This paper develops a fuzzy logic based position controller whose membership functions are tuned by genetic algorithm. The main goal is to ensure successful velocity and position trajectories tracking between the mobile robot and the virtual reference cart. The proposed fuzzy controller has two inputs and two outputs. The first input represents the distance between the mobile robot and the refe...

In Data Envelopment Analysis (DEA), it is assumed that the role of each factor is known asinput or output. However, in some cases, there are shared factors that their input versusoutput status is not clearly known. These are flexible measures. In such cases, determiningwhether a factor is input or output is ambiguous. Therefore, using fuzzy concept seems to benecessary.In this paper, a two phas...

this paper presents a delay compensator fuzzy control for trajectory tracking of omni-directional mobile robots. fuzzy logic control (flc) of the robots is a suitable strategy for dealing with model uncertainties, nonlinearities and disturbances.  on the other hand, in many robotic applications such as mobile robots, delay phenomenon is able to substantially deteriorate the behavior of system's...

Conventional fuzzy logic controller is applicable when there are only two fuzzy inputs with usually one output. Complexity increases when there are more than one inputs and outputs making the system unrealizable. The ordinal structure model of fuzzy reasoning has an advantage of managing high-dimensional problem with multiple input and output variables ensuring the interpretability of the rule ...

This paper provides a framework for integrating fuzzy expert systems with discrete event simulation, which will be utilized to enhance the input modeling process in discrete event simulation. Predicting the activity output (i.e. duration) using fuzzy expert systems will provide a new modeling feature to discrete event simulation. In previous studies, fuzzy set theory was mainly utilized to cont...