Advanced LPV-MPC for UAV Control Using Particle Swarm Optimization.pdf

With an increasing focus on both performance and efficiency, UAV control systems have made great progress. In this work, we extend a previous LPV-MPC technique by including a more simplified control system for UAVs. The proposed control method removes the requirement for a velocity controller by concentrating on improving MPC performance using Particle Swarm Optimization (PSO) of the weight matrices. This system uses PSO to balance control effort with trajectory ac-curacy and simplifies the control architecture, hence improving UAV control efficiency. It is especially appropriate for situations where simplicity and energy economy are absolutely important.

Publication Details

Journal
Figshare
Published
2024-09-14
DOI
https://doi.org/10.6084/m9.figshare.27020653
Primary Topic
Adaptive Control of Nonlinear Systems
Type
article
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Advanced LPV-MPC for UAV Control Using Particle Swarm Optimization.pdf

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Adaptive Control of Nonlinear Systems
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Advanced LPV-MPC for UAV Control Using Particle Swarm Optimization.pdf

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Abstract

With an increasing focus on both performance and efficiency, UAV control systems have made great progress. In this work, we extend a previous LPV-MPC technique by including a more simplified control system for UAVs. The proposed control method removes the requirement for a velocity controller by concentrating on improving MPC performance using Particle Swarm Optimization (PSO) of the weight matrices. This system uses PSO to balance control effort with trajectory ac-curacy and simplifies the control architecture, hence improving UAV control efficiency. It is especially appropriate for situations where simplicity and energy economy are absolutely important.

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Advanced LPV-MPC for UAV Control Using Particle Swarm Optimization.pdf · Figshare (2024) | TGRS Research Map | TGRS