This paper deals with the general problem of space vehicle dynamics and control It presents the various approaches of this problem in a rather unified manner; the classical simplifying assumptions are curefully pointed out

Spacecraft dynamics and control

Recent advances in contact dynamics and post-capture control for combined spacecraft

Display Omitted We propose a new algorithm to control DC-DC converters.The new algorithm is based on Particle Swarm Optimization.The proposed controller does not require any parameter search like classical controllers.We compare the proposed controller with the PI Anti-Windup controller.The proposed controller exhibits better performance in terms of settling time and steady state oscillations. We propose a new controller for DC-DC converters based on particle swarm optimization (PSO). This new converter controller uses the PSO optimization method to directly control, by itself, the output voltage of a boost DC-DC converter. In order to validate and qualify the proposed converter controller, we analyzed and implemented some variants of the PSO algorithm, namely the standard PSO and the global local best PSO. The proposed converter controller was then compared with a variant of the classic PI controller with anti-windup, for different operational conditions. The three controllers compared in this work were implemented in the microcontroller TMS320F28027 by using the code composer studio from Texas Instruments. The results show that the proposed controller exhibits better behavior in terms of settling time and overshoot. Unlike most popular DC-DC converter controllers, the proposed controller does not require any sort of optimal parameter determination.

A new controller for DC-DC converters based on particle swarm optimization

As more and more satellites are launched into the space, dynamic estimation of spin satellites has become a critical component of the space situation awareness application. Some explored studies using exterior measurements from different sensors such as optical device and inverse synthetic aperture radar (ISAR) to estimate dynamic parameters of spin satellites. As a single sensor normally provides two-dimensional observation, three-dimensional estimations resulting from these algorithms are strictly related to the prior knowledge of targets characteristics. As a result, it is difficult to expand these methods to other satellites. In order to support the dynamic estimation of most spin satellites, this paper presents a novel dynamic estimation approach which employs synchronized optical-and-radar images. The optical-and-radar fusion strategy has demonstrated its superiority in image analysis field, and breaks down the dynamic estimation of spin satellites into two sub-problems: target attitude estimation and spin parameters estimation. In this work, the proposed algorithm deduces two explicit expressions of target dynamic parameters under the imaging projection model of the joint optical-and-radar observation. Through the particle swarm optimization (PSO), target dynamic parameters are determined in two stages. This paper presents some experiments illustrating the feasibility of the proposed method and subsequent conclusions, which reflect advantages of the joint optical-and-radar observation mode in image interpretation.

Optical-and-Radar Image Fusion for Dynamic Estimation of Spin Satellites

Accurate attitude and heading reference system (AHRS) play an essential role in navigation applications and human body tracking systems. Using low-cost microelectromechanical system (MEMS) inertial sensors and having accurate orientation estimation, simultaneously, needs optimum orientation methods and algorithms. The error of attitude estimation may lead to imprecise navigation and motion capture results. This paper proposed a novel intermittent calibration technique for MEMS-based AHRS using error prediction and compensation filter. The method, inspired from the recognition of gyroscope's error and by a proportional integral (PI) controller, can be regulated to increase the accuracy of the prediction. The experimentation of this study for the AHRS algorithm, aided by the proposed prediction filter, was tested with real low-cost MEMS sensors consists of accelerometer, gyroscope, and magnetometer. Eventually, the error compensation was performed by post-processing the measurements of static and dynamic tests. The experimental results present about 35% accuracy improvement in attitude estimation and demonstrate the explicit performance of proposed method.

https://www.mdpi.com/1424-8220/20/14/4055/pdf

Accuracy Improvement of Attitude Determination Systems Using EKF-Based Error Prediction Filter and PI Controller.

Real-time sensor fault detection and isolation for LEO satellite attitude estimation through magnetometer data

The attitude determination and control subsystem (ADCS) requirement of payload on the Algerian Satellite (Alsat-1) is stringent enough to demand some type of data processing in order to meet attitude determination requirements. Two vector magnetometers and four dual sun sensors are carried in order to determine the attitude. This paper describes the various steps of the design and the implementation of the reduced model of the extended Kalman filter (6-state EKF) for small Euler angles on the Alsat-1. For the 6- state filter, the state vector defines not only the attitude of the satellite, but also the rates at which the attitude is changing. This paper examines the six state Kalman filter from a theoretical standpoint before examining practical implementation.

http://www.wseas.us/e-library/conferences/2011/Angers/ACMMA/ACMMA-02.pdf

Six state Kalman filtering for LEO microsatellite attitude determination

A147 estimation is one of the important aspects in Attitude Determination and Control System (ADCS) of a satellite. Under normal working conditions, it is possible to achieve sufficiently a good attitude estimation using regular Kalman filtering. However, in the presence of sensor faults, the filter fails to provide the desired accuracy and may deteriorate the attitude estimation. To overcome this imperfection, a Fault Tolerant Extended Kalman Filter (FTEKF) is presented in this paper to improve the state estimation reliability even in the sensor fault situation. In accordance, a model of sensitivity factor is applied in the fault detection design of the filter to detect gyroscope sensor faults. Numerical comparison with Robust Extended Kalman Filter (REKF) is carried out for performance assessment. The proposed filter is approved to be robust against gyroscope faults with better filtering performance.

Reliable Kalman Filtering for Satellite Attitude Estimation Under Gyroscope Partial Failure

This paper presents a brief synthesis and useful performance analysis of different attitude filtering algorithms (attitude determination algorithms, attitude estimation algorithms, and nonlinear observers) applied to Low Earth Orbit Satellite in terms of accuracy, convergence time, amount of memory, and computation time. This latter is calculated in two ways, using a personal computer and also using On-board computer 750 (OBC 750) that is being used in many SSTL Earth observation missions. The use of this comparative study could be an aided design tool to the designer to choose from an attitude determination or attitude estimation or attitude observer algorithms. The simulation results clearly indicate that the nonlinear Observer is the more logical choice.

https://iopscience.iop.org/article/10.1088/1742-6596/783/1/012017/pdf

Performance comparison of attitude determination, attitude estimation, and nonlinear observers algorithms

The satellite in geostationary orbit present many flexibility due to flexible appendages, solar pressure and fuel sloshing in the tanks which they pose great challenges for accurate attitude control. In this paper, an anti-disturbance proportional-derivative (PD) controller is designed to stabilize the attitude while rejecting the effects of flexible vibrations, environmental disturbances, and unmodeled dynamics, whose are assumed as an extended state. This controller comprises two parts, i.e. an extended state observer and a PD controller with feedforward. First, flexible vibrations, with fuel sloshing and environmental disturbances, and unmodeled dynamics are regarded as an extended state which can be estimated by the extended state observer. Then, the estimated extended state can be compensated by feedforward and the attitude can be stabilized by the PD controller. Numerical simulation results are presented to demonstrate the effectiveness of the control scheme.

A. Bellar

Papers

Real-time sensor fault detection and isolation for LEO satellite attitude estimation through magnetometer data

Six state Kalman filtering for LEO microsatellite attitude determination

Reliable Kalman Filtering for Satellite Attitude Estimation Under Gyroscope Partial Failure

Performance comparison of attitude determination, attitude estimation, and nonlinear observers algorithms

Extended state observer based control of attitude stabilization for flexible spacecraft with solar pressure and slosh disturbances