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The purpose of this paper is to present a mathematical model of one very flexible transport category airplane whose structural dynamics was modeled with the strain-based formulation. This model can be used for the analysis of couplings between the flight dynamics and structural dynamics.

The model was developed with the use of Hamiltonian mechanics and strain-based formulation. Nonlinear flight dynamics, nonlinear structural dynamics and inertial couplings are considered.

The mathematical model allows the analysis of effects of high structural deformations on airplane flight dynamics.

The mathematical model has more than 60 degrees of freedom. The computational burden is too high, if compared to the traditional rigid body flight dynamics simulations.

The mathematical model presented in this work allows a detailed analysis of the couplings between flight dynamics and structural dynamics in very flexible airplanes. The better comprehension of these couplings will contribute to the development of flexible airplanes.

This work presents the application of nonlinear flight dynamics-nonlinear structural dynamics-strain-based formulation (NFNS_s) methodology to model the flight dynamics of one very flexible transport category airplane. This paper addresses also the way as the analysis of results obtained in nonlinear simulations can be made. Comparisons of the NFNS_s and nonlinear flight dynamics-linear structural dynamics methodologies are presented in this work.

This paper aims to clarify the flight dynamics characteristics and improve the flight performance for large-scale morphing aircrafts. With specific focus on the effects of morphing on mass distribution, aerodynamics and flight stability, the study aims to develop the dynamic model, outline the morphing strategies design and evaluate the flight stability in transient stage of morphing.

The mode of relaxing the rigidity condition was opted, which introduced the functions of position of center of mass and moments of inertia with respect to the morphing parameters, and yielded a parameter-dependent flight dynamics model. The morphing strategies were designed by optimizing the morphing parameters with the corresponding performance metric of each mission segment, where the aerodynamics was estimated concurrently by DATCOM. Based on the decoupled and linearized longitudinal parameter-dependent model, the flight stability in transient stage of morphing was evaluated based on Hurwitz rules, with the stability condition proposed.

The research suggests that the longitudinal flight stability in transient stage of morphing can be evaluated by the relationship of aerodynamic pitching moment derivatives and the effects of morphing on the mass distribution, which results in a constraint on the morphing rate.

The aerodynamics is computed under quasi-steady aerodynamic assumption in low morphing rate and only the longitudinal flight stability is analyzed. Therefore, researchers are encouraged to evaluate the lateral stability and aerodynamics in high morphing rate.

The paper includes implications for the improvement of the flight performance of a multi-mission morphing aircraft and the design of the flight control system.

Methods of dynamic modeling and morphing strategies design are proposed for large-scale morphing aircrafts, and the condition of flight stability in transient stage of morphing is obtained. The results provide reference to research works in the field of dynamics and control of large-scale morphing aircrafts.

Flapping-wing vehicles show various advantages as compared to fixed wing vehicles, making flapping-wing vehicles' study necessary in the current scenario. The present study aims to provide guidelines for fixing geometric parameters for an initial engineering design by a simple aerodynamic and flight dynamic parametric study.

A mathematical analysis was performed to understand the aerodynamics and flight dynamics of the micro-air vehicle (MAV). Only the forces due to the flapping wing were considered. The flapping motion was considered to be a combination of the pitching and plunging motion. The geometric parameters of the flapping wing were varied and the aerodynamic forces and power were observed. Attempts were then made to understand the flight stability envelope of the MAV in a forward horizontal motion in the vertical plane with similar parametric studies as those conducted in the case of aerodynamics.

From the aerodynamic study, insights were obtained regarding the interaction of design parameters with the aerodynamics and feasible ranges of values for the parameters were identified. The flapping wing was found to have neutral static stability. The flight dynamic analysis revealed the presence of an unstable oscillatory mode, a stable fast subsidence mode and a neutral mode, in the forward flight of the MAV. The presence of unstable modes highlighted the need for active control to restore the MAV to equilibrium from its unstable state.

The study does not take into account the effects of control surfaces and tail on the aerodynamics and flight dynamics of the MAV. There is also a need to validate the results obtained in the study through experimental means which shall be taken up in the future.

The parametric study helps us to understand the extent of the impact of the design parameters on the aerodynamics and stability of the MAV. The analysis of both aerodynamics and dynamic stability provides a holistic picture for the initial design. The study incorporates complex mathematical equations and simplifies such to understand the aerodynamics and flight stability of the MAV from an engineering perspective.

The study adds to already existing knowledge on the design procedures of a flapping wing.

The purpose of this paper is to present an approach to employ evolvable hardware concepts, to effectively construct flapping‐wing mechanism controllers for micro robots, with the evolved dynamically complex controllers embedded in a, physically realizable, micro‐scale reconfigurable substrate.

