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Most Aeronautical and Astronautical Systems (AAS) are inherently complex, multidisciplinary, nonlinear, and computationally intensive for design and analysis. Utilizing the Reliability-Based Multidisciplinary Design Optimization framework can address the multidisciplinary nature of these systems while accounting for inherent uncertainties. In this paper, an efficient methodology for Reliability-Based Multidisciplinary Design optimization of an aerial vehicle is developed. The computational burden of reliability assessment could make its integration within a Multidisciplinary Design Optimization cycle a formidable task. In this respect, a multilevel Multidisciplinary Design Optimization architecture is proposed in which the computational cost is reduced by considering the reliability analysis, as needed only for critical subsystems. To this end, a single-level Reliability-Based Multidisciplinary Design Optimization is derived using the Performance Measure Analysis and the Karush-Kuhn-Tucker condition. The work demonstrates the integration of this formulation into the proposed multilevel Reliability-Based Multidisciplinary Design Optimization architecture. The proposed design architecture is implemented for an aeroelastic Unpowered Guided Aerial Vehicle whose outcomes are compared with previous results obtained via a mono-level Uncertainty-Based Multidisciplinary Design Optimization architecture. [ABSTRACT FROM AUTHOR]

A review of advanced fault detection and diagnosis (FDD) techniques in attitude control systems (ACSs) of spacecraft is presented. In the first part of the paper, several types of ACS failure scenarios with their practical solutions are presented. Next, the existing approaches to FDD are considered and classified based on different criteria, including applications and design techniques. The literature of this part showed that to enhance ACS operational safety, predictability of failure of an ACS and/or of its components as well as reducing the possibility of failure occurrence is imperative. In addition, fast FDD of various kinds of failures is necessary to guarantee the required reliability of an ACS. The second part of this study highlights challenges involved with different FDD approaches, emphasizing their practical applicability. Current research gaps in FDD techniques such as insensitive residual signal, process monitoring methods, accurate plant model design, easy-to-use software development, FDD tuning process, dealing with noisy sensor measurements, time taken for fault management, the sensitivity of FDD system to faults, and FDD robustness are further elaborated on. Subsequently, the state-of-the-art FDD and its future needs are reflected on. The results of this study could direct spacecraft manufacturers and ACS providers to focus on future needs and improve ground testing for enhanced operational reliability and redundancy. [ABSTRACT FROM AUTHOR]

Microburst (MB) wind shear is one of the most important meteorological dangers threatening the aircraft (AC) safety and the life of passengers. Though there are some ground-based 3D Lidar systems to detect low-level MB wind shears to alert the pilots, there have been fewer scientific attempts to identify model-based MB parameters via AC onboard air and position data. The latter refers to the development and identification of an acceptable MB model upon which an automatic flight control (AFC) system can be designed to control the AC through wind shear microburst. In essence, accurate knowledge of MB model is an essential prerequisite for design and analysis of AFC systems that can safely fly the AC against microbursts, especially in crucial phases of flight such as takeoff and landing. The present study focuses on online estimation of MB parameters whose results pave the way for effective MB autopilot designs for safe flights through MB. The proposed task is accomplished via a model-based approach using the AC six degrees of freedom (6 DoF) equations of motion (EOM) integrated with the latest verified model of the MB utilizing the extended Kalman filter (EKF). In addition to a sensitivity analysis to determine the key MB model parameters, the performance of the estimation process is enhanced via a hybridization of the genetic algorithm (GA) with the EKF. The results are promising and indicate that the proposed scheme can identify the MB model parameters with sufficient accuracy needed for online applications with AFC design. [ABSTRACT FROM AUTHOR]

A novel integrated aeroelastic model of flapping wings (FWs) undergoing a prescribed rigid body motion is presented. In this respect, the FW nonlinear structural dynamics is enhanced via a newly proposed modification of implicit condensation and expansion (MICE) method that better considers the structural nonlinear effects. In addition, the unsteady aerodynamic model is also an extension of the widely utilized modified strip theory (MST) in which the flexibility effects are accounted for (MST-Flex). The integrated utility of the proposed generalized MICE and MST-Flex is demonstrated to be more realistic for elastic FW flight simulation applications. The prescribed rigid body motion is produced via a servo motor whose dynamics is also considered for the analysis. A special case study is also performed whose combined aeroelastic solution is determined and validated under a sinusoidal flapping motion. To this end, an experimental setup is designed and tested in order to validate the proposed integrated approach for aeroelastic modeling of FWs. There is very good agreement between the numerical and experimental results for elastic FW aerodynamics. It should be noted that the proposed integrated aeroelastic approach is readily adaptable to all kinds of elastic wings with arbitrary geometry and various combination of structural elements. [ABSTRACT FROM AUTHOR]

