Interval Type-2 Fuzzy Logic Modeling and Control of a Mobile Two-Wheeled Inverted Pendulum

2018 ◽  
Vol 26 (4) ◽  
pp. 2030-2038 ◽  
Author(s):  
Jian Huang ◽  
MyongHyok Ri ◽  
Dongrui Wu ◽  
Songhyok Ri
Keyword(s):  
Fuzzy Logic ◽  
Inverted Pendulum ◽  
Modeling And Control ◽  
Logic Modeling ◽  
Fuzzy Logic Modeling ◽  
Wheeled Inverted Pendulum ◽  
Interval Type ◽  
And Control

Finishing mill strip gage setup and control by interval type-1 non-singleton type-2 fuzzy logic systems

2014 ◽  
Vol 24 ◽  
pp. 900-911 ◽  
Author(s):  
Gerardo M. Méndez ◽  
Oscar Castillo ◽  
Rafael Colás ◽  
Héctor Moreno
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Systems ◽  
Finishing Mill ◽  
Logic Systems ◽  
Interval Type ◽  
And Control

scholarly journals Genetic Algorithm and Particle Swarm Optimization Based Cascade Interval Type 2 Fuzzy PD Controller for Rotary Inverted Pendulum System

2015 ◽  
Vol 2015 ◽  
pp. 1-15 ◽  
Author(s):  
Mukhtar Fatihu Hamza ◽  
Hwa Jen Yap ◽  
Imtiaz Ahmed Choudhury
Keyword(s):  
Genetic Algorithm ◽  
Particle Swarm Optimization ◽  
Steady State ◽  
Control Strategy ◽  
Inverted Pendulum ◽  
Swarm Optimization ◽  
Interval Type ◽  
And Control ◽  
Rotary Inverted Pendulum

This paper presents the design of an optimized Interval Type 2 Fuzzy Proportional Derivative Controller (IT2F-PDC) in cascade form for Rotary Inverted Pendulum (RIP) system. The parameters of the IT2F-PDC are optimised by using Genetic Algorithm (GA) and Particle Swarm Optimization (PSO). The goal is to balance the pendulum in upright unstable equilibrium position. The IT2F-PDC which is the extended version of conventional type 1 fuzzy logic controller, improves the control strategy by using the advantage of its footprint of uncertainty for the fuzzy membership function. The performance characteristics considered for the controller are steady state error, settling time, rise time, maximum overshoot, and control energy. Experimental and simulation results indicated that the effectiveness and robustness of the proposed GA- and PSO-based controllers on the RIP with respect to load disturbances, parameter variation, and noise effects have been improved over state-of-the-art method. However, the comparative results for simulation and experiment based on cascade IT2F-PDC indicate that GA-based IT2F-PDC has lower steady state error while PSO-based IT2F-PDC has lower overshoot, settling time, and control energy, but both have almost the same rise time. The proposed control strategy can be regarded as a promising strategy for controlling different unstable and nonlinear systems.

scholarly journals Hybrid Genetic Manta Ray Foraging Optimization and Its Application to Interval Type 2 Fuzzy Logic Control of An Inverted Pendulum System

2020 ◽  
Vol 917 ◽  
pp. 012082
Author(s):  
Ahmad Azwan bin Abdul Razak ◽  
Ahmad Nor Kasruddin bin Nasir ◽  
Nor Maniha Abdul Ghani ◽  
Shuhairie Mohammad ◽  
Mohd Falfazli Mat Jusof ◽  
...  
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Control ◽  
Inverted Pendulum ◽  
Pendulum System ◽  
Logic Control ◽  
Inverted Pendulum System ◽  
Interval Type ◽  
Manta Ray

Finishing mill thread speed set-up and control by interval type 1 non-singleton type 2 fuzzy logic systems

2012 ◽  
Vol 39 (5) ◽  
pp. 342-354 ◽  
Author(s):  
G M Méndez ◽  
R Colás ◽  
L Leduc ◽  
I Lopez-Juarez ◽  
R Longoria
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Systems ◽  
Finishing Mill ◽  
Logic Systems ◽  
Set Up ◽  
Interval Type ◽  
And Control
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