Wind-optimal path planning: Application to aircraft trajectories

Airborne Wind Energy

To achieve a high conversion efficiency and at the same time robust control of a pumping kite power system it is crucial to optimize the three-dimensional flight path of the tethered wing. This chapter extends a dynamic system model to account for a realistic, turbulent wind environment and adds a flight path planner using a sequence of attractor points and turn actions. Path coordinates are calculated with explicit geometric formulas. To optimize the power output the path is adapted to the average wind speed and the vertical wind profile, using a small set of parameters. The planner employs a finite state machine with switch conditions that are highly robust towards sensor errors. The results indicate, that the decline of the average power output of pumping kite power systems at high wind speeds can be mitigated. In addition it is shown, that reeling out towards the zenith after flying figure eight flight maneuvers significantly reduces the traction forces during reel-in and thus increases the total efficiency.

Journal of Aerospace Information Systems, 2014

This study develops a trajectory optimization algorithm for approximately minimizing aircraft travel time and fuel burn by combining a method for computing minimum-time routes in winds on multiple horizontal planes, and an aircraft fuel burn model for generating fuel-optimal vertical profiles. It is applied to assess the potential benefits of flying userpreferred routes for commercial cargo flights operating between Anchorage, Alaska and major airports in Asia and the contiguous United States. Flying wind optimal trajectories with a fuel-optimal vertical profile reduces average fuel burn of international flights cruising at a single altitude by 1-3%. The potential fuel savings of performing en-route step climbs are not significant for many shorter domestic cargo flights that have only one step climb. Wind-optimal trajectories reduce fuel burn and travel time relative to the flight plan route by up to 3% for the domestic cargo flights. However, for trans-oceanic traffic, the fuel burn savings could be as much as 10%. The actual savings in operations will vary from the simulation results due to differences in the aircraft models and user defined cost indices. In general, the savings are proportional to trip length, and depend on the en-route wind conditions and aircraft types.

Journal of Guidance, Control, and Dynamics

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.

Journal of Guidance, Control, and Dynamics, 2011

There are indications that persistent contrails can lead to adverse climate change, although the complete effect on climate forcing is still uncertain. A flight trajectory optimization algorithm with fuel and contrails models, which develops alternative flight paths, provides policy makers the necessary data to make tradeoffs between persistent contrails mitigation and aircraft fuel consumption. This study develops an algorithm that calculates wind-optimal trajectories for cruising aircraft while avoiding the regions of airspace prone to persistent contrails formation. The optimal trajectories are developed by solving a non-linear optimal control problem with path constraints. The regions of airspace favorable to persistent contrails formation are modeled as penalty areas that aircraft should avoid and are adjustable. The tradeoff between persistent contrails formation and additional fuel consumption is investigated, with and without altitude optimization, for 12 city-pairs in the continental United States. Without altitude optimization, the reduction in contrail travel times is gradual with increase in total fuel consumption. When altitude is optimized, a two percent increase in total fuel consumption can reduce the total travel times through contrail regions by more than six times. Allowing further increase in fuel consumption does not seem to result in proportionate decrease in contrail travel times.

Journal of Computer and Systems Sciences International, 2012

The flight of an unmanned aerial vehicle under complicated conditions and hazards is con sidered. Hazards are given in terms of 2D relief. To find the optimal 2D path minimizing the risk given constraints on flight time and velocity, the problem with the non given boundary condition is trans formed to the problem with the fixed flight time and the boundary problem solved numerically. The found 2D path is used to construct the polynomial approximation of the 3D path taking into account the local relief.

