Satellite Attitude Control System Research Articles

Kalman filter and satellite attitude control system analytical design

Kalman filter and satellite attitude control system analytical design

Two-stage exogenous Kalman filter for time-varying fault estimation of satellite attitude control system

This paper addresses the study of observer-based two-stage extended Kalman filter (TSEKF) estimation problem for the satellite attitude control system (ACS) in the presence of unknown time-varying actuator faults. In the traditional TSEKF methods, the considered faults always refers to constant signal in the propagation of the filter estimation, even though time-varying faults are taken into account in simulation demonstrations. In order to promote the accuracy of the TSEKF algorithm, a nonlinear observer is designed to obtain the fault dynamics and the state estimation with consideration of the nonlinear nature of the satellite ACS, and its estimation results are treated as exogenous signals used for linearizing the nonlinear ACS model. Then based on the observed fault information and the linearized ACS model, the TSEKF estimator is designed to obtain the exogenous filtering scheme, which can simultaneously reconstruct the state and faults accurately. Finally, by using the so called two-stage exogenous Kalman filter (TSXKF), simulation results show that when a time-varying fault occurs, more ideal estimation results can be obtained than those of TSEKF and better dynamic performance can be achieved than that of nonlinear observers.

Fault Detection and Avoidance for Spacecraft Failure using PSO Algorithm

Fault detection algorithm design of satellite inflight control is important for most remote sensing satellites. The responsibility of a satellite attitude control system always keeps the satellite in a stable mode. A satellite control mode contains standby, imaging and detumbling modes. Before we start imaging, we used to prepare an attitude control system to change satellite angles according to payload camera planning schedule to shoot a specific area of interest. After imaging is complete, the attitude control changes satellite angles back to nadir (zero tilting angels). Some control problems may cause failures which put the satellite in a detumbling mode due to accumulated torque on reaction wheel of the satellite. Artificial intelligent design algorithm of particle swarm optimization (PSO) is proposed to control the satellite in real-time mode, which decreases the angular velocity received from the satellite. This approach calculates the difference between the real-time measurement and the designed angular velocity (∆θ) within the satellite communication session time. The Matlab customization function implements PSO controller. The mathematical model of satellite attitude control system has been designed according to the satellite dynamics and kinematics laws. The approached mathematical model is implemented using Simulink Matlab tools.

Parity space-based fault isolation using minimum error minimax probability machine

In this paper, a new parity space-based fault isolation (FI) approach is proposed for linear discrete time-invariant systems. The main contribution lies in the integrated design of FI system and fault isolability properties without any assumptions on the probability distribution of unknown inputs. First, a fault isolability evaluation index is defined as the worst-case probability of correct FI in different faulty scenarios, and a new objective function is proposed for the integrated design of parity space-based residual generator, evaluation logic and fault isolability properties. Based on this, the FI problem is formulated as a bank of optimal multiclass classification problems. Next, using the technique of minimum error minimax probability machine (MEMPM), a group of feasible parity space matrices for residual generation are obtained. Furthermore, the FI method by MEMPM is presented with a desirable trade-off between the fault isolability properties in different faulty scenarios. To show the effectiveness of the proposed method, a satellite attitude control system subject to six faults is considered.

Fault Prediction of Satellite Attitude Control System Based on Neural Network

Fault Prediction of Satellite Attitude Control System Based on Neural Network

Probability Analysis of Fault Diagnosis Performance for Satellite Attitude Control Systems

