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This paper aims to investigate the fast attitude coordinated control problem for rigid satellite swarms with communication delays.

Based on behavior‐based control approach, the attitude control system is designed to guarantee that the attitude of the satellite swarm converge to a dynamic reference state in finite time. A fast sliding mode is developed to improve the convergence rate and robustness of the control system. All the effects of communication delays, parameter uncertainties and external disturbances are taken into account simultaneously, and the communication topology of the satellite swarm can be arbitrary types. Numerical simulations are provided to demonstrate the analytic results.

Despite the existence of communication delays, parameter uncertainties and external disturbances, the stability of the closed‐loop system can be successfully guaranteed and the proposed control strategies are effective to overcome these unexpected phenomena subject to arbitrary communication topology.

This paper introduces a fast terminal sliding mode control method which can guarantee the fast convergence of the attitude state of the satellite swarm in the presence of communication delays, switched communication topology, parameter uncertainties and external disturbances.

The main reason for the low accuracy of magnetometer-based autonomous orbit determination is the coarse accuracy of the geomagnetic field model. Furthermore, the geomagnetic field model error increases obviously during geomagnetic storms, which can still further reduce the navigation accuracy. The purpose of this paper is to improve the accuracy of magnetometer-based autonomous orbit determination during geomagnetic storms.

In this paper, magnetometer-based autonomous orbit determination via a measurement differencing extended Kalman filter (MDEKF) is studied. The MDEKF algorithm can effectively remove the time-correlated portion of the measurement error and thus can evidently improve the accuracy of magnetometer-based autonomous orbit determination during geomagnetic storms. Real flight data from Swarm A are used to evaluate the performance of the MDEKF algorithm presented in this study. A performance comparison between the MDEKF algorithm and an extended Kalman filter (EKF) algorithm is investigated for different geomagnetic storms and sampling intervals.

The simulation results show that the MDEKF algorithm is superior to the EKF algorithm in terms of estimation accuracy and stability with a short sampling interval during geomagnetic storms. In addition, as the size of the geomagnetic storm increases, the advantages of the MDEKF algorithm over the EKF algorithm become more obvious.

The algorithm in this paper can improve the real-time accuracy of magnetometer-based autonomous orbit determination during geomagnetic storms with a low computational burden and is very suitable for low-orbit micro- and nano-satellites.

Keeping satellite position within close tolerances is key for the utilization of satellite formations for space missions. The presence of perturbation forces makes control inevitable if such mission objective is to be realised. Various approaches have been used to obtain feedback controller parameters for satellites in a formation; this paper aims to approach the problem of estimating the optimal feedback parameter for a leader–follower pair of satellites in a small eccentric orbit using nature-based search algorithms.

The chaotic artificial bee colony algorithm is a variant of the basic artificial bee colony algorithm. The algorithm mimics the behaviour of bees in their search for food sources. This paper uses the algorithm in optimizing feedback controller parameters for a satellite formation control problem. The problem is formulated to optimize the controller parameters while minimizing a fuel- and state-dependent cost function. The dynamical model of the satellite is based on Gauss variational equations with J2 perturbation. Detailed implementation of the procedure is provided, and experimental results of using the algorithm are also presented to show feasibility of the method.

The experimental results indicate the feasibility of this approach, clearly showing the effective control of the transients that arise because of J2 perturbation.

This paper applied a swarm intelligence approach to the problem of estimating optimal feedback control parameter for a pair of satellites in a formation.

This paper aims to present an innovative system able to establish an inter-satellite communication crosslink and to determine the mutual physical positioning for CubeSats belonging to a swarm.

Through a system involving a smart antenna array managed by a beamforming control strategy, every CubeSat of the swarm can measure the direction of arrival (DOA) and the distance (range) to estimate the physical position of the received signal. Moreover, during the transmission phase, the smart antenna shapes the beam to establish a reliable and directive communication link with the other spacecraft and/or with the ground station. Furthermore, the authors introduce a deployable structure fully developed at Politecnico di Torino that is able to increase the external surface of CubeSats: this surface allows to gain the interspace between elements of the smart antenna.

As a consequence, the communication crosslink, the directivity and the detection performance of the DOA system in terms of directivity and accuracy are improved.

Moreover, the deployable structure offers a greater usable surface, so a larger number of solar panels can be used. This guarantees up to 25 W of average power supply for the on-board systems and for transmission on a one-unit (1U) CubeSat (10 × 10 × 10 cm).

