft and satellite attitude cont…
This paper introduces the notion of an Input Constrained Control Barrier Function (ICCBF), as a method to synthesize safety-critical controllers for non-linear control affine systems with input constraints. The method identifies a subset of the safe set of states, and constructs a controller to render the subset forward invariant. The feedback controller is represented as the solution to a quadratic program, which can be solved efficiently for real-time implementation. Furthermore, we show that ICCBFs are a generalization of Higher Order Control Barrier Functions, and thus are applicable to sy…