Application of composite lattice structures in aerospace application can bring about considerable weight savings, thus allowing for increased payload weight. This study is devoted to reliability analysis of composite anisogrid lattice interstage structure (CALIS) used in typical launch vehicle (LV). CALIS is usually formed in to thin-walled cylindrical or conical shell via helical and circumferential ribs that can act as a lightweight load bearing support structure interfacing any two stages of the LV. Thus, the current study is of practical importance as the interstage structure is acted upon by rather high axial and bending forces emanating from LV external aerodynamics, thrust and inertial forces. As there are always uncertainties associated with the material properties, structural geometry, loading conditions as well as the manufacturing processes, CALIS is faced with stochastic load and strength characteristics. In this sense, CALIS structural reliability is of importance and is thus investigated with respect to material strength, local and global buckling via different reliability techniques. The analytical reliability results are verified against a Monte Carlo simulation and analysis. In addition, a comprehensive sensitivity analysis is performed for some of key CALIS design variables that dominantly affect its structural reliability. [ABSTRACT FROM AUTHOR]

Airships are inherently sensitive to random atmospheric disturbances that could potentially make their data gathering and observation missions a formidable task. In this context robust closed loop feedback controllers are important. The present study is therefore focused on optimal feedback controller design of an indigenous domestically designed airship (DA) for added robustness against atmospheric disturbances. While the general airship six degrees of freedom (6DoF) governing equations of motion are mathematically nonlinear, one often needs to resort to local linearization methods to benefit from proven linear closed loop controller (CLC) design approaches. In this sense an optimal linear quadratic regulator/tracker (LQR/LQT) seems to be a viable alternative for DA control purposes whose implementation relies on local linearization of the 6DoF nonlinear equations around the instantaneous airship trajectory. In order to demonstrate the capabilities of the proposed CLC design against external turbulences, a random wind profile over the DA hull is assumed and the airship behavior is analyzed in regulation as well as the tracking mode. The results show that the proposed CLC design complies with the all mission requirements and adequately reduces the impact of environmental random wind fluctuations. Given the small computational time required for control gain and command determination within the LQR/LQT algorithm against the DA mission flight time, the proposed CLC can be utilized online as a feedback control strategy while the airship is performing any physical atmospheric experiment. [ABSTRACT FROM AUTHOR]

A novel trajectory design methodology is proposed in the current work to minimize the state uncertainty in the crucial mission of spacecraft rendezvous. The trajectory is shaped under constraints utilizing a multiple-impulse approach. State uncertainty is characterized in terms of covariance, and the impulse time as the only effective parameter in uncertainty propagation is selected to minimize the trace of the covariance matrix. Furthermore, the impulse location is also adopted as the other design parameter to satisfy various translational constraints of the space mission. Efficiency and viability of the proposed idea have been investigated through some scenarios that include constraints on final time, control effort, and maximum thruster limit addition to considering safe corridors. The obtained results show that proper selection of the impulse time and impulse position fulfills a successful feasible rendezvous mission with minimum uncertainty. [ABSTRACT FROM AUTHOR]

Microburst is considered an extreme powerful hazard for aircrafts, especially during takeoff, approach and landing phases of flight. Current airborne piloting practices involve taking alternative routes, if early detection of microburst wind shear (MBW) for its effective avoidance is possible. In this respect, design and analysis of precision automatic flight path control systems for microburst penetration are of outmost importance whose success can significantly reduce crash risks and thus enhance the flight safety. The current study is focused on the design and analysis of a three-dimensional model predictive controller for a wide body transport type aircraft encountering MBW in approach to landing phase of flight. This task is performed utilizing the full nonlinear six degrees of freedom aircraft equations of motion and the most complete 3D model of the MBW and its gradients. The results are promising for online applications as the proposed model predictive controller-based controller has effectively guided and kept the aircraft on the approach glide path with negligible deviations against aircraft initial lateral displacements, sharp edge gust disturbance as well as the MBW. [ABSTRACT FROM AUTHOR]

Summary: 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 continuous ant colony system is used for simultaneous integrated tuning of the LQR and observer parameters through all processes. Optimization of the controller and the observer is performed with the objective of system structural reliability. An optimized version of classical LQR controller is also developed for making comparisons between the two control methods. Finally, a comparison is made between the mean power consumption of the 2 controllers. It is realized that the reliability‐based controller decreases operating costs without compromising system safety. [ABSTRACT FROM AUTHOR]

The effect of inertial forces on the Structural Dynamics (SD) behaviour of Elastic Flapping Wings (EFWs) is investigated. In this regard, an analytical modal-based SD solution of EFW undergoing a prescribed rigid body motion is initially derived. The formulated initial-value problem is solved analytically to study the EFW structural responses, and sensitivity with respect to EFWs’ key parameters. As a case study, a rectangular wing undergoing a prescribed sinusoidal motion is simulated. The analytical solution is derived for the first time and helps towards a conceptual understanding of the overall EFW's SD behaviour and its analysis required in their designs. Specifically, the EFW transient and steady response in on-off servo condition is also attended. [ABSTRACT FROM AUTHOR]

