Letteratura scientifica selezionata sul tema "Phugoid trajectory"

In this study, a guidance scheme for an aerodynamically controlled hypersonic boost-glide class of flight vehicle is proposed. In this work, optimum glide dynamic pressure corresponding to maximum L/ D throughout the flight is calculated and a mid-course guidance law formulation to track the dynamic pressure while suppressing phugoid oscillations is proposed for real-time flight trajectory shaping. Efficacy of the proposed guidance scheme has been demonstrated through simulation studies. Robustness analysis on the proposed guidance algorithm is carried out using Monte Carlo technique. Lastly, a pattern search algorithm-based offline generated maximum L/ D optimal trajectory existing in literature, which meets minimum dynamic pressure, maximum airframe skin temperature, as well as other in-flight and terminal constraints is used as reference trajectory to evaluate the performance of the proposed guidance scheme.

In this paper, a novel design approach for low-speed recovery of a high-performance fighter aircraft is presented. It is shown that the phugoid mode has an important bearing on the problem of low-speed departure. Based on the analysis of the phugoid mode trajectories, a novel low-speed protection algorithm is presented in this paper. The proposed low speed recovery is achieved in three phases. The first phase consists of detecting the incipient departure followed in the second phase by the application of suitable recovery controls and finally the third phase ends with the transfer of controls to the pilot. The design of the first and the third phase consist of choosing the correct trigger conditions which ensures safe recovery of the aircraft in all conditions. The proposed Automatic low speed recovery is triggered when the aircraft trajectory crosses a fixed boundary in the region spanned by the dynamic pressure and its rate of decrease. It is observed that this boundary is approximately a straight line, implying that it is equivalent to a forward prediction in time to indicate when the aircraft will reach the lowest controllable airspeed. This Automatic Low Speed Recovery with Forward Prediction (ALSR-FP) algorithm is found to be simpler than other existing design methods and effective in preventing low speed departure for a variety of pilot inputs that result in the aircraft losing airspeed leading to stall. In the second phase control inputs are chosen to align the velocity vector to the direction of local gravity. The recovery phase is considered complete after the aircraft reaches the dynamic pressure which is approximately 10 % higher than the minimum dynamic pressure for control. Performance of the ALSR-FP is demonstrated using the high-performance fighter aircraft ADMIRE model which has a delta wing configuration, canards and multiple redundant controls. It is also shown that the proposed algorithm can be easily implemented on board for any other fighter and civil aircraft.

Purpose This paper aims to overcome the main obstacle to compare the merits of the different control strategies for fixed-wing unmanned aerial vehicles (UAVs) to assess autopilot performances. Up to now, the published studies of control strategies have been carried out over disperse models, thus being complicated, if not impossible, to compare the merits of each proposal. The authors present a worked benchmark for autopilots studies, consisting of generalized models obtained by merging UAVs’ parameters gathered from selected literature (journals) with other parameters directly obtained by the authors to include some relevant UAVs whose models are not provided in the literature. To obtain them it has been used a dedicated software (from U.S. Air Force). Design/methodology/approach The proposed models have been constructed by averaging both the main aircraft defining parameters (model derivatives) and pole-zero locations of longitudinal transfer functions. The suitability of the used methodologies has been checked from their capability to fit the short period and the phugoid modes. Previous analytical model arrangement has been required to match a uniform set of parameters, as the inner state variables are neither the same along the different published models nor between the additional models the authors have here contributed. Besides, moving models between the space state representation and transfer function is not just a simple averaging process, as neither the parameters nor the model orders are the same in the different published works. So, the junction of the models to a common set of parameters requires some residual’s computation and transient responses assessment (even Fourier analysis has been included to preserve the dominance of the phugoid) to keep the main properties of the models. The least mean squares technique has been used to have better fittings between SISO model parameters with state–space ones. Findings Both the SISO (Laplace) and state-space models for the longitudinal transfer function of an “averaged” fixed-wing UAV are proposed. Research limitations/implications More complicated situations, such as strong wind conditions, need another kind of models, usually based on finite element method simulation. These particular models apply fluid dynamics to study aerostructural aircraft aspects, such as flutter and other aerolastic aspects, the behavior under icing conditions or other distributed parameter problems. Even some models aim to control other aspects than the autopilot, such as the trajectory prediction. However, these models are not the most suitable for the basic UAV autopilot design (early design), so they are outside the objective of this paper. Obviously, the here-considered UAVs are not all the existing ones, but the number is large enough to consider the result as a reliable and realistic representation. The presented study may be seen as a stepping stone, allowing to include other UAVs in future works. Practical implications The proposed models can be used as benchmarks, or as a previous step to produce improved benchmarks, in order to have a common and realistic scenario the compare the benefits of the different control actions in UAV autopilots continuously presented in the published research. Originality/value A work with the scope of the presented one, merging model parameters from literature with other (often referred in papers and websites) whose parameters have been obtained by the authors has been never published.

AbstractFor the entry guidance problem of hypersonic gliding vehicles (HGVs), an analytical predictor–corrector guidance method based on feedback control of bank angle is proposed. First, the relative functions between the velocity, bank angle and range-to-go are deduced, and then, the analytical relation is introduced into the predictor–corrector algorithm, which is used to replace the traditional method to predict the range-to-go via numerical integration. To eliminate the phugoid trajectory oscillation, a method for adding the aerodynamic load feedback into the control loop of the bank angle is proposed. According to the quasi-equilibrium gliding condition, the function of the quasi-equilibrium glide load along with the velocity variation is derived. For each guidance period, the deviation between the real-time load and the quasi-equilibrium gliding load is revised to obtain a smooth reentry trajectory. The simulation results indicate that the guidance algorithm can adapt to the mission requirements of different downranges, and it also has the ability to guide the vehicle to carry out a large range of lateral maneuvers. The feedback control law of the bank angle effectively eliminates the phugoid trajectory oscillation and guides the vehicle to complete a smooth reentry flight. The Monte Carlo test indicated that the guidance precision and robustness are good.

