Attitude Control System Research Articles

Finite-horizon approximate optimal attitude control based on adaptive dynamic programming for ultra-low-orbit satellite

This study investigates the finite-horizon approximate optimal attitude control problem for ultra-low-orbit satellites, addressing the complexities introduced by substantial disturbance, actuator faults, actuator saturation, and time constraint. Initially, a fixed-time concurrent learning fault and disturbance estimation approach is proposed that relieves persistent excitation constraints and isolates different influences individually. Subsequently, the cost function is designed with actuator fault estimation, ensuring that the control strategy consistently adheres to actuator saturation constraints and can compensate for current faults. Furthermore, based on the adaptive dynamic programming, an approximate optimal attitude control approach is proposed, which employs time-varying activation functions to approximate the optimal cost function. A fixed-time neural network weight adaptation strategy is designed to ensure the precision and reliability of the approximation. Finally, the numerical simulation confirms the validity and practical applicability of the proposed approach in satellite attitude control systems.

Asymmetric full-state constrained attitude control for a flexible agile satellite with multiple disturbances and uncertainties

In this paper, an asymmetric full-state constrained attitude control method for a flexible agile satellite with multiple disturbances and uncertainties is proposed. Both the attitudes and angular velocities of the flexible agile satellite are guaranteed in the asymmetric/symmetric bounds by utilizing the time-varying integral barrier Lyapunov function (TVIBLF) and constant integral barrier Lyapunov function (IBLF) respectively. Compared with the existing error-based barrier Lyapunov functions, the asymmetric TVIBLF does not need error transformation, relaxes the conservation of the initial requirements, and has more compatibility. Furthermore, the proposed asymmetric TVIBLF can deal with the asymmetric time-varying constraints without loss of generality. In addition, the high-frequency flexible vibrations, inertial uncertainties, and unknown external disturbance torques affected on the agile satellite are considered respectively. On one hand, a modal observer is utilized to suppress the high-frequency flexible vibration effects on the attitudes. On the other hand, the inertial uncertainties and unknown external disturbance torques are estimated with a multi-variable nonlinear disturbance observer. Therefore, both the asymmetric full-state constrained performances and robustness of the attitude control system for the flexible agile satellite are achieved. The stability of the closed-loop system is proved and numerical simulations have validated the effectiveness of the proposed method.

Robust Distributed Observers for Simultaneous State and Fault Estimation over Sensor Networks

This paper focuses on simultaneous estimation of states and faults for a linear time-invariant (LTI) system observed by sensor networks. Each sensor node is equipped with an observer, which uses only local measurements and local interaction with neighbors for monitoring. The observability of said observer is analyzed where non-local observability of a sensor node is required in terms of the system state and faults. The distributed observers present features of H∞ performance to constrain the influence of disturbances on the estimation errors, for which the global design condition is transformed into a linear matrix inequality (LMI). The LMI is proven to be solvable given collective observability of the system and a suitable H∞ performance index. Moreover, in the case that no disturbances exist, fully distributed observers with adaptive gains are designed to asymptotically estimate the states and faults without using any global information from the network. Finally, the effectiveness of the proposed methods is verified through case studies on a spacecraft’s attitude control system.

Enhanced Fault Detection in Satellite Attitude Control Systems Using LSTM-Based Deep Learning and Redundant Reaction Wheels

Reliable fault detection in satellite attitude control systems stands as a critical aspect of ensuring the safety and success of space missions. Central to these systems, reaction wheels (RWs), despite being the most frequently used actuators, present a vulnerability given their susceptibility to faults—a factor with the potential to precipitate catastrophic failures such as total satellite loss. In light of this, we introduce a fault detection methodology grounded in deep learning techniques specifically designed for satellite attitude control systems. Our proposed method utilizes a Long Short-Term Memory (LSTM) model adept at learning temporal patterns inherent to both healthy and faulty system behaviors. Incorporated into our model is a torque allocation algorithm designed to circumvent specific velocities known to induce torque disturbances, a factor known to influence LSTM performance adversely. To bolster the robustness of our fault detection technique, we also incorporated denoising autoencoders within the LSTM framework, thereby enabling the model to identify temporal patterns in healthy and faulty system behavior, even amidst the noise. The method was evaluated using cross-validation on simulated satellite data comprising 1000 time series samples and across different fault scenarios, such as stiction and resonance at varying intensities (90%, 50%, and 30%). The results confirm achieving performance metrics such as Mean Squared Error for accurate fault identification. This research underscores a stride in the evolution of fault detection and control strategies for satellite attitude control systems, holding promise to boost the reliability and efficiency of future space missions.

