Wind-optimal cruise trajectories using pseudospectral methods and ensemble probabilistic forecasts

Arribas, Daniel González; Arnedo, Manuel Soler; Sanjurjo-Rivo, Manuel

doi:10.1145/2899361.2899378

Cited by 5 publications

(7 citation statements)

References 16 publications

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“…In previous work [38], we found that omitting heading and bank angle dynamics for a free-routing cruise trajectory without sharp turns has minimal impact on solution accuracy (well below other sources of modelling error). The dynamics of the system are, therefore, described by the following system of differential equations (f in Equation (8)):…”

Section: B Dynamical Modelmentioning

confidence: 78%

“…We employ the procedure presented in [38] for building a smooth approximation to the wind with good accuracy. The optimal control problem is formulated as in Section II, discretized with a trapezoidal scheme (see [32,Chapter 4]) into a nonlinear optimization problem, which is then solved by the IPOPT solver [40].…”

Section: Case Studymentioning

confidence: 99%

“…This number does not include the cost of the preprocessing and initialization described in [38], which takes around a minute and we have not optimized for speed as it needs to be run only once. Table 1 shows the final s ize o f t he r esulting n onlinear o ptimization p roblems a fter t he t ranscription o f the DROCT.…”

Section: Case Studymentioning

confidence: 99%

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Robust Aircraft Trajectory Planning Under Wind Uncertainty Using Optimal Control

González-Arribas

Soler

Sanjurjo-Rivo

2018

Journal of Guidance, Control, and Dynamics

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Uncertainty in aircraft trajectory planning and prediction generates major challenges for the future Air Traffic Management system. Therefore, understanding and managing uncertainty will be necessary to realize improvements in air traffic capacity, safety, efficiency and environmental impact. Meteorology (and, in particular, winds) represents one of the most relevant sources of uncertainty. In the present work, a framework based on optimal control is introduced to address the problem of robust and efficient trajectory planning under wind forecast uncertainty, which is modeled with probabilistic forecasts generated by Ensemble Prediction Systems. The proposed methodology is applied to a flight p l anning s c enario u n der a f r ee-routing operational paradigm and employed to compute trajectories for different sets of user preferences, exploring the trade-off between average flight cost and p r edictability. Results show how the impact of wind forecast uncertainty in trajectory predictability at a pre-tactical planning horizon can be not only quantified, b u t a l so r e duced t h rough t h e application of the proposed approach.

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Section: B Dynamical Modelmentioning

confidence: 78%

Section: Case Studymentioning

confidence: 99%

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Robust Aircraft Trajectory Planning Under Wind Uncertainty Using Optimal Control

González-Arribas

Soler

Sanjurjo-Rivo

2018

Journal of Guidance, Control, and Dynamics

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“…In this section, we start by discussing the optimal control structures under uncertainties in UCCD problems. These structures attempt to answer inherently different questions and have been used in separate studies in the literature [20,[25][26][27][28][29][30][31][32][33]. While these structures have a significant impact on the problem implementation and its associated solution, they have not been collectively discussed in the literature to the best of the authors' knowledge.…”

Section: Uccd Implementationmentioning

confidence: 99%

Investigations Into Uncertain Control Co-Design Implementations for Stochastic in Expectation and Worst-Case Robust

Azad

Herber

2022

Volume 5: Dynamics, Vibration, and Control

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As uncertainty considerations become increasingly important aspects of concurrent plant and control optimization, it is imperative to identify and compare the impact of uncertain control co-design (UCCD) formulations on their associated solutions. While previous work has developed the theory for various UCCD formulations, their implementation, along with an in-depth discussion of the structure of UCCD problems, implicit assumptions, method-dependent considerations, and practical insights, is currently missing from the literature. Therefore, in this study, we address some of these limitations by proposing two optimal control structures for UCCD problems that we refer to as the open-loop single-control (OLSC) and open-loop multiple-control (OLMC). Next, we implement the stochastic in expectation UCCD (SE-UCCD) and worst-case robust UCCD (WCR-UCCD) for a simplified strain-actuated solar array (SASA) case study. For the implementation of SE-UCCD, we use generalized Polynomial Chaos expansion and benchmark the results against Monte Carlo Simulation. Next, we solve a simple SASA WCR-UCCD through OLSC and OLMC structures. Insights from such implementations indicate that constructing, implementing, and solving a UCCD problem requires an in-depth understanding of the problem at hand, formulations, and solution strategies to best address the underlying co-design under uncertainty questions.

