Distributed Parameterized Predictive Control for Multi-robot Curve Tracking

被引:3
|
作者
Pacheco, Gabriel, V [1 ]
Pimenta, Luciano C. A. [2 ]
Raffo, Guilherme, V [2 ]
机构
[1] Univ Fed Minas Gerais, Grad Program Elect Engn, Belo Horizonte, MG, Brazil
[2] Univ Fed Minas Gerais, Dept Elect Engn, Belo Horizonte, MG, Brazil
来源
IFAC PAPERSONLINE | 2020年 / 53卷 / 02期
基金
巴西圣保罗研究基金会;
关键词
Vector fields; distributed model predictive control; alternating direction method of multipliers; multi-robot systems; coordination; DECENTRALIZED CONTROLLERS;
D O I
10.1016/j.ifacol.2020.12.1054
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This work proposes a guidance strategy of multiple robots to converge and circulate a curve while avoiding collisions by using a distributed model predictive control. To build the model predictive control framework, systems guided by control laws with parameters are considered, which laws are embedded in the optimization problem. After that, the same problem is distributed using the Alternating Direction Method of Multipliers and nonlinear optimization. To solve the task of convergence and circulation of a closed path, a vector field based control law is embedded in the predictive control scheme. The control law results from the sum of two components, a convergence term and a circulation term, whereas each term has one proportional parameter associated. Numerical results present an application example, and the strategy effectiveness is discussed. Copyright (C) 2020 The Authors.
引用
收藏
页码:3144 / 3149
页数:6
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