In this paper, we focus our study on analysis of fault diagnosis performance for satellite attitude control systems subject to $l_{2}$ -norm-bounded process disturbances and measurement noises, which concerns with fault detectability and fault isolability. For an observer-based fault detection (FD), a major concern is to answer if the choice of a threshold satisfies an acceptable trade-off between fault detection rate (FDR) and false alarm rate (FAR). The smaller a threshold is, the better is the FDR, but the poorer is the FAR. In addition to this, knowledge of fault isolability is useful for answering how difficult it is to isolate a fault from another one. The main contributions of this paper are the probabilistic performance evaluation of the FD system in the context of FAR and a contribution analysis-based method of fault isolation. First, an extended $H_{i}/H_{\infty }$ optimization-based FD scheme is applied to the satellite attitude control systems and a recursive algorithm is presented to the implementation of online FD. Second, regarding the uncertain statistical characteristics of the unknown inputs, randomized algorithms are developed to verify the achievable FAR for a prescribed given threshold. Especially, without knowing the $l_{2}$ -norm boundedness of the unknown inputs, a probabilistic estimation of worst case threshold is also obtained to guarantee an acceptable level of FAR. Third, a contribution analysis-based method of fault isolation is proposed for satellite attitude control systems. Finally, the effectiveness of the proposed algorithms is verified through a satellite attitude control system.

Intelligent Fuzzy PD+I Controller with Stabilizer for Nano Satellite Attitude Control System

This paper discusses the variation of proportional and derivative gains in a system under the control of PD+I controller that uses fuzzy inference method an effort is made to design the fuzzy proportional-derivative (PD) + I controller for a nonlinear the proposed fuzzy PD + I structure shows superior performance in the Nano-satellite attitude control system. Given that 2-input PD type controllers are commonly used to control Nano satellite attitude systems (Innovative Satellite InnoSAT), This paper analysis the performance of Fuzzy PD+I on satellite system. Fuzzy PD+I controller design can control Nano satellite attitude control system nicely and utilized the Fuzzy PD+I controller which optimize the stability of the Nano Satellite control system. In addition, the scheme is robust to variations in nonlinearities, as well as the steady-state gain of the plant. We illustrate the effectiveness of our scheme In MATLAB / SMULINK simulation environment.

Fault Identification for a Closed-Loop Control System Based on an Improved Deep Neural Network.

Fault identification for closed-loop control systems is a future trend in the field of fault diagnosis. Due to the inherent feedback adjustment mechanism, a closed-loop control system is generally very robust to external disturbances and internal noises. Closed-loop control systems often encourage faults to propagate inside the systems, which may lead to the consequence that faults amplitude becomes smaller and fault characteristics difference becomes more inapparent. Hence, it has been challenging to achieve fault identification for such systems. Traditional fault identification methods are not particularly designed for closed-loop control systems and thus cannot be applied directly. In this work, a new fault identification method is proposed, which is based on the deep neural network for closed-loop control systems. Firstly, the fault propagation mechanism in closed-loop control systems is theoretically derived, and the influence of fault propagation on system variables is analyzed. Then deep neural network is applied to find fault characteristics difference between different data modes, and a sliding window is used to amplify the fault-to-noise ratio and characteristics difference, with an aim to increase the identification performance. To verify this method, the simulations that are based on a numerical simulation model, the Tennessee industrial system and the satellite attitude control system are conducted. The results show that the proposed method is more feasible and more effective in fault identification for closed-loop control systems compared with traditional data-driven identification methods, including distance-based and angle-based identification methods.

Modeling and Simulation of Satellite Attitude Dynamics and Control System using Modelica

The control of attitude of a satellite is difficult to verify since several subsystems of different disciplines, e.g., flexible multibody dynamics, machines, electronics and control, are involved and strongly coupled. A traditional method is to model each single discipline subsystem with a domain specific software, and combine them through interfaces. However, the problems are that lots of interfaces between software have to be developed, and manual decoupling of systems should be considered during modelling process. In this Paper, models of the dynamics and the control system are established in a unified modelling software, MWorks, which is an Integrated Development Environment of Modelica. The model can be used to verify the satellite control strategy, and also provide an effective means for satellite attitude control system design. Moreover, on this basis, the whole satellite was modelled to access state parameters changes under the coupling of the dynamic subsystem, the attitude control subsystem, the power supply subsystem, the propulsion subsystem and the integrated electronic subsystem can be synthetically considered.