Convex set reliability-based optimal attitude control for space solar power station with bounded and correlated uncertainties

Considering the bounded and correlated uncertainties in the inherently nonlinear attitude dynamics, this paper proposes an uncertain optimal attitude control for space solar power stations (SSPS), subjected to the convex set-based reliability constraint. To accurately and cost-effectively quantify the uncertainty in the SSPS attitude control system, the uncertain attitude dynamics are proposed based on nominal SSPS with convex set-based uncertainties. Given the known bounds and correlations of the random variables, the convex set-based attitude dynamics of SSPS can be conveniently constructed and transformed into corresponding uncertain state-space equations. Uncertain state and output can be solved using the extended-order matrix and uncertainty propagation method. A convex set-based Riccati equation is: developed using the convex set theory, traditional algebraic Riccati equation (ARE), and Lyapunov equation, which can obtain all the uncertain components of feedback gain, input torque, and cost function, respectively. Convex set-based time-dependent reliability (CSTR) is applied to assess the safety of the attitude control system by setting critical values and considering the time-dependent effect, which is regarded as an important constraint in the optimal attitude control issue with uncertainty. A numerical example of SSPS is provided to verify the proposed uncertain controller within the reliability-constrained optimization framework, demonstrating its effectiveness in managing nonlinear system dynamics under uncertainty.

New Approach of Hybrid Momentum Exchange Devices for Spacecraft Attitude Control System

New Approach of Hybrid Momentum Exchange Devices for Spacecraft Attitude Control System

USLC: Universal self‐learning control via physical performance policy‐optimization neural network

AbstractThis article proposes an online universal self‐learning control (USLC) algorithm based on a physical performance policy‐optimization neural network, which aims to solve the problem of universal self‐learning optimal control laws for nonlinear systems with various uncertain dynamics. As a key system characterization, this algorithm predicts the discrepancy between the optimal and current control laws by evaluating overall performance in each iterative learning cycle, leveraging an offline‐trained universal policy network. This approach is universal, as it does not rely on an exact system model and can adaptively control performance preferences across various tasks by customizing the physical performance cost weights. Using the established control law‐performance surface and contraction Lyapunov function, the necessary assumptions and proofs for the stable convergence of the system within a three‐dimensional manifold space are provided. To demonstrate the universality of USLC, simulation experiments are conducted on two different systems: a low‐order circuit system and a high‐order variable‐span aircraft attitude control system. The stable control achieved under varying initial values and boundary conditions in each system illustrates the effectiveness of the proposed method. Finally, the limitations of this study are discussed.

Feature-weighted Random Forest with Boruta for Fault Diagnosis of Satellite Attitude Control Systems

The performance of random forest (RF) based satellite attitude control system (ACS) fault diagnosis methods is limited by uninformative features in high-dimensional data. To solve this problem, we proposed a feature-weighted random forest with Boruta (FWRFB) based fault diagnosis method is proposed for fault diagnosis of ACSs. Firstly, a Boruta feature selection algorithm is used to obtain a feature set and determine significant feature weights. Subsequently, a novel feature-weighted random forest (FWRF) algorithm is designed, which utilizes feature-weighted random sampling instead of simple random sampling to generate feature subsets in the RF. The FWRFB effectively utilizes the feature information while mitigating noise interference. Finally, a FWRFB-based diagnostic module is developed for online fault diagnosis of ACSs. The effectiveness of the proposed method is verified by the ACS data from a semi-physical simulation platform.