This paper describes the physical implementation of the antenna array system on a 1U CubeSat by using the deployable structure developed. Depending on actuators and ability that every CubeSat disposes, various interaction levels between elements can be achieved, thus making the CubeSat constellation an efficient and valid solution for space missions.

The capability to predict and evaluate various configurations’ performance during the conceptual design phase using multidisciplinary design analysis and optimization can significantly increase the preliminary design process’s efficiency and reduce design and development costs. This research paper aims to perform multidisciplinary design and optimization for an expendable microsatellite launch vehicle (MSLV) comprising three solid-propellant stages, capable of delivering micro-payloads in the low earth orbit. The methodology’s primary purpose is to increase the conceptual and preliminary design process’s efficiency by reducing both the design and development costs.

Multidiscipline feasible architecture is applied for the multidisciplinary design and optimization of an expendable MSLV at the conceptual level to accommodate interdisciplinary interactions during the optimization process. The multidisciplinary design and optimization framework developed and implemented in this research effort encompasses coupled analysis disciplines of vehicle geometry, mass calculations, aerodynamics, propulsion and trajectory. Nineteen design variables were selected to optimize expendable MSLV to launch a 100 kg satellite at an altitude of 600 km in the low earth orbit. Modern heuristic optimization methods such as genetic algorithm (GA), particle swarm optimization (PSO) and SA are applied and compared to obtain the optimal configurations. The initial population is created by passing the upper and lower bounds of design variables to the optimizer. The optimizer then searches for the best possible combination of design variables to obtain the objective function while satisfying the constraints.

All of the applied heuristic methods were able to optimize the design problem. Optimized design variables from these methods lie within the lower and upper bounds. This research successfully achieves the desired altitude and final injection velocity while satisfying all the constraints. In this research effort, multiple runs of heuristic algorithms reduce the fundamental stochastic error.

The use of multiple heuristics optimization methods such as GA, PSO and SA in the conceptual design phase owing to the exclusivity of their search approach provides a unique opportunity for exploration of the feasible design space and helps in obtaining alternative configurations capable of meeting the mission objectives, which is not possible when using any of the single optimization algorithm.

The optimized configurations can be further used as baseline configurations in the microsatellite launch missions’ conceptual and preliminary design phases.

Satellite launch vehicle design and optimization is a complex multidisciplinary problem, and it is dealt with effectively in the multidisciplinary design and optimization domain. It integrates several interlinked disciplines and gives the optimum result that satisfies these disciplines’ requirements. This research effort provides the multidisciplinary design and optimization-based simulation framework to predict and evaluate various expendable satellite launch vehicle configurations’ performance. This framework significantly increases the conceptual and preliminary design process’s efficiency by reducing design and development costs.

The geomagnetic field vector is a function of the satellite’s position. The position and speed of the satellite can be determined by comparing the geomagnetic field vector measured by on board three-axis magnetometer with the standard value of the international geomagnetic field. The geomagnetic model has the disadvantages of uncertainty, low precision and long-term variability. Therefore, accuracy of autonomous navigation using the magnetometer is low. The purpose of this paper is to use the geomagnetic and sunlight information fusion algorithm to improve the orbit accuracy.

In this paper, an autonomous navigation method for low earth orbit satellite is studied by fusing geomagnetic and solar energy information. The algorithm selects the cosine value of the angle between the solar light vector and the geomagnetic vector, and the geomagnetic field intensity as observation. The Adaptive Unscented Kalman Filter (AUKF) filter is used to estimate the speed and position of the satellite, and the simulation research is carried out. This paper also made the same study using the UKF filter for comparison with the AUKF filter.

The algorithm of adding the sun direction vector information improves the positioning accuracy compared with the simple geomagnetic navigation, and the convergence and stability of the filter are better. The navigation error does not accumulate with time and has engineering application value. It also can be seen that AUKF filtering accuracy is better than UKF filtering accuracy.

Geomagnetic navigation is greatly affected by the accuracy of magnetometer. This paper does not consider the spacecraft’s environmental interference with magnetic sensors.

Magnetometers and solar sensors are common sensors for micro-satellites. Near-Earth satellite orbit has abundant geomagnetic field resources. Therefore, the algorithm will have higher engineering significance in the practical application of low orbit micro-satellites orbit determination.

This paper introduces a satellite autonomous navigation algorithm. The AUKF geomagnetic filter algorithm using sunlight information can obviously improve the navigation accuracy and meet the basic requirements of low orbit small satellite orbit determination.

This paper aims to investigate the decentralised strategy to coordinate the reconfiguration of multiple spacecraft.

