Sharif Digital Repository

Concurrent orbit and attitude determination (COAD) plays a key role in reducing the cost of navigation and control subsystem for small satellites. This article is devoted to the problem of the COAD of satellites. A measurement package consisting of three axis magnetometer (TAM) and a sun sensor is shown to be sufficient to estimate the attitude and orbit information. To this end, an autonomous gyro-less COAD algorithm is proposed and implemented through the centralized data fusion of the TAM and the sun sensor. The set of nonlinear-coupled roto-translation dynamics of the satellite is used with a modified unscented Kalman filter (MUKF) to estimate the full satellite states. The MUKF is... 

This paper deals with the problems of attitude determination, parameter identification and reference sensor calibration simultaneously. An LEO satellite's attitude, inertia tensor as well as calibration parameters of Three-Axis-Magnetometer (TAM) including scale factors, misalignments and biases along three body axes are estimated during a maneuver designed to satisfy the condition of persistency of excitation. The advanced nonlinear estimation algorithm of Unscented Kalman Filter (UKF) is a good choice for nonlinear estimation problem of attitude determination, but its computational cost is considerably larger than the widespread low accurate Extended Kalman Filter. Reduced Sigma Point... 

Motion planning is a key factor in enhancing the autonomy level of unmanned flying vehicles. A new dynamic hybrid algorithm is developed to solve the motion planning problem in real-time using a heuristic optimization approach. The proposed algorithm effectively combines desired features such as rapid convergence to an optimal path with reduced computational effort. In addition to the terrain obstacles, the proposed algorithm is able to avoid random threats that may arise sporadically in the terrain. Using the maneuver automaton concept, nonlinear dynamic model and performance constraints are also considered in the process of motion planning to further ensure feasible trajectories.... 

Motion planning and trajectory control are two basic challenges of unmanned vehicles. In motion planning problem, feasible trajectories are developed while nonlinear dynamic model and performance constraints of the vehicle under utility are considered. In this study, motion planning is performed via an enhanced particle swarm optimization algorithm. The resulting offline generated trajectories are tracked using a nonlinear trajectory control system methodology. The Lyapunov-based constrained backstepping approach and command filters are utilized in designing the trajectory control system. Command filters smoothen the input signals and provide their derivatives. Evaluation of the proposed... 

This paper deals with attitude determination, parameter identification and reference sensor calibration simultaneously. A LEO satellite's attitude, inertia tensor as well as calibration of Three-Axis-Magnetometer (TAM) are estimated during a maneuver designed to satisfy persistency of excitation condition. For this purpose, kinematic and kinetic state equations of spacecraft motion are augmented for the determination of inertia tensor and TAM calibration parameters including scale factors, misalignments and biases along three body axes. Attitude determination is a nonlinear estimation problem. Unscented Kalman Filter (UKF) as an advanced nonlinear estimation algorithm with good performance... 

Orbit determination (OD) problem utilizing onboard sensors is a key requirement for many current and future space missions. Though there exists ample research and work on this subject, a novel algorithm is presented in this paper for the nonlinear problem of OD. In this regard, initially a new cubature-quadrature particle filter (CQPF) that uses the square-root cubature-quadrature Kalman filter (SR-CQKF) to generate the importance proposal distribution is developed. The developed CQPF scheme avoids the limitation of the standard particle filter (PF) concerning new measurements. Subsequently, CQPF is enhanced to take advantage of the relative entropy (Kullback-Leibler Distance) criterion to... 

New heuristic filters are proposed for state estimation of nonlinear dynamic systems based on particle swarm optimization (PSO) and differential evolution (DE). The methodology converts state estimation problem into dynamic optimization to find the best estimate recursively. In the proposed strategy the particle number is adaptively set based on the weighted variance of the particles. To have a filter with minimal parameter settings, PSO with exponential distribution (PSO-E) is selected in conjunction with jDE to self-adapt the other control parameters. The performance of the proposed adaptive evolutionary algorithms i.e. adaptive PSO-E, adaptive DE and adaptive jDE is studied through a... 

This paper focuses on multi-objective reliability optimization of a two-stage launch vehicle using a hybridized Genetic Algorithm-Particle Swarm Optimization with provisions of relative weighting between the objectives. In this respect, the launch vehicle key subsystems as well as their functions are initially introduced. Subsequently, the system reliability block diagram is constructed using the launch vehicle working order of the subsystems augmented with the requirements for a robust fault/failure tolerant design and performance. Next, based on the proposed reliability block diagram arrangement a bi-objective optimization is formulated to maximize the system reliability while minimizing... 

Accurate orbit determination (OD) is vital for every space mission. This paper proposes a novel heuristic filter based on adaptive sample-size Gaussian swarm optimization (AGSF). The proposed estimator considers the OD as a stochastic dynamic optimization problem that utilizes a swarm of particles in order to find the best estimation at every time step. One of the key contributions of this paper is the adaptation of the swarm size using a weighted variance approach. The proposed strategy is simulated for a low Earth orbit (LEO) OD problem utilizing geomagnetic field measurements at 700 km altitude. The performance of the proposed AGSF is verified using Monte Carlo simulation whose results... 

A major issue required to enhance the autonomy level of unmanned vehicles is real-time motion planning. In this context, optimal trajectories need to be generated online considering the vehicle's dynamic potentials and constraints. However, autonomous air vehicles often need to plan and execute their missions with varying objectives that may even be dictated in flight. Therefore, the current study introduces and focuses on the new concept of variable-objective motion planning. In this regard, a new dynamic multi-objective heuristic optimization algorithm is developed for path and motion planning of autonomous air vehicles in presence of deterministic terrain obstacles as well as random... 

