TELKOMNIKA Telecommunication Computing Electronics and Control
Neuro-fuzzy-based anti-swing control of automatic tower crane

TELKOMNIKA Telecommunication Computing Electronics and Control
Neuro-fuzzy-based anti-swing control of automatic tower crane

ANFIS controller
Fuzzy control
Fuzzy-tuned PID controller
Intelligent control
Tower crane

Controlling the position of the final load and the anti-swing control of the
loads during the operation of the tower crane are challenging tasks. These
are the most important control issues for safe operation, which are difficult
to achieve easily with conventional control systems. Hence, the need to
integrate the concepts of soft-computing into the tower crane control system.
The aim of this research work is to design an adaptive-network-based fuzzy
inference system (ANFIS) controller to move the payload to the final position
with the lowest possible swing angle. To evaluate the ability of the proposed
controller to meet the control requirements, its performance was compared to
three other controllers: a conventional proportional derivative (PD) controller,
a fuzzy-tuned PD controller and a fuzzy controller. MATLAB-based
computer simulations of the crane and controllers were carried out to verify
and compare the performance of the proposed controllers. The obtained
results show the effectiveness of the ANFIS-based controller in adjusting the
load position while keeping the load fluctuations small at the final position.
The load oscillation angle is about ±2.28° with the ANFIS controller while it
is about ±10° when using the PD controller. In addition, only one

Saleh B. Al-Tuhaifi, Kasim Mousa Al-Aubidy

http://telkomnika.uad.ac.id

Feb 16, 2023

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