The system of interest consists of multiple spacecraft with independent subsystem dynamics and local constraints, but is linked through their coupling constraints. The proposed method decomposes the centralised problem into smaller subproblems. It minimises the fuel consumption of multiple spacecraft performing a reconfiguration manoeuvre through an iterative computation. In particular, each agent optimises its individual cost function using the most recently available local solution for the other agents.

The simulation scenarios include spacecraft formation reconfiguration and close manoeuvres around obstacles were conducted. The simulation results showed the fast convergence of the proposed algorithm, while local and inter-vehicle constraints were maintained.

The main advantage of this approach is that it adopts a linear form of the objective function. This allows the local optimisation problem to be formulated as a mixed-integer, linear programming problem, most of which can be quickly solved with resort to commercial software.

Fractionated satellite clusters need coming together and avoiding crashing with limited random initial relative motion conditions. It is not necessary to keep the invariable configuration. The purpose of this paper is to put forward a control law which simulates organism swarm motion.

The motion of satellites follows three rules: coming together, velocity homology and avoiding crash. According to the rules, three control forces should be applied to satellite individuals. The final control force is the sum of three control forces. Electromagnetic dipole strengths calculation is formulated as nonlinear optimization problem. Considering control strengths have to be got in real time, iterative steps of optimization algorithm are fixed.

A control law which simulates organism swarm motion is put forward. The simulation shows the organism swarm motion simulation control law can keep fractionated satellite cluster coming together and avoiding crash. When iterative steps of optimization algorithm is fixed, the error of solve nonlinear equations is acceptable.

The control law is robust and easy to realize. When electromagnetic satellite cluster need not keep fixed configuration, it is a choice of control law of relative motion.

The purpose of this study is to, first, provide an overview of the previously conducted works related to thermal analysis of space equipment, including battery packages, especially lithium (Li)-ion ones. Second, the need for a reduced thermal mathematical model (RTMM) and a procedure devising it is defined. Finally, an experimental steady-state temperature distribution test is conducted to finalize the RTMM study.

This study was carried out as part of a development project for thermal analysis of Li-ion battery packages used in a space equipment. The study presents certain stages of the design of the battery pack in parallel with battery technology development. Following a literature review, a numerical thermal analysis is conducted; then interface thermal conductance values are found out by means of the first law of thermodynamics; and the study is completed with the help of an experimental test.

The study provides key aspects for a successful battery-package thermal design for a space equipment. Additionally, the study summarizes the experimental results used in the RTMM process and the computed thermal conductance values between node couples.

Thermal analysis is important and vital in space equipment considering their harsh working conditions and environments. Hence, the study provides a RTMM for the thermal analysis of Li-ion battery packages, instead of a full finite element model, to save computational time and CPU usage. The findings are supported by experimental results. Hence, presented details can be used as guidelines for enterprises having a goal of battery package technology achievement, including design and manufacturing.

After providing a literature review of studies conducted on satellite subsystems including Li-ion batteries, this study presents a clear, complete and verified process of a RTMM for a Li-ion battery package in aero/space structures design. It presents details of building up a model and calculation methodology through an iterative procedure in which an optimization algorithm known as particle swarm optimization (PSO) was benefitted. In the RTMM, additionally, experimental temperature distributions obtained through thermal vacuum test were presented. It has been shown that the model can be used reliably in designing space equipments.

The purpose of this paper is to develop a theoretical design for the attitude control of electromagnetic formation flying (EMFF) satellites, present a nonlinear controller for the relative translational control of EMFF satellites and propose a novel method for the allocation of electromagnetic dipoles.

The feedback attitude control law, magnetic unloading algorithm and large angle manoeuvre algorithm are presented. Then, a terminal sliding mode controller for the relative translation control is put forward and the convergence is proved. Finally, the control allocation problem of electromagnetic dipoles is formulated as an optimization issue, and a hybrid particle swarm optimization (PSO) – sequential quadratic programming (SQP) algorithm to optimize the free dipoles. Three numerical simulations are carried out and results are compared.

The proposed attitude controller is effective for the sun-tracking process of EMFF satellites, and the magnetic unloading algorithm is valid. The formation-keeping scenario simulation demonstrates the effectiveness of the terminal sliding model controller and electromagnetic dipole calculation method.

The proposed method can be applied to solve the attitude and relative translation control problem of EMFF satellites in low earth orbits.

The paper analyses the attitude control problem of EMFF satellites systematically and proposes an innovative way for relative translational control and electromagnetic dipole allocation.