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“…Direct methods, which have the potential of dealing with more complex and complete problems as discussed in Section 2.4.3, have also been used to optimize trajectories on general wind fields. In [158], [183] and [159], the wind is modeled as a polynomial obtained by regression on tabular data and hybrid optimal control is used in conjunction with a direct transcription to solve the optimal control problem; the wind approximation scheme is improved in [13] with a multiphase formulation.…”

Section: Wind-optimal Aircraft Trajectoriesmentioning

confidence: 99%

Robust aircraft trajectory planning under uncertain convective environments with optimal control and rapidly developing thunderstorms

González-Arribas

Soler

Sanjurjo-Rivo

et al. 2019

Aerospace Science and Technology

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The Air Traffic Management (ATM) system in the busiest airspaces in the world is currently being overhauled to deal with multiple capacity, socioeconomic, and environmental challenges. One major pillar of this process is the shift towards a concept of operations centered on aircraft trajectories (called Trajectory-Based Operations or TBO in Europe) instead of rigid airspace structures. However, its successful implementation (and, thus, the realization of the associated improvements in ATM performance) rests on appropriate understanding and management of uncertainty. Due to its complex socio-technical structure, the design and operations of the ATM system are heavily impacted by uncertainty, proceeding from multiple sources and propagating through the interconnections between its subsystems.One major source of ATM uncertainty is weather. Due to its nonlinear and chaotic nature, a number of meteorological phenomena of interest cannot be forecasted with complete accuracy at arbitrary lead times, which leads to uncertainty or disruption in individual air and ground operations that propagates to all ATM processes. Therefore, in order to achieve the goals of SESAR and similar programs, it is necessary to deal with meteorological uncertainty at multiple scales, from the trajectory prediction and planning processes to flow and traffic management operations. This thesis addresses the problem of single-aircraft flight planning considering two important sources of meteorological uncertainty: wind prediction error and convective activity. As the actual wind field deviates from its forecast, the actual trajectory will diverge in time from the planned trajectory, generating uncertainty in arrival times, sector entry and exit times, and fuel burn. Convective activity also impacts trajectory predictability, as it leads pilots to deviate from their planned route, creating challenging situations for controllers. In this work, we aim to develop algorithms and methods for aircraft trajectory optimization that are able to integrate information about the uncertainty in these meteorological phenomena into the flight planning process at both pre-tactical (before departure) and tactical horizons (while the aircraft is airborne), in order to generate more efficient and predictable trajectories.To that end, we frame flight planning as an optimal control problem, modeling the motion of the aircraft with a point-mass model and the BADA performance model. Optimal control methods represent a flexible and general approach that has a long history of success in the aerospace field. As a numerical scheme, we use direct methods, which can deal with nonlinear systems of moderate and high-dimensional state spaces in a computationally manageable way. Nevertheless, while this framework is well-developed in the context of deterministic problems, the techniques for the solution of practical ix x Abstract optimal control problems under uncertainty are not as mature, and the methods proposed in the literature are not applicable to the flight planning probl...

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Wind-optimal cruise trajectories using pseudospectral methods and ensemble probabilistic forecasts

Cited by 5 publications

References 16 publications

Robust Aircraft Trajectory Planning Under Wind Uncertainty Using Optimal Control

Robust Aircraft Trajectory Planning Under Wind Uncertainty Using Optimal Control

Investigations Into Uncertain Control Co-Design Implementations for Stochastic in Expectation and Worst-Case Robust

Robust aircraft trajectory planning under uncertain convective environments with optimal control and rapidly developing thunderstorms

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