Dual-Quaternion-Based Fault-Tolerant Control for Spacecraft Tracking With Finite-Time Convergence

Results are presented for a study of dual-quaternion-based fault-tolerant control for spacecraft tracking. First, a six-degrees-of-freedom dynamic model under a dual-quaternion-based description is employed to describe the relative coupled motion of a target-pursuer spacecraft tracking system. Then, a novel fault-tolerant control method is proposed to enable the pursuer to track the attitude and the position of the target even though its actuators have multiple faults. Furthermore, based on a novel time-varying sliding manifold, finite-time stability of the closed-loop system is theoretically guaranteed, and the convergence time of the system can be given explicitly. Multiple-task capability of the proposed control law is further demonstrated in the presence of disturbances and parametric uncertainties. Finally, numerical simulations are presented to demonstrate the effectiveness and advantages of the proposed control method

Secure motion control of micro-spacecraft using semi-homomorphic encryption

This paper studies the secure motion control problem for micro-spacecraft systems. A novel semi-homomorphic encrypted control framework, consisting of a logarithmic quantizer, two uniform quantizers, and an encrypted control law based on the Paillier cryptosystem is developed. More specifically, a logarithmic quantizer is adopted as a digitizer to convert the continuous relative motion information to digital signals. Two uniform quantizers with different quantization sensitivities are designed to encode the control gain matrix and digitized motion information to integer values. Then, we develop an encrypted state-feedback control law based on the Paillier cryptosystem, which allows the controller to compute the control input using only encrypted data. Using the Lyapunov stability theory and the homomorphic property of the Paillier cryptosystem, we prove that all signals in the closed-loop system are uniformly ultimately bounded. Different from the traditional motion control laws of spacecraft, the proposed encrypted control framework ensures the security of the exchanged data over the communication network of the spacecraft, even when communication channels are eavesdropped by malicious adversaries. Finally, we verify the effectiveness of the proposed encrypted control framework using numerical simulations

Adaptive Backstepping Control for Air-Breathing Hypersonic Vehicles with Input Nonlinearities

This paper addresses the control problem of air-breathing hypersonic vehicles subject to input nonlinearities, aerodynamic uncertainties and flexible modes. An adaptive backstepping controller and a dynamic inverse controller are developed for the altitude subsystem and the velocity subsystem, respectively, where the former eliminates the problem of “explosion of terms” inherent in backstepping control. Moreover, a modified smooth inverse of the dead-zone is proposed to compensate for the dead-zone effects and reduce the computational burden. Based on this smooth inverse, an input nonlinear pre-compensator is designed to handle input saturation and dead-zone nonlinearities, which leads to a simpler control design for the altitude subsystem subject to these two input nonlinearities. It is proved that the proposed controllers can guarantee that all closed-loop signals are bounded and the tracking errors converge to an arbitrarily small residual set. Simulation results are carried out to demonstrate the effectiveness of the proposed control scheme

ADP-based spacecraft attitude control under actuator misalignment and pointing constraints

This paper is devoted to real-time optimal attitude reorientation control of rigid spacecraft control. Particularly, two typical practical problems - actuator misalignment and forbidden pointing constraints are considered. Within the framework of adaptive dynamic programming (ADP), a novel constrained optimal attitude control scheme is proposed. In this design, a special reward function is developed to characterize the environment feedback and deal with the pointing constraints. Notably, a novel argument term is introduced to the reward function for overcoming the inevitable difficulty in actuator misalignment. By virtue of the Lyapunov stability theory, the ultimate boundedness of state error and the optimality of the proposed method can be guaranteed. Finally, the effectiveness and performance of the developed ADP-based controller are evaluated by not only numerical simulations but also experimental tests with a hardware-in-loop platform

Learning-based 6-DOF control for autonomous proximity operations under motion constraints

This paper proposes a reinforcement learning (RL)-based six-degree-of-freedom (6-DOF) control scheme for the final phase proximity operations of spacecraft. The main novelty of the proposed method are from two aspects: 1) the closed-loop performance can be improved in real-time through the RL technique, achieving an online approximate optimal control subject to the full 6-DOF nonlinear dynamics of spacecraft; 2) Nontrivial motion constraints of proximity operations are considered and strictly obeyed during the whole control process. As a stepping stone, the dual-quaternion formalism is employed to characterize the 6-DOF dynamics model and motion constraints. Then, an RL-based control scheme is developed under the dual-quaternion algebraic framework to approximate the optimal control solution subject to a cost function and a Hamilton-Jacobi-Bellman equation. In addition, a specially designed barrier function is embedded in the reward function to avoid motion constraint violations. The Lyapunov-based stability analysis guarantees the ultimate boundedness of state errors and the weight of NN estimation errors. Besides, we also show that a PD-like controller under dual-quaternion formulation can be employed as the initial control policy to trigger the online learning process. The boundedness of it is proved by a special Lyapunov strictification method. Simulation results of prototypical spacecraft missions with proximity operations are provided to illustrate the effectiveness of the proposed method

