Optimal Path-Following Guidance with Generalized Weighting Functions Based on Indirect Gauss Pseudospectral Method

Chen, Qi; Wang, Xugang; Yang, Jing

doi:10.1155/2018/3104397

Cited by 6 publications

(3 citation statements)

References 25 publications

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“…The terminal state is obtained from the initial state and the integral of the right function, and Gauss integral is used for discretization calculation. After the above transformation, the original optimal control problem is transformed into a parametric optimization problem with a series of algebraic constraints, which is also called Nonlinear Programming problem (NLP) [35][36][37].…”

Section: Principle Of Gauss Pseudospectral Methodsmentioning

confidence: 99%

Time-varying Formation Dynamics Modeling and Constrained Trajectory Optimization of Multi-quadrotor UAVs

Zhang

2021

Preprint

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The formation of multiple quadrotor UAVs with long navigation will encounter many flight constraints, so it is necessary to change the formation to avoid these constraints. In this paper, Voronoi graph theory is used to treat UAVs formation as a rigid body. The rigid body structure can be changed by changing the formation before different constraints, after passing constraints the rigid body structure remains the formation unchanged or form into the prescribed formation. The time-varying model is established to facilitate the use of optimization. Based on Gauss pseudospectral method (GPM), the path optimization of a single quadrotor UAV is carried out. The followed UAVs in formation are treated as constraints. The constraints of maximum turning radius and formation transformation time of other UAVs are considered in the optimization process. The minimum time required for formation transformation is optimized to solve the transformation optimization, and the performance index of trajectory optimization is to minimize the energy consumed by the leader quadrotor UAV within the specified time. Finally, the simulation proves the method proposed in this paper.

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Section: Principle Of Gauss Pseudospectral Methodsmentioning

confidence: 99%

Time-varying Formation Dynamics Modeling and Constrained Trajectory Optimization of Multi-quadrotor UAVs

Zhang

2021

Preprint

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“…The optimization problem defined by ( 23) and ( 24) needs to be converted into a discrete nonlinear programming problem (NLP) to solve [41]. VOLUME 11, 2023 According to the two-point boundary value problem, the required time t 0 ∈ [t 0 , t f ] taken for landing is first scaled to τ ∈ [−1, 1], and the mapping relationship is expressed as:…”

Section: B Discretization Of the Trajectory Optimization Problemmentioning

confidence: 99%

Dynamics Modeling and Autonomous Landing for Flexible Parafoil-Vehicle Multibody System

et al. 2023

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In this paper, the autonomous landing of the parafoil used for aerial vehicles is investigated through the numerical approach. The coupled parafoil-vehicle dynamics model is developed based on the multibody method. The transition process from aircraft flight to parafoil glide is designed in a global system framework. To deal with large flexible deformations during the deployment process, the parafoil canopy is approximated as interacting symmetric subparts using the geometric division method. The pseudo-spectral method is employed to generate a reference trajectory for the landing target. As the system dynamics are introduced into constraint conditions, the generated trajectory is beneficial to improve landing precision. In addition, other optimization objectives, including minimal energy consumption and obstacle avoidance, are considered in trajectory planning. The enhanced proportional integral control is designed to follow the reference trajectory. The neural network inversion model is used to reduce the coupling effect between the longitudinal and the directional control channels. There is a coupling effect that the two controls both are implemented through left and right trailing-edge deflections. An adaptive output allocation method is proposed to ensure that the directional control always is effective in particular when one side reaches saturation. Finally, simulations for autonomous landing under different conditions are carried out to validate the integrated system.INDEX TERMS Flexible parafoil model, multi-body system, trajectory optimization, flight control.

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“…It is aimed that the robots follow the shortest distances in the desired path trajectory and the path under the most suitable conditions according to the robot characteristics. Optimum conditions at the path tracking stage includes criteria such as robot velocity, avoidance of obstacles and robot collisions, orbital planning suitable for robot kinematics and dynamics (Chen et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

Waypoint-Based Path Tracking Approach For Self-Organized Swarm Robots

Mısır

ÇELİK

Gökrem

2022

IJERAD

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In this paper, a waypoint-based path tracking approach is suggested for the swarm robots to follow the desired path in an organized way. In the study, the applicability of the waypoint-based path tracking on the swarm robots that show flexible and scalable behavior has been demonstrated. To evaluate the proposed path planing approach with regard to scalability and flexibility, simulations have been applied in with/without obstacle arenas with different numbers of robots and according to different lookahead distances. With the proposed approach, each swarm robots exhibit swarm behavior in an organized manner depending on the distance of the lookahead to the path to track in the with / without obstacle arenas.

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Optimal Path-Following Guidance with Generalized Weighting Functions Based on Indirect Gauss Pseudospectral Method

Cited by 6 publications

References 25 publications

Time-varying Formation Dynamics Modeling and Constrained Trajectory Optimization of Multi-quadrotor UAVs

Time-varying Formation Dynamics Modeling and Constrained Trajectory Optimization of Multi-quadrotor UAVs

Dynamics Modeling and Autonomous Landing for Flexible Parafoil-Vehicle Multibody System

Waypoint-Based Path Tracking Approach For Self-Organized Swarm Robots

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