Small fault detection method for actuator of satellite attitude control system

Small fault detection method for actuator of satellite attitude control system

Minimum-Time Attitude Maneuver and Robust Attitude Control of Small Satellite Mounted with Data Relay Communication Antenna

This paper proposes a nonlinear control method for carrying out Minimum-time satellite attitude maneuver and antenna motion which have robustness against model uncertainty. In recent years, small Earth observation satellites have been utilized and expected to maneuver rapidly in missions such as multi-target acquisition. On the other hand, small satellites need to send the observation data to ground station. Recently, small Earth observation satellites acquire high-resolution data, resulting in an increase in the time required for data communication. Thus, small satellites need to use inter-orbit communication link through Data Relay test satellite sending data from Data Relay communication (DRC) antenna. In conventional operations, the antenna motion is implemented after satellite attitude maneuver. However, this method has a time delay between the completion of the attitude maneuver and the start of data communication. The purpose of this study is to extend the time of earth observation and data communication by carrying out satellite maneuver and antenna motion concurrently. Because small satellite mounted with DRC antenna has large mass ratio of the antenna, we cannot ignore time variability of the moment of inertia of the whole system and reaction torque generated by antenna motion. Hence, in order to take the influence of the antenna motion into consideration, we combine a satellite attitude control system and an antenna drive system into one control system by governing equations and constructing the optimal control problem. We convert the optimal control problem into a NLP by discretizing the control input (a series of pulses) to minimize the final time of the total maneuver that includes the antenna adjustment. In addition, it is considered that a model uncertainty and unknown disturbance occurs in real space. Thus, we have to design feedback controller to secure robustness in model error and unknown disturbance. Accordingly in order to propose a nonlinear control method for carrying out minimum-time satellite attitude maneuver and antenna motion which have robustness against model uncertainty and unknown disturbance, we calculate a reference attitude by application of optimal control input torque to ideal satellite model and design servo controller by using state-dependent Riccati equation (SDRE) control method in order to track time-variant reference attitude.

Active Fault-tolerant Gyromoment Control of Satellites and Free-flying Robots

Abstract The methods for modeling and detection of anomalous in the automatic control systems, and also practical methods for active analysis of anomalous situations, are presented. We develop algorithms for consecutive classification of onboard equipment failures and reconfiguration of control loop. The simulation results are presented for the attitude control systems of the information satellites and space robots.

Fault Detection Method of Luojia1-01 Satellite Attitude Control System Based on Supervised Local Linear Embedding

This paper is aimed at the telemetry data of Luojia1-01 satellite attitude control system, and carries out the research on high-dimensional data feature extraction and fault detection based on supervised local linear embedding (SLLE). Because the general linear feature extraction method can not mine the feature information of nonlinear high-dimensional telemetry data, a data feature extraction and fault detection method based on local linear embedding is designed. Combined with the statistics SPE and T 2 , the low-dimensional feature information is obtained for data statistics and monitoring faults. Due to the local linear embedded manifold learning method for the traditional batch processing mode is difficult to update and improve the database online, and the supervised local linear embedding method is introduced. The online sample feature extraction and fault detection schemes are designed, and the database is updated by updating the weight matrix through online samples. Finally, the effectiveness of the method is verified by Luojia1-01 satellite telemetry data. The results show that the fault detection method based on SLLE reduces the false alarm rate (FAR) by approximately 3% and the missing alarm rate (MAR) by approximately 10% compared with local linear embedding (LLE). This method effectively improves the detection capability of the anomalous state of Luojia1-01 satellite and has certain engineering application value.

