Stochastic analysis of fuel consumption in aircraft cruise subject to along-track wind uncertainty

Vázquez, Rafael; Rivas, Damiân; Franco, Antônio

doi:10.1016/j.ast.2017.03.027

Cited by 22 publications

(11 citation statements)

References 12 publications

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“…In the literature on the aircraft control in the presence of wind, different random models such as white noise (Deori et al, 2016; Rezaee et al, 2014), beta distribution (Vazquez et al, 2017), and Markov chain (Liu et al, 2019) have been applied to drive wind speed behavior. In effect, it has been demonstrated that wind modeling using Weibull distribution produces more reliable results than the other distributions (Carta et al, 2009; Zárate-Minano et al, 2016).…”

Section: Simulation Resultsmentioning

confidence: 99%

Fault-tolerant formation control of stochastic nonlinear multi-agent systems with time-varying weighted topology

Siavash

Majd

Tahmasebi

2020

Transactions of the Institute of Measurement and Control

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In this paper, the fault-tolerant formation control of nonlinear stochastic multi-agent systems in the presence of actuator faults, disturbances, and time-varying weighted topology is considered. While most traditional fault-tolerant control methods in the literature use fixed weights on the topology edges, in this study these weights are considered time-varying using a pre-designed function, which allows formulating the system more realistically. Moreover, in contrast with previous works on fault-tolerant multi-agent systems, in this study, the model of the agents is considered to be stochastic in general. Furthermore, the actuators of the agents are considered to have a time-varying fault of additive and multiplicative types. A passive and an active fault-tolerant controllers are designed based on the back-stepping sliding-mode approach. In the passive method, a constant robust controller is proposed using an upper bound of the faults while, in the active controller, the additive and multiplicative faults are estimated using adaptive laws. The active and passive fault-tolerant controllers guarantee that the formation errors converge to a bounded region near the origin in a mean-square sense and all of the existing signals in the closed-loop system remain bounded in probability. The results of the formation control are extended to consensus control as well. Finally, a stochastic multi-aircraft model and an RLC circuit with stochastic part are used as two case studies to illustrate the effectiveness of the proposed design method.

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Section: Simulation Resultsmentioning

confidence: 99%

Fault-tolerant formation control of stochastic nonlinear multi-agent systems with time-varying weighted topology

Siavash

Majd

Tahmasebi

2020

Transactions of the Institute of Measurement and Control

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“…We consider the effects of wind speed and direction in dynamic weather conditions. Highly random nature of wind speed and direction (i.e., headwind and tailwind) greatly influences the battery consumption rate and flight range of the drone [36] [37]. We present a model to determine the impact of wind speed and direction on the travel time of a drone.…”

Section: Effects Of Wind Speed and Direction In Daasmentioning

confidence: 99%

Resilient Composition of Drone Services for Delivery

Shahzaad,

Bouguettaya,

Mistry

et al. 2020

Preprint

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We propose a novel resilient drone service composition framework for delivery in dynamic weather conditions. We use a skyline approach to select an optimal set of candidate drone services at the source node in a skyway network.Drone services are initially composed using a novel constraint-aware deterministic lookahead algorithm using the multi-armed bandit tree exploration. We propose a heuristic-based resilient service composition approach that adapts to runtime changes and periodically updates the composition to meet delivery expectations. Experimental results prove the efficiency of the proposed approach.

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“…A great impact in flight duration was observed, with no seasonal variation, and an important decrease when the time frame gets closer to the used forecast. Moreover, Vazquez et al [10] analyzed the influence of along-track wind uncertainty (also based on EPS) in fuel mass distribution based on a probabilistic transformation method. Both studies can be casted as trajectory prediction problems since the flight path is known a priori, and thus, they are only capable of characterizing uncertainty.…”

Section: Introductionmentioning

confidence: 99%

“…For flight planning purposes, a rather straightforward approach is to extend some of the probabilistic trajectory prediction approaches (e.g., [9,10]) to consider a higher algorithmic level in which the flight path is found using the discrete optimization method. This was followed by Cheung et al in [11], where they used a Dijkstra-based trajectory predictor and also evaluated the quality of different EPSs, and by Franco et al [12], who addressed the optimization of a North Atlantic crossing also using a Dijkstra algorithm together with their probabilistic trajectory predictor based on the probabilistic transformation method.…”

Section: Introductionmentioning

confidence: 99%

Characterization and Enhancement of Flight Planning Predictability under Wind Uncertainty

García-Heras

Soler

González-Arribas

2019

International Journal of Aerospace Engineering

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A novel study is presented aiming at characterizing and illustrating potential enhancements in flight planning predictability due to the effects of wind uncertainty. A robust optimal control methodology is employed to calculate robust flight plans. Wind uncertainty is retrieved out of Ensemble Probabilistic Forecasts. Different wind approximation functions are compared, typifying errors, and illustrating its importance for accurate solving of the robust optimal control problem. A set of key performance indicators is defined for the quantification of uncertainty in terms of flight time and fuel consumption. Two different case studies are presented and discussed. The first one is based on a representative sample of the whole 2016 year for a single origin-destination and a forecast time step of 6 hours. As for the second, we select the most uncertain day together with a multiorigin-destination set of flights with forecast time steps up to 2 days.

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Stochastic analysis of fuel consumption in aircraft cruise subject to along-track wind uncertainty

Cited by 22 publications

References 12 publications

Fault-tolerant formation control of stochastic nonlinear multi-agent systems with time-varying weighted topology

Fault-tolerant formation control of stochastic nonlinear multi-agent systems with time-varying weighted topology

Resilient Composition of Drone Services for Delivery

Characterization and Enhancement of Flight Planning Predictability under Wind Uncertainty

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