This paper investigates the problem of optimal transfer trajectory design towards the L2 centered Halo orbit of the Sun-Earth three body system, where the initial launch is to start from a low Earth parking orbit (LEO). The proposed optimal transfer trajectory consists of an active part with low-thrust propulsion and a passive coasting part with no thrust or fuel consumption. In this respect a pseudo-stable manifold (SM) is initially determined through backward time integration of the bicircular four body (BCFB) equations of motion, whose initial states are obtained via stable manifolds of the restricted three body problem (R3BP). The optimal transfer trajectories are extracted via a hybrid... 

An optimal fuel guidance strategy with acceleration limit is derived for interception of maneuvering targets. The guidance/control system is assumed as a linear time-varying arbitraryorder and is identical in each channel. An approximate model for drag acceleration is also considered in the solution. The optimal fuel strategy has some detrimental effects in most practical situations, if it is used entirely to the end. This strategy can be used at the beginning of the guidance phase for large initial heading errors in order to quickly reduce it with minimum effort. An explicit guidance law is then developed for minimum and nonminimum phase autopilots in order to modify the undesirable effects... 

In this paper, optimal trajectories of a spacecraft traveling from Earth to Moon using impulsive maneuvers (ΔV maneuvers) are investigated. The total flight time and the summation of impulsive maneuvers ΔV are the objective functions to be minimized. The main celestial bodies influencing the motion of the spacecraft in this journey are Sun, Earth and Moon. Therefore, a three-dimensional restricted four-body problem (R4BP) model is utilized to represent the motion of the spacecraft in the gravitational field of these celestial bodies. The total ΔV of the maneuvers is minimized by eliminating the ΔV required for capturing the spacecraft by Moon. In this regard, only a mid-course impulsive... 

In this study the effect of the Sun on the Lagrange points of the Earth-Moon system is investigated. A restricted four-body problem (R4BP) is introduced to take into account the effect of the Sun, Earth and Moon on the motion of an infinitesimal particle. The motion of the Earth-Moon-barycenter (EMB) around the Sun is considered to be elliptic in the ecliptic plane. Similarly, the motion of the Moon around the Earth is presumed to be elliptic, but out of the ecliptic plane. In this way, a spatial R4BP with non-coplanar motion of primaries is derived, which is named as BiElliptic problem (BEP). Transforming the equations of motion to a coordinate system originated at the EMB that rotates with... 

Time-varying structural reliability of a multistage solid-propellant launch vehicle subjected to deterministic and stochastic loads is investigated. The study is of practical importance because the launch vehicle's structure is influenced by a combination of external aerodynamics as well as inertial and internal ballistic loads emanating from the solid rocket motors. In addition, as launch-vehicle flight conditions change during flight, the vehicle will be subjected to time-varying loads. In this sense, the environmental, aerodynamic, and internal pressure fluctuations can be interpreted as stochastic forces affecting the launch-vehicle structural reliability. To account for temporal... 

Reliability evaluation is a key factor in serviceability and safety analysis of air vehicles. Structural health monitoring methods have grown to a degree of maturity in many industries. However, there is a challenging interest to tie in SHM with reliability assessment. In this respect, consideration of stochastic structural dynamics with SHM data and random loadings opens a new chapter in failure prevention. The current study focuses on the stochastic behavior of structures as a way to relate SHM data with reliability. In this respect, uncertain factors such as atmospheric turbulence, structural parameters, and sensor outputs are considered in the process of reliability assessment. Firstly,... 

The utility of probability density evolution method for reliability-based active vibration control of a cantilevered flexible beam is experimentally investigated. In this respect, an optimal linear quadratic regulator (LQR) is utilized together with an observer to design an online full-state feedback controller. In order to design a well-performing controller and to simulate the controller performance, a system model is obtained via identification techniques. Reliability tests are consequently performed to verify the effectiveness of the presented reliability assessment method as a foundation for reliability-based control. Subsequently, a hybrid metaheuristic optimization scheme of... 

This paper presents design of a typical Guided Flying Vehicle (GFV) using the multidisciplinary design optimization (MDO). The main objectives of this multi-disciplinary design are maximizing the payload’s weight as well as minimizing the miss distance. The main disciplines considered for this design include aerodynamics, dynamic, guidance, control, structure, weight and balance. This design of GFV is applied to three and six Degree of Freedom (DOF) to show comparison of simulation results. The hybrid scheme of optimization algorithm is based on Nelder-Mead Simplex optimization algorithm and Nondominated Sorting Genetic Algorithm II (NSGA II), called Simplex-NSGA II. This scheme is... 

The problem of time optimal magnetic attitude control is treated and an open loop solution is first obtained using a variational approach. In order to close the control loop, a neural network with time varying weights is proposed as a feedback optimal controller applicable to the time varying nonlinear system. The good robustness and low real-time computational burden of the proposed neuro-controller makes the controller more useful compared to the other control methods. © 2008 IEEE  

Purpose - The purpose of this paper is to develop a novel solution for the predicted error and introduces a systematic method to develop optimal and explicit guidance strategies for different missions. Design/methodology/approach - The predicted error is derived from its basic definition through analytic]al dynamics. The relations are developed for two classes of systems. First, for systems in which the acceleration commands are truncated at a specified time. Second, for systems in which the corrective maneuvers are cut off at a specified time. The predicted error differential equation is obtained in a way that allows for derivation of several optimal and explicit guidance schemes. Findings...