Real-time optimal trajectory planning for autonomous vehicles and lap time simulation using machine learning

Garlick, Sam; Bradley, Andrew P.

doi:10.1080/00423114.2021.2011929

Cited by 5 publications

(1 citation statement)

References 41 publications

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“…Manufacturers are producing a large number of quadcopters in response to the increasing demand for these aerial vehicles ( Deepak & Singh, 2016 ). As production goes up, it becomes clearer how important it is to develop new algorithms that can accurately track references and make it easier for quadcopters to ignore disturbances ( Mendoza-Soto, Corona-Sánchez & Rodríguez-Cortés, 2018 ; Song, Zhao & Theil, 2023 ; Garlick & Bradley, 2021 ). The need to increase the effectiveness of quadcopters in various fields is what drives the primary emphasis on improving algorithms in this constantly changing environment.…”

Section: Introductionmentioning

confidence: 99%

Enhanced trajectory tracking for quadrotors: disturbance observer state feedback control

Ren,

Wang,

Guan

2024

PeerJ Computer Science

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This study investigates the dynamics and trajectory tracking of quadcopters by utilizing the Disturbance Observer-based Control (DOBC) algorithm. The quadcopter’s dynamic model, which consists of six degrees of freedom, includes both disturbances and uncertainties in the model. The DOBC approach incorporates the disturbance model into the system by introducing it at the input variables. It then compensates for disturbances to achieve accurate tracking of different reference trajectories. The simulated trajectories span a range of motion, varying from simple straight paths to complex spiral paths. In order to verify and evaluate the efficacy of the suggested control technique, simulations are performed using MATLAB. The simulations conclusively show that the disturbance observer-based method effectively achieves the tracking of specified reference trajectories in three-dimensional space. The study highlights the effectiveness of the DOBC algorithm in reducing the effects of disturbances and uncertainties, thereby improving the quadcopter’s capacity to accurately track various trajectories.

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