In this paper, a continuous time recurrent neural network (CTRNN)‐evolvable hardware (a neuromorphic variant of evolvable hardware) framework and methodologies are employed in the process of designing the evolution experiments. CTRNN is selected as the neuromorphic reconfigurable substrate with most efficient Minipop Evolutionary Algorithm, configured to drive the evolution process. The uniqueness of the reconfigurable CTRNN substrate preferred for this study is perceived from its universal dynamics approximation capabilities and prospective to realize the same in small area and low power chips, the properties which are very much a basic requirement for flapping‐wing based micro robot control. A simulated micro mechanical flapping insect model is employed to conduct the feasibility study of evolving neuromorphic controllers using the above‐mentioned methodology.

It has been demonstrated that the presented neuromorphic evolvable hardware approach can be effectively used to evolve controllers, to produce various flight dynamics like cruising, steering, and altitude gain in a simulated micro mechanical insect. Moreover, an appropriate feasibility is presented, to realize the evolved controllers in small area and lower power chips, with available fabrication techniques and as well as utilizing the complex dynamics nature of CTRNNs to encompass various controls ability in a architecturally static hardware circuit, which are more pertinent to meet the constraints of micro robot construction and control.

The proposed neuromorphic evolvable hardware approach along with its modules intact (CTRNNs and Minipop) can provide a general mechanism to construct/evolve dynamically complex and optimal controllers for flapping‐wing mechanism based micro robots for various environments with least human intervention. Further, the evolved neuromorphic controllers in simulation study can be successfully transferred to its hardware counterpart without sacrificing its anticipated functionality and realized within a predictable area and power ranges.

The purpose of this paper is to build a neural model of an aircraft from flight data and online estimation of the aerodynamic derivatives from established neural model.

A neural model capable of predicting generalized force and moment coefficients of an aircraft using measured motion and control variable is used to extract aerodynamic derivatives. The use of neural partial differentiation (NPD) method to the multi-input-multi-output (MIMO) aircraft system for the online estimation of aerodynamic parameters from flight data is extended.

The estimation of aerodynamic derivatives of rigid and flexible aircrafts is treated separately. In the case of rigid aircraft, longitudinal and lateral-directional derivatives are estimated from flight data. Whereas simulated data are used for a flexible aircraft in the absence of its flight data. The unknown frequencies of structural modes of flexible aircraft are also identified as part of estimation problem in addition to the stability and control derivatives. The estimated results are compared with the parameter estimates obtained from output error method. The validity of estimates has been checked by the model validation method, wherein the estimated model response is matched with the flight data that are not used for estimating the derivatives.

Compared to the Delta and Zero methods of neural networks for parameter estimation, the NPD method has an additional advantage of providing the direct theoretical insight into the statistical information (standard deviation and relative standard deviation) of estimates from noisy data. The NPD method does not require the initial value of estimates, but it requires a priori information about the model structure of aircraft dynamics to extract the flight stability and control parameters. In the case of aircraft with a high degree of flexibility, aircraft dynamics may contain many parameters that are required to be estimated. Thus, NPD seems to be a more appropriate method for the flexible aircraft parameter estimation, as it has potential to estimate most of the parameters without having the issue of convergence.

This paper highlights the application of NPD for MIMO aircraft system; previously it was used only for multi-input and single-output system for extraction of parameters. The neural modeling and application of NPD approach to the MIMO aircraft system facilitate to the design of neural network-based adaptive flight control system. Some interesting results of parameter estimation of flexible aircraft are also presented from established neural model using simulated data as a novelty. This gives more value addition to analyzing the flight data of flexible aircraft as it is a challenging problem in parameter estimation of flexible aircraft.

This paper aims to propose a nonlinear model for aeroelastic aircraft that can predict the flight parameters throughout the investigated flight envelopes.

A system identification method based on the support vector machine (SVM) is developed and applied to the nonlinear dynamics of an aeroelastic aircraft. In the proposed non-parametric gray-box method, force and moment coefficients are estimated based on the state variables, flight conditions and control commands. Then, flight parameters are estimated using aircraft equations of motion. Nonlinear system identification is performed using the SVM network by minimizing errors between the calculated and estimated force and moment coefficients. To that end, a least squares algorithm is used as the training rule to optimize the generalization bound given for the regression.

The results confirm that the SVM is successful at the aircraft system identification. The precision of the SVM model is preserved when the models are excited by input commands different from the training ones. Also, the generalization of the SVM model is acceptable at non-trained flight conditions within the trained flight conditions. Considering the precision and generalization of the model, the results indicate that the SVM is more successful than the well-known methods such as artificial neural networks.

In this paper, both the simulated and real flight data of the F/A-18 aircraft are used to provide aeroelastic models for its lateral-directional dynamics.

This paper proposes a non-parametric system identification method for aeroelastic aircraft based on the SVM method for the first time. Up to the author’s best knowledge, the SVM is not used for the aircraft system identification or the aircraft parameter estimation until now.

The purpose of this paper is to perform an indoor autonomous flight of ornithopter using a novel motion capture system.