Attitude Control System for Quadrotor Using Robust Monte Carlo Model Predictive Control

Monte Carlo Model Predictive Control (MCMPC) is a kind of non-linear Model Predictive Control (MPC) that determines control inputs using the Monte Carlo method. The Monte Carlo method used in MCMPC can handle discontinuous phenomena, and there have been reports of its application in control systems for quadrotors, where the objective is to maintain the stability of the attitude during collisions. However, as with conventional MPC, concerns remain about control performance degradation due to modeling errors and external disturbances such as unexpected wind gusts. In this study, we propose a novel Robust Monte Carlo Model Predictive Control (RMCMPC), which improves the robustness of MCMPC by considering the hypersurface known from the Sliding Mode Control (SMC) theory. The proposed RMCMPC is applied to a quadrotor attitude control system, and its effectiveness is validated through numerical simulations.

Improved Adaptive Sensor Fault Recovery for an Attitude Control System Simulator Using a New Terminal Sliding Mode Controller with Faster Convergence and Guaranteed Performance

Improved Adaptive Sensor Fault Recovery for an Attitude Control System Simulator Using a New Terminal Sliding Mode Controller with Faster Convergence and Guaranteed Performance

Adaptive multi-model predictive control with optimal model bank formation: Consideration of local models uncertainty and stability

The Multiple Model Control (MMC) structure comprises three main components: the model bank, controller bank, and supervisor algorithm. Precise design of these components is crucial for achieving high control performance within the MMC framework, albeit this effort is not without its challenges. These challenges involve optimizing the model and controller banks ensuring system stability when dealing with uncertainties in the local models and enabling smooth switching between model-controller pairs. This paper addresses these challenges by presenting a comprehensive approach. Firstly, the optimal model bank is designed using an automatic clustering approach. Then, the design of the adaptive multi-model predictive controller bank and a supervisor algorithm capable of performing soft switching are discussed. The proposed control system exhibits the capability to ensure closed-loop system stability within each individual subspace, as well as during the transitioning between distinct subspaces. This stability is preserved even in the face of inherent uncertainties associated with the local models comprising the model bank. To evaluate and validate the performance of the proposed control system, it is applied to a satellite attitude control system. The results confirm the effectiveness and performance of the control system. The proposed control system holds promise for controlling highly nonlinear, complex, or switched systems, ensuring closed-loop system stability, and achieving high control performance.

Study of the features of angular stabilization of spacecraft with flexible struc-tural elements with the use mobile control methods

The development of space power engineering is one of the well-known lines in rocket and space science and innovative technologies which attracts the attention of many scientists and researchers. Engineering solutions in space-based solar power plant design and wireless space-to-Earth and satellite-to-satellite power transmission and power spacecraft control methods have been substantiated theoretically to sufficient depth. However, despite this, there is a need to improve methods for and approaches to the development of an optimal design methodology for power spacecraft. A way to improve existing approaches to the development of space-based solar power plants and power satellites may be the use of mobile control methods in the development of an attitude and orbit control system. Such methods allow one to reduce power consumption for control operations. The goal of this paper is to study the features of mobile control and construct a methodology for the development of solar power satellites’ attitude and orbit control system (AOCS) using mobile control algorithms. The paper considers the features of mobile control algorithm synthesis for the attitude control and stabilization of solar power spacecraft (solar power plants and power satellites). Power spacecraft control tasks are classified, and the expediency of using mobile control methods is justified. An analysis is made for the stability problem that arises in controlling power spacecraft with flexible elements. The paper presents methodological recommendations on determining the AOCS design parameters for space-based solar power plants and power spacecraft for wireless satellite-to-satellite power transmission. This methodology may be used in power satellite development.

