Open AccessControl of Cricket System Using LQR Controller Optimized by Particle Swarm Optimization
Author(s) -
Yongli Zhang,
Yunfei Li,
Yu Liu,
Guorong Yi
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1670/1/012016
Subject(s) - control theory (sociology) , particle swarm optimization , controller (irrigation) , cricket , underactuation , nonlinear system , computer science , stability (learning theory) , multivariable calculus , control engineering , engineering , control (management) , physics , algorithm , artificial intelligence , ecology , quantum mechanics , machine learning , agronomy , biology
The cricket system, as a strongly coupled, nonlinear and multivariable two dimensional cue system, is a typical representative of unstable and underactuated system. In this paper, the system is analyzed by modeling based on the cricket experimental platform, and while designing the LQR controller, the particle swarm algorithm is introduced to optimize the controller parameters to determine the optimal weight matrix Q in order to solve the difficult problem of controller parameter rectification. The simulation results show that the PSO-LQR can restore the balance of the system in a shorter period of time with enhanced stability compared to a single LQR controller, which exhibits good control performance.