Timepix in LEO Orbit onboard the VZLUSAT-1 Nanosatellite: 1-year of Space Radiation Dosimetry Measurements

The VZLUSAT-1 satellite, the first Czech CubeSat, was successfully launched on June 23, 2017, to a 510 km Sun-synchronous low-Earth orbit. It carries several scientific payloads including a Timepix detector as focal plane imager for the X-Ray telescope onboard. The Timepix detector contributes significantly to the satellite data collection, with more than 25 000 sampling acquisitions in the first year of deployment. Despite limitations of the satellite attitude control system, necessary for capturing X-Ray images of the Sun, the Timepix detector allows measuring the space radiation environment along the satellite orbit. As of September 2018, we conducted 33 whole-Earth mappings, recording radiation doses around the planet. Further, we show data from scans of the South Atlantic Anomaly and polar radiation horns, where the location and acquisition time were tailored to minimize event pile-up and particle track overlap. Since October 2017, the optics segment of the onboard X-Ray telescope was deployed, which exposed the Timepix detector unshielded to free open space. This change produced entirely new observations namely of low energy charged particles and a significant increase of measured particle flux. We also registered the effects of exposing the sensor to direct intense sunlight. We will summarize on the actual performance of the custom readout interface, which exceeds expectations in the constrained environment of the low-cost and low-powered CubeSat nanosatellite.

Modified L1 Adaptive Control Design for Satellite FMC Systems with Actuators Time Delay

A modified method for satellite attitude control system in presence of novel actuators is proposed in this paper. The attitude control system is composed of three fluidic momentum controller (FMC) actuators that are used to control Euler angles and their dynamics is considered in satellite attitude equations as well. L1 adaptive control is utilized for satellite three-axial stabilization. A significant characteristic of L1 adaptive control structure is that robustness is guaranteed in presence of fast adaptation. The main achievement of this controller is that the error norm is inversely proportional to the square root of adaptation gains. Therefore, large values of gains provides some advantages. The proposed L1 adaptive control is designed based on simplified attitude dynamic equations without satellite coupling effects, and then it is placed on coupled nonlinear equations. Next, the impact of available delay on FMC actuators is investigated. Simulation results suggest that the system remains stable with the assumption of actuators time delay, but it experiences some oscillations in Euler angles, control inputs and angular velocities. In order to solve this problem, a modified L1 adaptive control system including a predictive observer with high estimation speed is used. Finally, it is recognized that the available oscillations are reduced even when the actuator time delay increases and thus the control system’s performance improves.

Model-based deep reinforcement learning with heuristic search for satellite attitude control

PurposeRecently, deep reinforcement learning is developing rapidly and shows its power to solve difficult problems such as robotics and game of GO. Meanwhile, satellite attitude control systems are still using classical control technics such as proportional – integral – derivative and slide mode control as major solutions, facing problems with adaptability and automation.Design/methodology/approachIn this paper, an approach based on deep reinforcement learning is proposed to increase adaptability and autonomy of satellite control system. It is a model-based algorithm which could find solutions with fewer episodes of learning than model-free algorithms.FindingsSimulation experiment shows that when classical control crashed, this approach could find solution and reach the target with hundreds times of explorations and learning.Originality/valueThis approach is a non-gradient method using heuristic search to optimize policy to avoid local optima. Compared with classical control technics, this approach does not need prior knowledge of satellite or its orbit, has the ability to adapt different kinds of situations with data learning and has the ability to adapt different kinds of satellite and different tasks through transfer learning.

Fault diagnosis method for closed-loop satellite attitude control systems based on a fuzzy parity equation

This article proposes a fault diagnosis method for closed-loop satellite attitude control systems based on a fuzzy model and parity equation. The fault in a closed-loop system is propagated with the feedback loop, increasing the difficulty of fault diagnosis and isolation. The study uses a Takagi-Sugeno (T-S) fuzzy model and parity equation to diagnose and isolate a fault in a closed-loop satellite attitude control system. A fully decoupled parity equation is designed for the closed-loop satellite attitude control system to generate a residual that is sensitive only to a specific actuator and sensor. A T-S fuzzy model is used to describe the nonlinear closed-loop satellite attitude control system. With the combination of the T-S fuzzy model and fully decoupled parity equation, the fuzzy parity equation (FPE) of the nonlinear system can be obtained. Then this article uses a parameter estimator based on a Kalman filter to identify deviations and scale factor changes from information contained in the residuals generated by the FPE. The actuator and sensor fault detection and isolation simulation of the three-axis stable satellite attitude control system is provided for illustration.