The ornithopter platform has no on‐board sensors and processors for state estimation or feedback control. Instead, passive markers on the ornithopter body reflect IR light of the multiple strobing CCD cameras, and the position data of the markers are streamed to the ground station in almost real time. Control inputs such as wingbeat frequency and rudder angle are generated by the proportional feedback controllers which are implemented in the ground station and transmitted to the ornithopter. Due to the complexity and nonlinearity of aerodynamics and flexible multibody dynamics, the flight dynamics of ornithopter are difficult to realize in the closed form of state‐space system equations. A controller for stabilizing the flight state variables of ornithopter is not necessary to be implemented by means of flapping counter‐forces and torques which make ornithopter have inherent flight stability. The gains of controllers for following circular trajectories are obtained by a trial‐and‐error approach rather than a model‐based design.

The autonomous ornithopter successfully circulates the pre‐described radius with the constant altitude and the result shows that control strategies proposed in this study are sufficient to implement the autonomy of ornithopter flight.

The autonomous flight of ornithopter is firstly conducted in a confined indoor environment by using the motion capture system and the control performance is evaluated in terms of position errors.

The purpose of this paper is to present a method for determining the safe flight boundaries of the asymmetrically loaded airplane in the terminal flight phases. The method is applicable to both, the inherent airplane asymmetries and those asymmetries resulting from the airplane use irregularities, asymmetric stores under the wing being one of the examples. The method is aimed to be used in the airplane design and combat airplane service life support.

The analysis method is based on the comparison of demanded and structurally available flight control displacements. Control surface aerodynamic properties, structurally available flight control displacements and dynamic pressure define control surface authority as the capability of control surfaces to generate the forces and moments needed by the airplane to perform required maneuvers. Demanded flight control displacements are those related to the maneuvering requirements and to those needed to compensate lateral wind and any type of the asymmetric airplane load.

The method results are given in the form of the speed and lateral wind component and are a subset of the total set of airplane safe flight boundaries. The key objective is the improvement of flight safety of the asymmetrically loaded airplane.

The method supplements the safe flight boundaries of the symmetrically loaded airplane, the minimal landing speed being the dominant limitation. This boundary positions method analysis in the domain of linear lift coefficient variation, as the function of the angle of attack permits the addition of control surface displacements required to perform the maneuvers and compensate the asymmetrical loads.

The method combines a simple roll dynamics model, stationary equations of the airplane lateral-directional motion and several numeric analysis procedures to obtain the results. This new combination possesses synergy properties and is implemented as the computer program.

The present study aimed to demonstrate different computational models, data and stability results obtained in a wide number of projects of various aircrafts such as unmanned aerial vehicles (UAVs), general aviation and big passenger flying airliners in blended wing body (BWB) configurations. Many details of modeling and computing are shown for unconventional configurations, namely, for a BWB aircraft and for tailless UAVs.

Mathematical models for analysis of static and dynamic stability were built and investigated based on equations of motion in the linearized form using the so-called state variable model for a steady-state disturbed, generally asymmetric, flight.

Flight dynamics models and associated computational procedures appeared to be useful, both in a preliminary design phase and during the final assessment of the configuration at flight tests. It was also found that the difference between thresholds for static and dynamic stability conditions was equal to 9 per cent of mean aerodynamic chord (MAC) in the case of BWB and 3 per cent of MAC in the case of tailless UAVs.

Many useful information about aircraft dynamics can be easily obtained from computational analyses including time to half/double and periods of oscillation, undamped frequencies, damping ratio and many others. Stability analysis of different unconventional configurations will be easier and faster if an access to such configurations is available.

This paper presents a very efficient method of assessment of the designing parameters, especially in an early stage of the design process. In open literature, there are a great number of datasets for classical configurations, but it is hard to find anything for passenger BWB and tailless UAVs. Stability computations are performed based on equations of motion derived in the stability frame of the reference fixed with one-quarter of MAC. It can be considered as an original, not typical but a very practical approach because values of stability and control derivatives do not change even if the centre of gravity is travelling.

In this paper, the suboptimal algorithm of adaptive control system is presented, which is specially adjusted for automatic flight control systems of general aviation and commuter aircraft, and unmanned aircraft (UMA) that conduct flights in atmospheric turbulence. At first, the method could be applied for correcting these changes in flight dynamics parameters, which cannot be compensated with the aid of an open adaptation loop. At the same time, full identification of aircraft model in real time is not required. This method is based on the estimation of most typical parameters of the aircraft mathematical model, which are most closely related to parameters, which are unmeasurable during flight, like aircraft real mass and position of center of gravity. The structure of an adaptation algorithm of aircraft flight control laws is based on the expert knowledge in the field of flight dynamics and is the result of optimization calculations. The examples which show attaining better flight comfort of the PZL M20, “Mewa” general aviation aircraft and quality improvement of the UMA, “Vector” pitch angle automatic control, have been presented.