Swiftly Chasing Gravitational Waves across the Sky in Real Time

We introduce a new capability of the Neil Gehrels Swift Observatory, dubbed “continuous commanding,” that achieves 10 s latency response time on orbit to unscheduled target-of-opportunity requests received on the ground. We show that this will allow Swift to respond to premerger (early-warning) gravitational-wave (GW) detections, rapidly slewing the Burst Alert Telescope (BAT) across the sky to place the GW origin in the BAT field of view at or before merger time. This will dramatically increase the GW/gamma-ray burst (GRB) codetection rate and enable prompt arcminute localization of a neutron star merger. We simulate the full Swift response to a GW early-warning alert, including input sky maps produced at different early-warning times, a complete model of the Swift attitude control system, and a full accounting of the latency between the GW detectors and the spacecraft. 60 s of early warning can double the rate of a prompt GRB detection with arcminute localization, and 140 s guarantees observation anywhere on the unocculted sky, even with localization areas ≫1000 deg2. While 140 s is beyond current GW detector sensitivities, 30–70 s is achievable today. We show that the detection yield is now limited by the latency of LIGO/Virgo cyberinfrastructure and motivate a focus on its reduction. Continuous commanding has been integrated as a general capability of Swift, significantly increasing its versatility in response to the growing demands of time-domain astrophysics. We demonstrate this potential on an externally triggered fast radio burst (FRB), slewing 81° across the sky, and collecting X-ray and UV photons from the source position <150 s after the trigger was received from the Canadian Hydrogen Intensity Mapping Experiment, thereby setting the earliest and deepest such constraints on high-energy activity from nonrepeating FRBs. The Swift Team invites the community to consider and propose novel scientific applications of ultra-low-latency UV, X-ray, and gamma-ray observations.

In-orbit demonstration of acquisition and tracking on OSIRIS4CubeSat.

OSIRIS4CubeSat is the smallest commercially available laser communication terminal within the confines of 0.3-units. It was launched as PIXL-1 inside of a 3-unit CubeSat into space to demonstrate optical direct to earth links. This work primarily focuses on the commissioning phase, particularly emphasizing the performance of the active fine pointing and tracking mechanism. This steering mechanism, with a 1 degree radius field of regard, plays a decisive role in compensating for pointing inaccuracies from the satellite's attitude determination and control system. The design and validation of open-loop acquisition and closed-loop tracking are presented. The feedback sensor adapts to changing beacon power levels, that occur during a direct to earth link, by an adaptive gain control. Subsequent evaluation of satellite passes, with telemetry recordings obtained from the deployed CubeSat, showcases superior performance that meets the pointing requirements of the link budget. By using the developed control-loop logic, OSIRIS4CubeSat achieves a mean tracking error of 71 µrad, with a 3σ deviation of 140 µrad down to low power levels of 238 pW. These results serve as validation of OSIRIS4CubeSat, demonstrating its capability to enable high-speed data transmission from low Earth orbit to the Earth's surface at data rates of up to 100 Mbit/s.

Fabrication Time Diagrams for In-Space Manufacturing of Large Reticulated Structures

Abstract In-space manufacturing (ISM), or the construction of structures from raw feedstock materials in the space environment, is a promising approach for building large, external support structures for future space missions. Most research and development on ISM to date has focused on ground-based or microgravity-based demonstrations of candidate fabrication processes; however, the combined design of the ISM spacecraft and the fabrication process has not been fully investigated. In this paper, we estimate the fabrication times for truss support structures subject to various spacecraft constraints, including the available fabrication power, the attitude control system (ACS) authority, and the avoidance of control–structure interactions. Using the key assumptions of (1) a fabrication process that sequentially extrudes struts, (2) a fixed spacecraft orientation, and (3) negligible effects of environmental disturbance torques, we generate fabrication time diagrams that depict the dominant constraints and estimates of the fabrication time for a range of dimensions. Our results indicate that for large, dense reticulated geometries such as the curved gridshell and tetrahedral truss, the angular momentum storage of the spacecraft ACS is the dominant constraint on fabrication time. Additionally, our results suggest the following strategies for reducing fabrication time: manufacturing with multiple spacecraft; using stiff, lightweight feedstock; maximizing fabrication power and ACS capability; and minimizing spacecraft bus mass. These strategies represent design tradeoffs, emphasizing how the design of an ISM spacecraft cannot be considered independently of the fabricated structure.

Design of an Optimal Allocator for Power Consumption Minimization in Hexarotor Drone Control Systems

This paper presents an allocator design that considers the power consumption of rotors in the attitude and altitude control system of a hexarotor drone. Based on the power consumption model, the proposed method computes the thrust force that minimizes the total power consumption of the rotor while satisfying the control force constraints required by the controller. To obtain the rotor power consumption model, we conducted experiments on the rotor characteristics using the motors and electronic speed controllers used in the drones. Finally, numerical simulations were performed using the obtained power consumption models to compare the rotor power consumption of the proposed method with that of the conventional method, quantitatively evaluating the effectiveness of the proposed method.

