scholarly journals An Embedded Type-2 Fuzzy Controller for a Mobile Robot Application

10.5772/25573 ◽  
2011 ◽  
Author(s):  
Leonardo Leottau ◽  
Miguel Melgarejo
Keyword(s):  
Mobile Robot ◽  
Fuzzy Controller ◽  
Embedded Type

scholarly journals Navigation control of mobile robot using interval type-2 neural fuzzy controller optimized by dynamic group differential evolution

2018 ◽  
Vol 10 (1) ◽  
pp. 168781401775248 ◽  
Author(s):  
Tzu-Chao Lin ◽  
Chao-Chun Chen ◽  
Cheng-Jian Lin
Keyword(s):  
Mobile Robot ◽  
Differential Evolution ◽  
Fuzzy Controller ◽  
Dynamic Group ◽  
Unknown Environments ◽  
Navigation Control ◽  
Interval Type ◽  
Wall Following ◽  
Neural Fuzzy

This study developed and effectively implemented an efficient navigation control of a mobile robot in unknown environments. The proposed navigation control method consists of mode manager, wall-following mode, and towards-goal mode. The interval type-2 neural fuzzy controller optimized by the dynamic group differential evolution is exploited for reinforcement learning to develop an adaptive wall-following controller. The wall-following performance of the robot is evaluated by a proposed fitness function. The mode manager switches to the proper mode according to the relation between the mobile robot and the environment, and an escape mechanism is added to prevent the robot falling into the dead cycle. The experimental results of wall-following show that dynamic group differential evolution is superior to other methods. In addition, the navigation control results further show that the moving track of proposed model is better than other methods and it successfully completes the navigation control in unknown environments.

scholarly journals Optimization of Fuzzy Controller Using Galactic Swarm Optimization with Type-2 Fuzzy Dynamic Parameter Adjustment

Axioms ◽  
2019 ◽  
Vol 8 (1) ◽  
pp. 26 ◽  
Author(s):  
Emer Bernal ◽  
Oscar Castillo ◽  
José Soria ◽  
Fevrier Valdez
Keyword(s):  
Mobile Robot ◽  
Fuzzy Systems ◽  
Fuzzy Controller ◽  
Dynamic Parameter ◽  
Autonomous Mobile Robot ◽  
Dynamic Adjustment ◽  
Swarm Optimization ◽  
Galactic Swarm Optimization ◽  
Adjustment Of Parameters

Galactic swarm optimization (GSO) is a recently created metaheuristic which is inspired by the motion of galaxies and stars in the universe. This algorithm gives us the possibility of finding the global optimum with greater precision since it uses multiple exploration and exploitation cycles. In this paper we present a modification to galactic swarm optimization using type-1 (T1) and interval type-2 (IT2) fuzzy systems for the dynamic adjustment of the c3 and c4 parameters in the algorithm. In addition, the modification is used for the optimization of the fuzzy controller of an autonomous mobile robot. First, the galactic swarm optimization is tested for fuzzy controller optimization. Second, the GSO algorithm with the dynamic adjustment of parameters using T1 fuzzy systems is used for the optimization of the fuzzy controller of an autonomous mobile robot. Finally, the GSO algorithm with the dynamic adjustment of parameters using the IT2 fuzzy systems is applied to the optimization of the fuzzy controller. In the proposed approaches, perturbation (noise) was added to the plant in order to find out if our approach behaves well under perturbation to the autonomous mobile robot plant; additionally, we consider our ability to compare the results obtained with the approaches when no perturbation is considered.

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