A cooperative particle swarm optimization approach for tuning an MPC-based quadrotor trajectory tracking scheme

Aristotelis Kapnopoulos; Alex Alexandridis

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A cooperative particle swarm optimization approach for tuning an MPC-based quadrotor trajectory tracking scheme

机译：A cooperative particle swarm optimization approach for tuning an MPC-based quadrotor trajectory tracking scheme

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摘要

This paper presents a novel method for tuning a quadrotor trajectory-tracking model predictive control (MPC) framework, based on cooperative particle swarm optimization (PSO). The overall control strategy is decomposed into two different schemes; the first scheme, which is responsible for position control, is based on MPC, whereas the second one, which regulates the attitude of the quadrotor, makes use of three standard PID controllers. To optimize the trajectory tracking ability of the quadrotor, a cooperative PSO framework is introduced for tuning the large number of parameters of diverse nature, which are employed by the different controllers. The method makes use of two distinct swarms, with the first one containing the position controller parameters and the second one the attitude controller parameters. By exchanging information, the two swarms work together in a cooperative way in order to explore more efficiently the search space and discover tuning parameters that improve the trajectory tracking performance. Simulation results on a detailed quadcopter model over trajectories with different geometric characteristics, and comparisons to other tuning approaches verified by statistical testing, illustrate the efficiency of the proposed scheme in optimizing the control parameters. The scheme's robustness is also verified by testing the performance of the resulting controller on trajectories different than the ones used for tuning it.

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来源
《Aerospace science and technology》 |2022年第8期|107725.1-107725.16|共16页
作者
Aristotelis Kapnopoulos; Alex Alexandridis;
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作者单位

Department of Electrical and Electronic Engineering, University of West Attica, Ancient Olive Grove Campus, Thivon 250 & P. Ralli, 12244, Aigaleo, Greece;

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收录信息美国《科学引文索引》(SCI);美国《工程索引》(EI);
原文格式 PDF
正文语种英语
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关键词
Cooperative methods; Model predictive control; Particle swarm optimization; Path tracking; Tuning; Quadcopter;

A cooperative particle swarm optimization approach for tuning an MPC-based quadrotor trajectory tracking scheme

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