Graph-based path decision modeling for hypersonic vehicles with no-fly zone constraints

Zhang, Yuan; Zhang, Ran; Li, Huifeng

doi:10.1016/j.ast.2021.106857

Cited by 9 publications

(3 citation statements)

References 28 publications

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“…Researchers have refined these methodologies and obtained positive outcomes. Zhang et al [15,16] proposed a path-trajectory dual-level planning method for hypersonic vehicles under complex no-fly zone constraints to avoid getting trapped in local solutions and reduce the error caused by simplifying the motion model. Chen et al [17] introduced an iterative algorithm to estimate the switching position and re-entry flight time, aiming to guide the hypersonic vehicle to enter the midterminal guidance switch window successfully while adhering to no-fly zone constraints in scenarios where the target is undergoing rapid maneuvers.…”

Section: Introductionmentioning

confidence: 99%

A Novel Strategy for Hypersonic Vehicle With Complex Distributed No-Fly Zone Constraints

Zhengxin,

Shifeng

2024

International Journal of Aerospace Engineering

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Aiming at solving trajectory planning problem with complex distributed no-fly zone constraints, this paper proposed a novel obstacle avoidance strategy. For longitudinal motion, an angle of attack adjustment method is employed to adjust lift and design the angle of attack profile, while adjusting the bank angle for range and altitude correction to meet terminal constraints. For lateral motion, this paper developed enhanced attractive, repulsive, and velocity potential fields. Combined with the proposed repulsive force reconstruction method, this effectively resolves the overmaneuvering problem of traditional artificial potential field methods (APFMs) for vehicle. In order to avoid mismatched magnitudes of attractive and repulsive forces, a complementary no-fly zone avoidance strategy based on minimum turn radius is introduced, updating the bank angle command during no-fly zone avoidance. Simulation results indicate that the proposed strategy can address the avoidance of sudden threat, proving to be feasible and effective for handling complex distributed no-fly zone avoidance problems.

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Section: Introductionmentioning

confidence: 99%

A Novel Strategy for Hypersonic Vehicle With Complex Distributed No-Fly Zone Constraints

Zhengxin,

Shifeng

2024

International Journal of Aerospace Engineering

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“…This approach allows for the determination of control profiles that satisfy equilibrium glide conditions, terminal conditions, and a range of load factor constraints while also minimizing the peak heat rate. Meanwhile, mission constraints such as specifying a particular destination or satisfying a particular flight trajectory are requirements that depend on different missions [27]. The collision and obstacle avoidance problem is a fundamental research area in the domain of multiagent systems and has recently acquired significant attention in the robotics and control system communities.…”

Section: Introductionmentioning

confidence: 99%

Distributed Formation Control with Obstacle and Collision Avoidance for Hypersonic Gliding Vehicles Subject to Multiple Constraints

Zhang,

Luo,

2023

International Journal of Aerospace Engineering

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Multiple hypersonic gliding vehicles’ (HGVs’) formation control problems with obstacle and collision avoidance are investigated in this paper, which is addressed in the stage of entry gliding. The originality of this paper stems from the formation control algorithm where constraints of dynamic pressure, heating rate, total aerodynamic load, control inputs, collision avoidance, obstacle avoidance, and the terminal states are considered simultaneously. The algorithm implements a control framework designed to be of two terms: distributed virtual controller and actual control input solver. The distributed virtual controller is based on distributed model predictive control with synchronous update strategy, where the virtual control signals are derived by the optimization simultaneously at each time step for each HGV under directed communication topology. Subsequently, according to the virtual control signals obtained, a coupled nonlinear equation set is solved to get actual control signals: each HGV’s bank angle together with the angle of attack. The actual control input solver adopts a feasible solution process to calculate the actual control signals while dealing with constraints. Finally, extensive numerical simulations are implemented to unveil the proposed algorithm’s performance and superiority.

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“…This situation causes the UAV to consume more energy [11]. In the presence of obstacles and constraints, optimal path planning is required for the UAV to safely follow the specified path with minimum energy and time consumption [12,13]. The UAV path planning problem is a complex optimization problem that requires efficient algorithms to solve.…”

Section: Introductionmentioning

confidence: 99%

Metaheuristic Optimization-Based Path Planning and Tracking of Quadcopter for Payload Hold-Release Mission

2022

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Under harsh geographical conditions where manned flight is not possible, the ability of the unmanned aerial vehicle (UAV) to successfully carry out the payload hold–release mission by avoiding obstacles depends on the optimal path planning and tracking performance of the UAV. The ability of the UAV to plan and track the path with minimum energy and time consumption is possible by using the flight parameters. This study performs the optimum path planning and tracking using Harris hawk optimization (HHO)–grey wolf optimization (GWO), a hybrid metaheuristic optimization algorithm, to enable the UAV to actualize the payload hold–release mission avoiding obstacles. In the study, the hybrid HHO–GWO algorithm, which stands out with its avoidance of local minima and speed convergence, is used to successfully obtain the feasible and effective path. In addition, the effect of the mass change uncertainty of the UAV on optimal path planning and tracking performance is determined. The effectiveness of the proposed approach is tested by comparing it with the metaheuristic swarm optimization algorithms such as particle swarm optimization (PSO) and GWO. The experimental results obtained indicate that the proposed algorithm generates a fast and safe optimal path without becoming stuck with local minima, and the quadcopter tracks the generated path with minimum energy and time consumption.

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Graph-based path decision modeling for hypersonic vehicles with no-fly zone constraints

Cited by 9 publications

References 28 publications

A Novel Strategy for Hypersonic Vehicle With Complex Distributed No-Fly Zone Constraints

A Novel Strategy for Hypersonic Vehicle With Complex Distributed No-Fly Zone Constraints

Distributed Formation Control with Obstacle and Collision Avoidance for Hypersonic Gliding Vehicles Subject to Multiple Constraints

Metaheuristic Optimization-Based Path Planning and Tracking of Quadcopter for Payload Hold-Release Mission

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