Trajectory Based Operations (TBO) has been identified by ICAO as a key aviation evolution with significant developments in Next Gen Flight Management Systems (FMS) to communicate with ground based 4DT Air Traffic Management (ATM) system of the future. The Next generation ATM and FMS systems will include the capability of generating 4D trajectories to increase aircraft efficiency and reduce emissions. Natural resources, such as the wind, can be exploited to reduce the aircraft's fuel usage and travel time while improving its operational efficiency. These benefits are realized if trajectories are formulated to maximise the time in tailwind scenarios. The results presented here quantify the fuel and time savings of a typical Australasian route using a simulated wind field as an input to the optimization problem. Minimum fuel burn and emissions are achieved by minimising flight time at constant cruise speed. The attainable savings appeal to aircraft operators as they reduce operatio...

AIAA Guidance, Navigation, and Control Conference, 2009

In the interest of providing online guidance for unmanned aircraft in strong wind fields, a method for decomposing grid-based wind data into an unstructured mesh is analyzed for its effectiveness in simplifying the computational complexity of the problem. The decomposition method is applied to a simulated severe storm data set, resulting in a set with a significantly reduced amount of points. Path planning is performed on both the raw data set and the simplified set using Ordered Upwind Methods combined with a cost function that considers both flight time and precipitation exposure. The results of the path planning are analyzed for required computational time and path accuracy.

2016

A major challenge for Trajectory-Based Operations is the existence of significant uncertainties in the models and systems required for trajectory prediction. In particular, weather uncertainty has been acknowledged as one of the most (if not the most) relevant ones. In the present paper we present preliminary results on robust trajectory planning at the pre-tactical level. The main goal is to plan trajectories that are efficient, yet predictable. State-of-the-art forecasts from Ensemble Prediction Systems are used as input data for the wind field, which we assume to be the unique source of uncertainty. We develop an ad-hoc optimal control methodology to solve trajectory planning problems considering uncertainty in wind fields. A set of Pareto- optimal trajectories is obtained for different preferences between predictability and average efficiency; in particular, we present and discuss results for the minimum average fuel trajectory and the most predictable trajectory, including the ...

15th AIAA Aviation Technology, Integration, and Operations Conference, 2015

This study examines three possible approaches to improving the speed in generating wind-optimal routes for air traffic at the national or global level. They are: (a) using the resources of a supercomputer, (b) running the computations on multiple commercially available computers and (c) implementing those same algorithms into NASA's Future ATM Concepts Evaluation Tool (FACET) and compares those to a standard implementation run on a single CPU. Wind-optimal aircraft trajectories are computed using global air traffic schedules. The run time and wait time on the supercomputer for trajectory optimization using various numbers of CPUs ranging from 80 to 10,240 units are compared with the total computational time for running the same computation on a single desktop computer and on multiple commercially available computers for potential computational enhancement through parallel processing on the computer clusters. This study also re-implements the trajectory optimization algorithm for further reduction of computational time through algorithm modifications and integrates that with FACET to facilitate the use of the new features which calculate time-optimal routes between worldwide airport pairs in a wind field for use with existing FACET applications. The implementations of trajectory optimization algorithms use MATLAB, Python, and Java programming languages. The performance evaluations are done by comparing their computational efficiencies and based on the potential application of optimized trajectories. The paper shows that in the absence of special privileges on a supercomputer, a cluster of commercially available computers provides a good option for computing wind-optimal trajectories for national and global air traffic system studies.

2008

In this paper, we present an approach to autonomous navigation of a balloon by optimally exploiting wind elds to minimize control (i.e. power requirements), time of travel, or other cost functionals. We use the principles of Discrete Mechanics and Optimal Control (DMOC) to compute optimal trajectories for a simpli ed model of balloon dynamics in a two-dimensional, time-dependent wind velocity eld. The wind eld was produced using the Weather Research and Forecasting (WRF) model for a region of the Mojave Desert on July 5, 2005. Due to inherent inaccuracies of the global wind model and the need for e cient optimization, we approach the problem of optimizing medium-scale (i.e., distances of the order approximately 100km) balloon trajectories using a simpli ed model of balloon dynamics. The results presented in this paper provide a framework to extend this approach to nding optimal trajectories in real-time for a three-dimensional wind eld. We hope to test our approach during a balloon ...