Le projet de thèse consiste à développer une solution pour l'atterrissage d'un drone à voilure fixe de configuration classique dans une zone limitée. Le principal défi consiste à réduire la vitesse de l'avion à une phase minimale pendant le vol, à l'aide d'algorithmes de contrôle automatique. La réduction de la vitesse d'un drone à voilure fixe s'effectue en augmentant son angle d'attaque, ce qui implique un freinage par la force de traînée. Cependant, cette manœuvre est critique pour un avion conventionnel, parce que si son angle d'attaque augmente au-delà de l'angle de décrochage, le véhicule peut perdre sa contrôlabilité, c'est-à-dire qu'il est possible que le véhicule aérien s'effondre et que sa structure soit endommagée. Le modèle mathématique est une représentation d'équations qui décrit le comportement de la dynamique du système. En considérant plusieurs variables pour obtenir une meilleure approximation de la dynamique du système, dans notre cas le véhicule à voilure fixe, la conception des stratégies de contrôle sera plus difficile et plus complexe. Dans ce travail de recherche, nous utiliserons un modèle mathématique non linéaire car les effets de décrochage peuvent être inclus par des approximations mathématiques du moment de tangage, des forces de portance et de traînée. Cela nous permet d'obtenir une meilleure performance des lois de contrôle pour la navigation autonome du drone à voilure fixe. L'une des limites des véhicules à voilure fixe est qu'ils atterrissent dans des espaces de dimensions réduites et que le pourcentage de dommages subis par leur structure est élevé. En outre, les perturbations extérieures et l'inexpérience des pilotes augmentent le risque de dommages. Il est bien connu qu'il est très difficile de satisfaire aux conditions d'une piste d'atterrissage. Par conséquent, la communauté scientifique s'est efforcée de mettre au point des solutions pour l'atterrissage dans des zones limitées. Dans la littérature, on trouve quelques solutions basées sur des véhicules hybrides et des systèmes de récupération. Les véhicules hybrides consistent à modifier la structure d'un véhicule à voilure fixe. Les moteurs sont répartis stratégiquement pour obtenir une configuration de véhicule multirotor, offrant certaines caractéristiques telles que le décollage et l'atterrissage verticaux. Cependant, ces actionneurs augmentent la masse du véhicule, la consommation d'énergie (ce qui réduit la durabilité du vol), la probabilité de défaillance, le coût d'acquisition, de réparation et d'entretien. Notre objectif dans ce travail de recherche est de concevoir et de valider des stratégies de contrôle pour l'atterrissage d'un drone à voilure fixe dans un espace limité. Les stratégies de contrôle ont été conçues selon deux approches : la première est basée sur le développement de manœuvres pour un drone à voilure fixe afin de réduire la vitesse à une phase minimale pendant le vol. Dans la deuxième approche, nous avons travaillé sur les stratégies de contrôle pour l'atterrissage d'un drone à voilure fixe sur un véhicule terrestre en mouvement. Une stratégie de contrôle a été proposée pour réduire la vitesse du drone à voilure fixe au minimum afin d'être capturé par un système de récupération. La stratégie de contrôle a été divisée en trois étapes de vol : dans la première étape, l'avion s'aligne dans le plan x-y tandis qu'il est conduit à une altitude souhaitée pour effectuer un vol de croisière. L'étape suivante consiste en un vol ascendant, axé sur le suivi d'une référence angulaire basée sur une trajectoire phugoïde. Cette trajectoire implique une augmentation de l'angle d'attaque jusqu'à l'angle de décrochage de l'avion. Ainsi, la vitesse aérienne obtient une réduction maximale dans des conditions sûres, permettant au drone d'être capturé par le système de récupération. Toutefois, si le drone n'est pas capturé par le système de récupération, une stratégie de contrôle est appliquée pour rétablir le vol de l'aéronef
The development of this thesis consists of designing some control strategies that allow a fixedwing drone with classical configuration to perform a safe landing in a limited area. The main challenge is to reduce the aircraft’s airspeed avoiding stall conditions. The developed control strategies are focused on two approaches: the first approach consists of the designing airspeed reduction maneuvers for a fixed-wing vehicle to be captured by a recovery system and for a safe landing at a desired coordinate. The next approach is focused on landing a fixed-wing drone on a moving ground vehicle. A dynamic landing trajectory was designed to lead a fixedwing vehicle to the position of a ground vehicle, reaching its position in a defined distance. Moreover, this trajectory was used in a cooperative control design. The control strategy consists of the synchronization of both vehicles to reach the same position at a desired distance. The aerial vehicle tracks the dynamic landing trajectory, and the ground vehicle controls its speed. In addition, we will propose a control architecture with a different focus, where the ground vehicle performs the tracking task of the aerial vehicle’s position in order to be captured. And, the drone’s task is to track a descending flight until the top of the ground vehicle. However, considering the speed difference between both vehicles. Therefore, we propose a new control architecture defining that the aircraft performs an airspeed reduction strategy before beginning its landing stage. The aircraft will navigate to a minimum airspeed, thus, allowing the ground vehicle to reach the fixed-wing drone’s position by increasing its speed. The control laws of each strategy were determined by developing the Lyapunov stability analysis, thus, the stability is guaranteed in each flight stage. Finally, the control strategies were implemented on prototypes allowing us to validate their performance and obtain satisfactory results for safe landing of a fixed-wing drone with classical configuration