Optimized data-driven prescribed performance attitude control for actuator saturated spacecraft

This article addresses the crucial requirements in spacecraft attitude control: prescribed performance guarantees under actuator saturation and real-time cost optimization. As an application-oriented study, an approximate optimal prescribed performance attitude control scheme is proposed for this objective. To be specific, the prescribed performance constraint is converted into the system dynamics and merged into the adaptive dynamic programming design philosophy. Subsequently, the online learning law is designed based on a special saturated HJB error, in which a dynamical scale is introduced to adjust the learning gain by measured data. It enhances learning efficiency and applicability. Then, uniformly ultimately bounded stability of the whole system is achieved with guaranteed convergence of optimization by the Lyapunov-based stability analysis. Finally, both numerical simulation and hardware-in-the-loop experiments demonstrate the superiority and effectiveness of the proposed method. These attributes and outcomes attained will promote the development of practical space missions

Optimized operational approach for multi-type reactive power compensation to enhance the grid integration strength of new energy clusters

The insufficient system strength in the high-proportion new energy access area has gradually emerged as a crucial factor contributing to the transient overvoltage issue. Therefore, it is imperative to propose a reactive power optimization operation mode that takes into consideration both the power grid strength and system operating voltage of the new energy cluster system. Firstly, the relationship between the evaluation index of power grid strength and the performance of system voltage response is elucidated, while analyzing the influence mechanism of various reactive power compensation devices on the power grid strength of new energy cluster systems. Then, a reactive power operation optimization model is proposed to maximize the strength of the system grid and minimize the voltage deviation. To solve this problem, a hybrid approach combining genetic algorithm and CPLEX solver is employed. Finally, the effectiveness of the proposed method is validated through a typical simulation example

Learning-based attitude tracking control with high-performance parameter estimation

This paper aims to handle the optimal attitude tracking control tasks for rigid bodies via a reinforcement learning-based control scheme, in which a constrained parameter estimator is designed to compensate system uncertainties accurately. This estimator guarantees the exponential convergence of estimation errors and can strictly keep all instant estimates always within pre-determined bounds. Based on it, a critic-only adaptive dynamic programming (ADP) control strategy is proposed to learn the optimal control policy with respect to a user-defined cost function. The matching condition on reference control signals, which is commonly employed in relevant ADP design, is not required in the proposed control scheme. We prove the uniform ultimate boundedness of the tracking errors and critic weight's estimation errors under finite excitation conditions by Lyapunov-based analysis. Moreover, an easy-to-implement initial control policy is designed to trigger the real-time learning process. The effectiveness and advantages of the proposed method are verified by both numerical simulations and hardware-in-loop experimental tests

Incremental twisting fault tolerant control for hypersonic vehicles with partial model knowledge

A passive fault tolerant control scheme is proposed for the full reentry trajectory tracking of a hypersonic vehicle in the presence of modelling uncertainties, external disturbances, and actuator faults. To achieve this goal, the attitude error dynamics with relative degree two is formulated first by ignoring the nonlinearities induced by the translational motions. Then, a multivariable twisting controller is developed as a benchmark to ensure the precise tracking task. Theoretical analysis with the Lyapunov method proves that the attitude tracking error and its first-order derivative can simultaneously converge to the origin exponentially. To depend less on the model knowledge and reduce the system uncertainties, an incremental twisting fault tolerant controller is derived based on the incremental nonlinear dynamic inversion control and the predesigned twisting controller. Notably, the proposed controller is user friendly in that only fixed gains and partial model knowledge are required

Sensor-based robust incremental three-dimensional guidance law with terminal angle constraint

In this work, a robust incremental three-dimensional (3D) guidance law is proposed considering terminal angle constraint against maneuvering targets. As a stepping stone, the line-of-sight (LOS) tracking error dynamics is employed for the 3D guidance law design. A sliding variable is constructed such that its first-order derivative excludes the relative range in the perturbation, which avoids the unboundedness of system perturbation induced by target maneuvers near collision. A time-varying version of the sliding variable is designed to accelerate convergence of the LOS tracking errors and avoid large initial sliding variables. Then, two guidance laws are derived as a benchmark via the nonlinear dynamic inversion (NDI)-based sliding mode control (NDI-SMC) and NDI-based time-varying sliding mode control (NDI-TVSMC), respectively. To further improve guidance robustness with reduced system perturbation, the sensor-based incremental nonlinear dynamic inversion (INDI) control is used to design the INDI-SMC-based and INDI-TVSMC-based guidance laws. The sensor-based guidance laws exploit the LOS angular acceleration and guidance command output at the latest step, which result in smaller guidance gains to reject the perturbation than the NDI guidance laws. Numerical simulations in various cases and comparison studies are conducted to verify the effectiveness and robustness of the proposed method