Comparing fluid ring and CMG servomechanisms for active control of rigid satellites

Purpose This paper aims to describe a novel type of attitude control system (ACS) in different configurations. This servomechanism is compared with control moment gyro (CMG) in significant parameters of performance for ACS of rigid satellite. Design/methodology/approach This new actuator is the fluid containing one or more rings and fluid flow is supplied by pump. The required torque control is obtained by managing fluid angular velocity. The cube-shaped satellite with three rings of fluid in the principle axes is considered for modeling. The satellite is considered rigid and nonlinear dynamics equation is used for it. In addition, the failure of the pyramid-shaped satellite with an additional ring fluid is discussed. Findings The controller model for four fluid rings has more complexity than for three fluid rings. The simulation results illustrated that four fluid rings need less energy for stabilization than three fluid rings. The performance of this type of actuator is compared with CMG. At last, it is demonstrated that performance parameters are improved with fluid ring actuator. Research limitations/implications Fluid ring actuator can be affected by environmental pressure and temperature. Therefore, freezing and boiling temperature of the fluid should be considered in system designation. Practical implications Fluid ring servomechanism can be used as ACS in rigid satellites. This actuator is compared by CMG, the prevalent actuator. It has less displacement attitude maneuver. Originality/value The results provide the feasibility and advantages of using fluid rings as satellite ACS. The quaternion error controller is used for this model to enhance its performance.

Observer‐Based Multiple Faults Diagnosis Scheme for Satellite Attitude Control System

AbstractThis paper proposes a multiple fault diagnosis (MFD) scheme based on an observer method for satellite attitude control systems (ACSs) subject to nonlinearity and external disturbances of the system. The essential idea is to develop a fault diagnosis scheme and design the corresponding observers for satellite ACSs. The nonlinearity, space external disturbances, sensor uncertainties, and multiple faults problem of the satellite ACS are all taken into account. The proposed MFD scheme is developed at two different levels. First, at the system level, two nonlinear observers based on analytical redundancy are designed for the MFD of the satellite ACS; this level roughly reveals the fault source. Then, at the component level, a bank of sliding mode observers activated by the results of the previous diagnosis is designed to precisely diagnose multiple faults of actuators in the satellite ACS; this level further precisely reveals the fault source. Both the nonlinear observers and the sliding mode observers are confirmed to be asymptotically stable via Lyapunov stability theory. Finally, numerical simulations of a satellite ACS are performed to illustrate the effectiveness of the proposed MFD scheme.

Design and analysis of an active gimbal simulator with three degrees-of-freedom for ground testing

In this paper, a new active gimbal simulator is developed for testing the attitude determination and control system of satellites. The active gimbal simulator is composed of a rolling joint, a pitching joint, a main support frame, an active yawing joint, and a fixture. The rolling joint enables the active gimbal simulator to be applied to the columnar satellite without the fixture. The contact forces between the rolling joint and the test satellite (or the fixture) can be regulated by the support of the pitching joint. The object attached to the active gimbal simulator is at neutral equilibrium and can maintain balance at an arbitrary attitude. Hence, the object can rotate freely without being affected by its gravity. The active gimbal simulator is an approximately free-to-free suspension or support method. Compared with the traditional gimbals, the active gimbal simulator can be applied to objects of arbitrary shape especially cylinders and the effect of exogenous mass and inertia introduced by the connection mechanism is reduced. The design parameters of the active gimbal simulator are optimized based on the force analysis. A specific prototype was made, and its feasibility was verified by laboratory-based experiments.