2017
DOI: 10.1007/s10846-017-0753-9
|View full text |Cite
|
Sign up to set email alerts
|

Multi-Objective Weight Optimization for Trajectory Planning of an Airplane with Structural Damage

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
4

Citation Types

0
9
0

Year Published

2020
2020
2024
2024

Publication Types

Select...
7

Relationship

0
7

Authors

Journals

citations
Cited by 17 publications
(9 citation statements)
references
References 41 publications
0
9
0
Order By: Relevance
“…Due to the stressful and highly workload nature of the emergency conditions, it is not safe to expect the pilot to do this challenging task without the assistance of automation. Therefore, researchers are working on automation enhancement to help the pilot safely recovering the impaired airplane [1][2][3][4][5]. Automation can help by identifying and adapting to the failure and planning a new optimal landing trajectory that considers new constraints related to the airplane's degraded performance and landing requirements [4,5].…”
Section: Introductionmentioning
confidence: 99%
See 1 more Smart Citation
“…Due to the stressful and highly workload nature of the emergency conditions, it is not safe to expect the pilot to do this challenging task without the assistance of automation. Therefore, researchers are working on automation enhancement to help the pilot safely recovering the impaired airplane [1][2][3][4][5]. Automation can help by identifying and adapting to the failure and planning a new optimal landing trajectory that considers new constraints related to the airplane's degraded performance and landing requirements [4,5].…”
Section: Introductionmentioning
confidence: 99%
“…According to the curved-based nature of the designed guidance route, each trajectory point is specified by the horizontal (πœ’) and vertical (𝛾) turning angles (Θ Μ… = (πœ’, 𝛾)) respecting the inertial plane. Therefore, each point is represented as (𝑋 Μ… , Θ Μ… ) = (π‘₯, 𝑦, 𝑧, πœ’, 𝛾) ∈ 𝑂 Γ— [0,2πœ‹)2 . Depending on the airplane feasible descending rate, which is dictated by the airplane's post-failure performance constraints [𝛾 π‘šπ‘–π‘› , 𝛾 π‘šπ‘Žπ‘₯ ], the trajectory can be expressed as a one-dimensional rotation:(𝑋 Μ… , Θ Μ… ) = [𝑋 π‘šπ‘–π‘› , 𝑋 π‘šπ‘Žπ‘₯ ] 3 β†’ 𝑂 Γ—[πœ’ π‘šπ‘–π‘› , πœ’ π‘šπ‘Žπ‘₯ ] by having a constant descending rate.…”
mentioning
confidence: 99%
“…A Multi-Objective Optimization (MOO) problem typically includes a set of solutions that are favorable for the rest of the solutions in the total search space. These solutions are known as Pareto-optimal solutions or non-dominated solutions [27][28][29], where the rest of the solutions are known as dominated solutions. All solutions in the non-dominated set are acceptable and none of them has the privilege respecting the other solutions [30].…”
Section: Introductionmentioning
confidence: 99%
“…Asadi et al 9 presented an automation strategy concerning damaged airplane recovery in which flight envelope estimation, fault detection and identification, 10 landing trajectory design, and tracking controller subsystems were proposed in an adaptive flight planner architecture, which assists the pilot in emergency fault or failure circumstances. Maneuvering flight envelope of a left-wing-damaged airplane (GTM model) for post-damage trajectory design was derived in Asadi et al 8 Based on the maneuvering flight envelope derived in Asadi et al, 8 a damaged airplane trajectory planning strategy was proposed and examined in the literature 9,11 in which trim database was used as feasible flight conditions for trajectory generation toward the desired landing site.…”
Section: Introductionmentioning
confidence: 99%
“…Among the structural damage investigations, wing damage is much more challenging since the wing is the main lift generating component and wing damage results in asymmetric configuration, therefore flight performance and handling quality of the aircraft are significantly deteriorated. [8][9][10][11] References [14][15][16] proposed reconfigurable adaptive control algorithm for a wing damaged airplane. Kim et al 17 investigate experimental evaluation of an adaptive neural network controller to a flying-wing type unmanned aerial vehicle experiencing partial wing-loss.…”
Section: Introductionmentioning
confidence: 99%