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, an experimental evaluation is conducted using a simple cantilevered beam. Subsequently, system identification is weaved in with a probability density evolution equation for calculating the reliability of a wing structural component. Numerical simulations demonstrate that structural reliability of a typical WSC can be effectively evaluated. The proposed scheme paves the way for new SHM research topics such as online life prediction and reliability based failure prevention. [ABSTRACT FROM AUTHOR]

Strain gauge balances (SGBs) are efficient and accurate means of static force measurement. However, due to their inherent elastic characteristics, they lack desired performance when used in dynamic loading conditions. In this paper, a novel technique is presented that remedies their inherent weakness in measuring dynamic periodic forces. The proposed method produces a correction factor to compensate the measured loading in dynamic situations. For this purpose, first an analytical investigation is performed to determine the structural dynamic behavior of a typical SGB system via the modal approach. This analytical investigation leads to identification of the structural interference effects that occurs on the SGB output in dynamic scenarios and renders the desired validated dynamic correction factor for periodic loading correction. The proposed methodology allows for extraction of the true SGB signal and/or loading out of the complex erroneous SGB output. As a case study, a periodic loading is measured via two different balances and the results are compared with and without taking into account the correction factor. The result of this investigation demonstrates that the introduced correction factor plays a crucial role in dynamic force estimation, especially when the loading frequency approaches the natural frequencies of the balancing system structure. [ABSTRACT FROM PUBLISHER]

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 implemented for finding an optimal solution through the MDO. The Simplex-NSGA II method is a heuristic optimization algorithm that applies to multi-objective functions and the results are then compared with the most famous algorithms, like Nondominated Sorting Genetic Algorithm II (NSGA II) and Multi-Objective Particle Swarm Optimization (MOPSO). Simulation results demonstrate the superior performance of the Simplex-NSGA II over NSGA II and MOPSO. Also, it is used in this study in order to achieve an optimal solution using MDO in both 3DOF and 6DOF simulations of GFV to reach desirable performance index. [ABSTRACT FROM AUTHOR]

Optimal trajectory and muscle forces of a human-like musculoskeletal arm are predicted for planar point-to-point movements using optimal control theory. The central nervous system (CNS) is modeled as an optimal controller that performs a reaching motion to final states via minimization of an objective function. For the CNS strategy, a cubic function of muscles stresses is considered as an appropriate objective function that minimizes muscles fatigue. A two-DOF nonlinear musculoskeletal planar arm model with four states and six muscle actuators is used for the evaluation of the proposed optimal strategy. The nonlinear variational formulation of the corresponding optimal control problem is developed and solved using the method of variation of extremals. The initial and (desired) final states (position and velocity) are used as input kinematic information, while the problem constraints include the motion range of each joint, maximum allowable muscle tension, and stability requirements. The resulting optimal trajectories are compared with experimental data as well as those corresponding to recent researches on model predictions of human arm movements. It is demonstrated that the proposed optimal control strategy using minimum fatigue criterion is more realistic in prediction of motion trajectories in comparison with previous work that has utilized minimum joints' torque criterion. Accordingly, minimization of muscles fatigue is an effective biomechanical criterion for the CNS in prediction of point-to-point human arm motions. Copyright © 2016 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

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 variations of the total loads experienced by the launch vehicle, its time-dependent structural reliability is formulated via a stress limit state function. The first-order reliability method is used to estimate the launch-vehicle cumulative failure probability as a function of flight time. The results are verified using the method of direct Monte Carlo simulation. Finally, a sensitivity of launch-vehicle structural reliability is performed against some statistical variations related to solid rocket motor and launch-vehicle design parameters that dominantly affect time-varying structural reliability. [ABSTRACT FROM AUTHOR]

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 the launch vehicle cost with design variables being the component reliability, system redundancy level, and the type of components. To examine the validity of the proposed algorithm, a benchmark problem in reliability-redundancy optimization is also investigated through the proposed scheme. Benchmark simulation results indicate that neither genetic algorithm nor the particle swarm optimization alone can produce sufficiently accurate optimal results, but their hybrid combination is more efficient and achieves the desired level of accuracy. Thus the proposed hybrid genetic algorithm-particle swarm optimization is applied to the problem of launch vehicle multi-objective reliability optimization that has resulted in a convex Pareto front, out of which many design points could be selected for implementation. Finally, a Monte Carlo simulation is performed against the subsystem reliability uncertainty in order to analyze the effect of uncertainty on the total launch vehicle reliability and cost. [ABSTRACT FROM AUTHOR]

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 threats. Effectiveness of the proposed algorithm is demonstrated via several simulated scenarios and verified against past research. The results are promising and indicative of a good potential of the proposed algorithm in producing optimal real-time optimal feasible trajectories with multi-variable objectives. [ABSTRACT FROM AUTHOR]