Adaptive predefined-time precise anti-unwinding attitude control for a spacecraft with inertia uncertainty

This paper proposes an adaptive predefined-time accurate anti-unwinding attitude controller for a spacecraft with uncertain inertia. The novelty of the proposed algorithm lies in that the spacecraft attitude error is regulated to exact zero after a predefined settling time, which is an explicit parameter in the control algorithm. A time mapping function containing the predefined settling time is introduced, thus transforming the time scale of the original attitude control system. Then a composite barrier Lyapunov function is constructed to avoid the unwinding phenomenon in the attitude control process, and an adaptive backstepping attitude controller is designed based on the attitude system in the new time scale. The stability analysis of the attitude system is carried out based on LaSalle-Yoshizawa theorem, and it is proved that the attitude quaternion and angular rate can converge to zero accurately within the desired predefined time without using the spacecraft inertia information. Numerical simulation results show the effectiveness and superiority of the proposed controller.

Reliability modeling of multi-state phased mission systems with random phase durations and dynamic combined phases

Random phase durations and dynamic combined phases challenge the application of existing reliability models in the reliability analysis of multistate-phased mission systems (MS-PMSs). To this end, this paper presents a new reliability modeling method for multi-state phased mission systems with random phase durations and dynamic combined phases. Initially, a multi-state multi-valued decision diagram-based (MMDD-based) reliability modeling method is created to efficiently map random phase durations and the dynamic combined phase nature of MS-PMSs into the reliability model. To solve the MMDD-based reliability model, a path probability evaluation method is subsequently constructed with the assistance of the Markov regenerative function. The effectiveness and the superior performance of the proposed MMDD-based reliability model and its solving algorithm are validated by the application to the reliability modeling and analysis of an attitude and orbit control system with multiple modes. Overall, this paper provides the reliability sector with a new reliability model and its solving algorithm to enhance the reliability and safety of multi-state phased mission systems.

A Model-Free Adaptive Positioning Control Method for Underactuated Unmanned Surface Vessels in Unknown Ocean Currents

Aiming to address the problem of underactuated unmanned surface vehicles (USVs) performing fixed-point operations at sea without dynamic positioning control systems, this paper introduces an original approach to positioning control: the virtual anchor control method. This method is applicable in environments with currents that change slowly and does not require prior knowledge of current information or vessel motion model parameters, thus offering convenient usability. This method comprises four steps. First, a concise linear motion model with unknown disturbances is proposed. Then, a motion planning law is designed by imitating underlying principles of ship anchoring. Next, an adaptive disturbance observer is proposed to estimate uncertainties in the motion model. In the last step, based on the observer, a sliding-mode method is used to design a heading control law, and a thrust control law is also designed by applying the Lyapunov method. Numerical simulation experiments with significant disturbances and tidal current variations are conducted, which demonstrate that the proposed method has a good control effect and is robust.

Self-triggered MPC with adaptive prediction horizon for nano-satellite attitude control system

Nano-satellites are essential tools for various applications, including scientific experiments, deep space exploration and astronomical observation. Achieving precise model predictions is crucial for their successful operation. To address the intricate constraints of nano-satellites and enhance control performance, the Model Predictive Control (MPC) algorithm is an effective solution. However, implementing an MPC-based attitude control system in actual engineering scenarios presents significant challenges, primarily due to the substantial computational burden, especially given the limited onboard computing resources of nano-satellites. In this paper, we introduce a modified adaptive self-triggered model predictive control (ST-MPC) algorithm designed to stabilize the attitude of nano-satellites, while simultaneously reducing communication and computational overhead compared to traditional MPC methods. The proposed self-triggered mechanism dynamically determines the next trigger time according to the system state. Moreover, we incorporate considerations for the efficiency of actuators to address the constraints imposed by the magnetic torque characteristics within the modified self-triggered mechanism. Additionally, a strategy for adaptive prediction horizon is proposed to balance computation load and control accuracy. The results of our simulations demonstrate the effectiveness of the modified ST-MPC algorithm in comparison to both traditional MPC and standard ST-MPC approaches. This algorithm may have the potential to significantly impact attitude control applications for nano-satellites.