Interval-Type 3 Fuzzy Differential Evolution for Designing an Interval-Type 3 Fuzzy Controller of a Unicycle Mobile Robot (original) (raw)

Design Interval Type-2 Fuzzy Like (PID) Controller for Trajectory Tracking of Mobile Robot

Iraqi Journal of Computer, Communication, Control and System Engineering, 2019

One of the major problems in the field of mobile robots is the trajectory tracking problem. There are a big number of investigations for different control strategies that have been used to control the motion of the mobile robot when the nonlinear kinematic model of mobile robots was considered. The trajectory tracking control of autonomous wheeled mobile robot in a changing unstructured environment needs to take into account different types of uncertainties. Type-1 fuzzy logic sets present limitations in handling those uncertainties while type-2 fuzzy logic sets can manage these uncertainties to give a superior performance. This paper focuses on the design of interval type-2 fuzzy like proportional-integral-derivative (PID) controller for the kinematic model of mobile robot. The firefly optimization algorithm has been used to find the best values of controller’s parameters. The aim of this controller is trying to force the mobile robot tracking a pre-defined continuous path with min...

A hierarchical design approach for interval type-2 fuzzy controllers applied to mobile robots

This paper presents a novel hierarchical design approach for interval type-2 fuzzy logic controllers applied to mobile robots. The approach achieves an optimum interval type-2 fuzzy controller when uncertainty is present in the control loop, which is associated to the use of non-deterministic models in the design process. The method consists of three steps: the first one is intended to obtain a stable interval type-2 fuzzy controller as an initial design. The second one optimizes the control system response without uncertainty by using a type-1 fuzzy controller derived from type-2 design. The last one optimizes the control system behavior through an interval type-2 version of the type-1 fuzzy controller regarding the uncertainty sources affecting the control loop. The method is successfully validated in two different mobile robots. Simulation results for both problems show that the interval type-2 fuzzy controllers designed using this approach always exhibit better performance than optimal type-1 fuzzy controllers when different kind of uncertainties affect the robot platform.

Fuzzy Logic Tracking Control for Unicycle Mobile Robots

Engineering Letters, 2006

This paper addresses the problem of trajectory tracking control in an autonomous, wheeled, mobile robot of unicycle type using Fuzzy Logic. The Fuzzy Logic Control (FLC) is based on a backstepping approach to ensure asymptotic stabilization of the robot's position and orientation arou nd the desired trajectory, taking into account the kinematics and dynamics of the vehicle. We use the Mamdani inference system to construct a controller, with nine IF-THEN rules and the centroid of area method as our deffuzification strategy where the inpu t torques and velocities are considered as linguistic variab les. The performance of this FLC are illustrated in a simulation study.

Optimization of Fuzzy Logic Controller Used for a Differential Drive Wheeled Mobile Robot

Applied Sciences, 2021

The energy-efficient motion control of a mobile robot fueled by batteries is an especially important and difficult problem, which needs to be continually addressed in order to prolong the robot’s independent operation time. Thus, in this article, a full optimization process for a fuzzy logic controller (FLC) is proposed. The optimization process employs a genetic algorithm (GA) to minimize the energy consumption of a differential drive wheeled mobile robot (DDWMR) and still ensure its other performances of the motion control. The earlier approaches mainly focused on energy reduction by planning the shortest path whereas this approach aims to optimize the controller for minimizing acceleration of the robot during point-to-point movement and thus minimize the energy consumption. The proposed optimized controller is based on fuzzy logic systems. At first, an FLC has been designed based on the experiment and as well as an experience to navigate the DDWMR to a known destination by follow...