Aircraft Optimal Terrain/Threat-Based Trajectory Planning and Control

Kamyar, Reza; Taheri, Ehsan

doi:10.2514/1.61339

Cited by 60 publications

(24 citation statements)

References 27 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…To do so, rstly, the optimal control problem was transcribed into a Non-Linear Program (NLP) prob-lem and, then, a Sequential Quadratic Programming (SQP) algorithm was solved the NLP. Another work by Kamyar and Taheri [20] applied a direct sequential method to solve a TF/TA trajectory planning. The control inputs were developed for time-, fuel-, and height-optimal scenarios using a 6DoF dynamic model.…”

Section: Optimal Control Methodsmentioning

confidence: 99%

“…The software code uses numerical methods to compute integration constant, the numbers a 4 ; a 5 ; :::; a n , and the integral term. (20) where H min is a design parameter that can be selected by the trajectory planner. Now, the aircraft ight trajectory planning could be considered as a free nal-time optimal control problem expressed as follows: \Based on the attener-mapping concept explained, Eqs.…”

Section: Formulation Of the Conceptmentioning

confidence: 99%

See 1 more Smart Citation

TF/TA Optimal Flight Trajectory Planning Using a Novel Regenerative Flattener Mapping Method

Kosari

Kassaei

2019

Scientia Iranica

View full text Add to dashboard Cite

In this paper, a new methodology is proposed to enhance the conformal mapping applications in the process of optimum trajectory planning in Terrain Following (TF) and Terrain Avoidance (TA) Flights. The new approach uses the conformal mapping concept as a attener tool to transform the constrained trajectory-planning problem with ight altitude restrictions due to the presence of obstacles into a regenerated problem with no obstacle and minimal height constraints. In this regard, the Schwarz-Christo el theorem was utilized to incorporate the height constraints into the aircraft dynamic equations of motion. The regenerated optimal control problem was then solved by a numerical method, namely the direct Legendre-Gauss-Radau pseudospectral algorithm. A composite performance index of ight time, terrain masking, and aerodynamic control e ort was optimized. Furthermore, to obtain realistic trajectories, the aircraft maximum climb and descent rates were imposed as inequality constraints in the solution algorithm. Several case studies for two-dimensional ight scenarios show the applicability of this approach in TF/TA trajectory planning. Extensive simulations con rm the e ciency of the proposed approach and verify the feasibility of solutions, satisfying all of the constraints underlying the problem.

show abstract

Section: Optimal Control Methodsmentioning

confidence: 99%

Section: Formulation Of the Conceptmentioning

confidence: 99%

TF/TA Optimal Flight Trajectory Planning Using a Novel Regenerative Flattener Mapping Method

Kosari

Kassaei

2019

Scientia Iranica

View full text Add to dashboard Cite

show abstract

“…For instance, the vehicle may be constrained to keep a minimum clearance from the ground to avoid collision with a building. This task is achieved through a path-planner (or guidance algorithm) [13]. The "Navigation" block represents the navigation algorithm that uses sensors to measure instantaneous position, velocity and orientation of the vehicle to be used by the "Controller" block.…”

Section: A Dynamic Modelingmentioning

confidence: 99%

“…A similar approach is used for motion analysis of flying vehicles when only planar motion is assumed. The inclusion of additional degrees of freedom is usually considered for higher-fidelity models and at later stages of design of systems to gain better understanding of the motion and to obtain realistic flight performance envelopes [11][12][13].…”

Section: Introductionmentioning

confidence: 99%

Quad-Rotor Flight Simulation in Realistic Atmospheric Conditions

et al. 2020

Self Cite

View full text Add to dashboard Cite

In trajectory planning and control design for unmanned air vehicles, highly simplified models are typically used to represent the vehicle dynamics and the operating environment. The goal of this work is to perform real-time, but realistic flight simulations and trajectory planning for quad-copters in low altitude (<500m) atmospheric conditions. The aerodynamic model for rotor performance is adapted from blade element momentum theory and validated against experimental data. Large-eddy simulations of the atmospheric boundary layer are used to accurately represent the operating environment of unmanned air vehicles. A reduced-order version of the atmospheric boundary layer data as well as the popular Dryden model are used to assess the impact of accuracy of the wind field model on the predicted vehicle performance and trajectory. The wind model, aerodynamics and control modules are integrated into a six-degree-of-freedom flight simulation environment with a fully nonlinear flight controller. Simulations are performed for two representative flight paths, namely, straight and circular paths. Results for different wind models are compared and the impact of simplifying assumptions in representing rotor aerodynamics is discussed. The simulation framework and codes are open-sourced for use by the community. Nomenclature Symbols c = Rotor chord, m c d = Lumped drag coefficient

show abstract

“…In order to clarify this point, Figure 5 depicts the time history of the switching functions defined in Eqs. (23) and (24). In fact, it shows that only those engines that operate at the maximum power are contributing to the thrust and rate of change of mass, whereas the engine(s) at the lowest power setting is (are) always inactive.…”

Section: Planetary Perturbations In the Modeling Represents The Distumentioning

confidence: 99%

A novel approach for optimal trajectory design with multiple operation modes of propulsion system, part 2

et al. 2020

Self Cite

View full text Add to dashboard Cite

Equipping a spacecraft with multiple solar-powered electric engines (of the same or different types) compounds the task of optimal trajectory design due to presence of both real-valued inputs (power input to each engine in addition to the direction of thrust vector) and discrete variables (number of active engines).Each engine can be switched on/off independently and "optimal" operating power of each engine depends on the available solar power, which depends on the distance from the Sun. Application of the Composite Smooth Control (CSC) framework to a heliocentric fuel-optimal trajectory optimization from the Earth to the comet 67P/Churyumov-Gerasimenko is demonstrated, which presents a new approach to deal with multiple-engine problems. Operation of engine clusters with 4, 6, 10 and even 20 engines of the same type can be optimized.Moreover, engine clusters with different/mixed electric engines are considered with either 2, 3 or 4 different types of engines. Remarkably, the CSC framework allows us 1) to reduce the original multi-point boundary-value problem to a two-point boundary-value problem (TPBVP), and 2) to solve the resulting TP-BVPs using a single-shooting solution scheme and with a random initialization of the missing costates. While the approach we present is a continuous neighbor of the discontinuous extremals, we show that the discontinuous necessary conditions are satisfied in the asymptotic limit. We believe this is the first indirect method to accommodate a multi-mode control of this level of complexity with realistic engine performance curves. The results are interesting and promising for dealing with a large family of such challenging multi-mode optimal control problems.

show abstract

Aircraft Optimal Terrain/Threat-Based Trajectory Planning and Control

Cited by 60 publications

References 27 publications

TF/TA Optimal Flight Trajectory Planning Using a Novel Regenerative Flattener Mapping Method

TF/TA Optimal Flight Trajectory Planning Using a Novel Regenerative Flattener Mapping Method

Quad-Rotor Flight Simulation in Realistic Atmospheric Conditions

A novel approach for optimal trajectory design with multiple operation modes of propulsion system, part 2

Contact Info

Product

Resources

About