Particle swarm optimization and spiral dynamic algorithm-based interval type-2 fuzzy logic control of triple-link inverted pendulum system : a comparative assessment

M. F., Masrom and N. M. A., Ghani and M. O., Tokhi (2021) Particle swarm optimization and spiral dynamic algorithm-based interval type-2 fuzzy logic control of triple-link inverted pendulum system : a comparative assessment. Journal of Low Frequency Noise, Vibration and Active Control, 40 (1). pp. 367-382. ISSN 1461-3484 (Print), 2048-4046 (Online). (Published)

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Abstract

This paper presents investigations into the development of an interval type-2 fuzzy logic control (IT2FLC) mechanism integrated with particle swarm optimization and spiral dynamic algorithm. The particle swarm optimization and spiral dynamic algorithm are used for enhanced performance of the IT2FLC by finding optimised values for input and output controller gains and parameter values of IT2FLC membership function as comparison purpose in order to identify better solution for the system. A new model of triple-link inverted pendulum on two-wheels system, developed within SimWise 4D software environment and integrated with Matlab/Simulink for control purpose. Several tests comprising system stabilization, disturbance rejection and convergence accuracy of the algorithms are carried out to demonstrate the robustness of the control approach. It is shown that the particle swarm optimization-based control mechanism performs better than the spiral dynamic algorithm-based control in terms of system stability, disturbance rejection and reduce noise. Moreover, the particle swarm optimization-based IT2FLC shows better performance in comparison to previous research. It is envisaged that this system and control algorithm can be very useful for the development of a mobile robot with extended functionality.

Item Type: Article
Additional Information: Indexed by WOS
Uncontrolled Keywords: Interval type-2 fuzzy logic control; Spiral dynamic algorithm; Particle swarm optimization
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Q Science > QA Mathematics > QA76 Computer software
T Technology > TK Electrical engineering. Electronics Nuclear engineering
Faculty/Division: Faculty of Electrical & Electronic Engineering
Institute of Postgraduate Studies
Depositing User: Mrs Norsaini Abdul Samat
Date Deposited: 19 Feb 2020 07:19
Last Modified: 29 Apr 2022 07:10
URI: http://umpir.ump.edu.my/id/eprint/25718
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