Optimal aircraft terrain-following analysis and trajectory generation

Lu, Ping; Pierson, Bion L.

doi:10.2514/6.1995-3479

Cited by 8 publications

(11 citation statements)

References 13 publications

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“…The cost function was taken according to Eqs. (8), (10), (12), and (14). The following weights were used, unless otherwise stated: w time = 0.2, w altitude = 1, and w riding qualities = 1.…”

Section: Resultsmentioning

confidence: 99%

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Fast Graph-Search Algorithms for General-Aviation Flight Trajectory Generation

Rippel

Bar-Gill

Shimkin

2005

Journal of Guidance, Control, and Dynamics

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We consider numerical algorithms for onboard flight trajectory generation and optimization in threedimensional space. Our approach relies on graph-search algorithms, which perform a global search over the set of feasible trajectories. We start by formulating a simplified kinematic model that is appropriate for generalaviation aircraft. The cost function to be optimized includes accounts for position-dependent criteria such as the flight altitude and terrain clearance. Additional dynamic components that involve the angular velocities are introduced to account for riding qualities and pilot workload. Using an approximate grid-based discretization scheme, we transform the continuous optimization problem into a search problem over a finite graph and apply Dijkstra's shortest-path algorithm to this problem. To reduce the computation time to acceptable levels, we introduce a novel state reduction technique that leads to suboptimal search. Further speedup is achieved by heuristic search techniques and hierarchical methods. Performance of the proposed algorithms is evaluated for a trajectory optimization problem with terrain following over a 100 × × 100 km area. Our experiments demonstrate the potential of these algorithms, when combined, to provide an onboard solution to realistic flight-trajectory-generation problems.

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Section: Resultsmentioning

confidence: 99%

“…The riding qualities cost component [Eq. (14)] is then given by (27) We have thus defined the graph G = (V, E) with nonnegative edge costs, C(u, v) ≥ 0. The required solution is the shortest path on this graph, which can be found using standard graph-search algorithms.…”

Section: B Graph Structure and Costsmentioning

confidence: 99%

Fast Graph-Search Algorithms for General-Aviation Flight Trajectory Generation

Rippel

Bar-Gill

Shimkin

2005

Journal of Guidance, Control, and Dynamics

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“…In fact, the desired lateral motion of aircraft is determined as the result of an optimal control problem, whereas the longitudinal path is constructed by segments of parabolas that clear critical points. Lu and Pierson (1995) use an optimal control approach for TF manoeuvre of an aircraft. In this approach, path following and flight time are combined in cost function.…”

Section: Previous Researchmentioning

confidence: 99%

“…In some cases, simple dynamics model are used too, for instance, Lu and Pierson (1995) use a simple dynamics; which mathematically guaranties an optimal solution. However, implementation of such solutions in actual scenarios is still a concern.…”

Section: Aircraft Dynamicsmentioning

confidence: 99%

Aircraft terrain following flights based on fuzzy logic

Rahim

Malaek

2011

Aircraft Engineering and Aerospace Technology

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“…In Ref. [3], the TF problem of an aireraft is fomiulated as an optimal control problem that combines short flight time and path following objectives. In the latter study the aircraft dynamics are represented by point mass equations of motion in a vertical plane.…”

Section: Department Of Aerospace Engineeringmentioning

confidence: 99%

A novel minimum time trajectory planning in terrain following flights

Malaek

Kosari²

2003 IEEE Aerospace Conference Proceedings (Cat. No.03TH8652)

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a new methodology has been proposed to enhance inverse dynamics applications in the process of trajectory planning and optimization in Terrain Following Flights (TFF). The new approach uses least square scheme to solve a general two-dimensional (2D) Terrain Following Flight in a vertical plane. In the mathematical process, Chebyshev polynomials are used to model the geographical data of the terrain in a given route in a manner suitable for the aircraft at hand. The aircraft then follows the modeled terrain with sufficient clearance. In this approach the TF problem is effectively converted to an optimal tracking problem. Results show that. this method provides a flexible approach to solve the TFF problem especially in conditions where the existing temin to he flown over is not mathematically well behaved TABLE OFCONTENTS

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Optimal aircraft terrain-following analysis and trajectory generation

Cited by 8 publications

References 13 publications

Fast Graph-Search Algorithms for General-Aviation Flight Trajectory Generation

Fast Graph-Search Algorithms for General-Aviation Flight Trajectory Generation

Aircraft terrain following flights based on fuzzy logic

A novel minimum time trajectory planning in terrain following flights

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