TY - JOUR
T1 - Fuzzy Cooperative Control for the Stabilization of the Rotating Inverted Pendulum System
AU - Wang, Yujue
AU - Mao, Weining
AU - Wang, Qing
AU - Xin, Bin
N1 - Publisher Copyright:
© Fuji Technology Press Ltd.
PY - 2023/5
Y1 - 2023/5
N2 - The rotating inverted pendulum is a nonlinear, multivariate, strongly coupled unstable system, and studying it can effectively reflect many typical control problems. In this paper, a parameter self-tuning fuzzy controller is proposed to perform the balance control of a single rotating inverted pendulum. Particle swarm optimization is used to adjust its control parameters, and simulation experiments are performed to show that the system can achieve stability with the designed parametric self-tuning fuzzy controller, with control performance better than that of the conventional fuzzy controller. Furthermore, the leader-follower control strategy is used to realize the cooperative control of multiple rotating inverted pendulums. Two QUBE-Servo 2 rotating inverted pendulums are used for a cooperative pendulum swing-up experiment and stabilization experiment, and the effectiveness of the proposed cooperative control strategy is verified.
AB - The rotating inverted pendulum is a nonlinear, multivariate, strongly coupled unstable system, and studying it can effectively reflect many typical control problems. In this paper, a parameter self-tuning fuzzy controller is proposed to perform the balance control of a single rotating inverted pendulum. Particle swarm optimization is used to adjust its control parameters, and simulation experiments are performed to show that the system can achieve stability with the designed parametric self-tuning fuzzy controller, with control performance better than that of the conventional fuzzy controller. Furthermore, the leader-follower control strategy is used to realize the cooperative control of multiple rotating inverted pendulums. Two QUBE-Servo 2 rotating inverted pendulums are used for a cooperative pendulum swing-up experiment and stabilization experiment, and the effectiveness of the proposed cooperative control strategy is verified.
KW - cooperative control
KW - fuzzy control
KW - parameter self-tuning
KW - particle swarm optimization
UR - http://www.scopus.com/inward/record.url?scp=85164165062&partnerID=8YFLogxK
U2 - 10.20965/jaciii.2023.p0360
DO - 10.20965/jaciii.2023.p0360
M3 - Article
AN - SCOPUS:85164165062
SN - 1343-0130
VL - 27
SP - 360
EP - 371
JO - Journal of Advanced Computational Intelligence and Intelligent Informatics
JF - Journal of Advanced Computational Intelligence and Intelligent Informatics
IS - 3
ER -